Network effects

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pages: 421 words: 110,406

Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You by Sangeet Paul Choudary, Marshall W. van Alstyne, Geoffrey G. Parker

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Sacks’s napkin sketch captures a classic example of network effects. It shows how the value of Uber to each of its participants grows the more people use it—which attracts still more users, thereby increasing the value of the service even more. Network effects refers to the impact that the number of users of a platform has on the value created for each user. Positive network effects refers to the ability of a large, well-managed platform community to produce significant value for each user of the platform. Negative network effects refers to the possibility that the growth in numbers of a poorly-managed platform community can reduce the value produced for each user. As we’ll see, positive network effects are the main source of value creation and competitive advantage in a platform business. However, network effects can also be negative, and in this chapter we’ll explain how and why negative network effects arise and what platform business managers can do about them.

And while platform businesses themselves are often extraordinarily profitable, the chief locus of wealth creation is now outside rather than inside the organization. Network effects are creating the giants of the twenty-first century. Google and Facebook each touch more than one-seventh of the world’s population. In the world of network effects, ecosystems of users are the new source of competitive advantage and market dominance. TAKEAWAYS FROM CHAPTER TWO Whereas giant industrial-era firms were made possible by supply economies of scale, today’s giants are made possible by demand economies of scale—expressed as network effects. Network effects are not the same as price effects, brand effects, or other familiar growth-building tools. Frictionless entry and other features of scalability maximize the value-building impact of network effects. A two-sided market (with both producers and consumers) gives rise to four kinds of network effects: same-side effects (positive and negative) and cross-side effects (positive and negative).

., despite competitive markets and the regulatory pressure created by antitrust legislation, a handful of firms dominate industries in which supply economies of scale play a large role—for example, the auto industry. As we also saw in chapter 2, network effects are the Internet-era source of market power. Thanks to positive network effects, the value created and the profit margins enjoyed by the company both increase as more users join the ecosystem.21 This is why firms with network effects can enjoy a 10x multiple in value relative to other firms that have comparable revenues but lack network effects.22 With their current product focus and business models, Houghton Mifflin Harcourt, NBC, Lexis, and Whirlpool do not have strong network effects. Amazon, Netflix, LegalZoom, and Nest do. Because positive network effects attract more users to whichever platform is larger, they are a second force that is likely to strengthen a market’s winner-take-all tendency.


pages: 302 words: 73,581

Platform Scale: How an Emerging Business Model Helps Startups Build Large Empires With Minimum Investment by Sangeet Paul Choudary

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Lowering investment ensures higher ROI and greater participation from producers, which ensures that the platform’s core interaction is highly repeatable. 3.4 THE CREATION OF CUMULATIVE VALUE Lock-In For An Opt-In World The power of network effects cannot be disputed. As platforms gather more value through external production, they attract more consumption, which in turn attracts even more production. Network effects guarantee repeatable interactions. Both producers and consumers repeatedly participate on a platform that has strong network effects. Network effects hold the keys to the long-term retention of producers and consumers, which increases the repeatability of the core interaction. But today, the power of the network effect is fading. The network effect isn’t the one-stop solution for repeatable interactions that it once was. SUFFICIENT NETWORK EFFECT Platforms with network effects often benefit from a winner-takes-all dynamic. The winner usually aggregates all producers and consumers onto one platform because of ever-strengthening network effects.

Such use cases are best supported by the platform itself, acting as a producer through a captive base of partner producers. 4.9 DISRUPTING CRAIGSLIST Quality As A Competitive Advantage Question: Why does Craigslist refuse to get disrupted, despite poor user experience and an utter lack of innovation? Answer: Strong Network Effects THREE FACTORS GOVERNING PLATFORM ADOPTION The success of platforms depends on the following three factors: 1.Network Effects. The single most important factor for a platform is its ability to build the network effect. Without a minimum number of buyers and sellers, platforms simply are not valuable enough. With network effects, a platform continues to attract producers and consumers sustainably. 2.Curation Of Content. The platform should have a mechanism for separating signal from noise. Owing to network effects, platforms encourage abundance, and users need a mechanism to sift through the abundance and find the most relevant items. Platforms should have a mechanism to reliably and credibly signal quality to consumers. 3.Curation Of Participants.

A scaling strategy for platforms should involve: 1.Scaling of production 2.Scaling of consumption 3.Strengthening of filters through ongoing data acquisition 4.Scaling social curation 5.Scaling community culture 6.Minimizing interaction risk There are significant management challenges when scaling a network effects platform, which are often underestimated. The above framework helps platforms scale in a manner that ensures repeatability and sustainability of the core interaction. 6.2 REVERSE NETWORK EFFECTS Why Scale May Be The Biggest Threat To Platforms Platforms may lose value as they scale. Scale, in fact, may be the greatest threat to platforms, if not managed well. As noted in the previous chapter, a failure in any one of the four actions – Creation, Curation, Customization, and Consumption – may lead to a failure of the core interaction. When one or more of these actions start to fail with increasing scale, we see the onset of reverse network effects. Network effects make a platform useful as more users use it, however, beyond a certain scale, network effects may work against the platform.


pages: 383 words: 81,118

Matchmakers: The New Economics of Multisided Platforms by David S. Evans, Richard Schmalensee

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Airbnb, Alvin Roth, big-box store, business process, cashless society, Chuck Templeton: OpenTable, creative destruction, Deng Xiaoping, if you build it, they will come, information asymmetry, Internet Archive, invention of movable type, invention of the printing press, invention of the telegraph, invention of the telephone, Jean Tirole, John Markoff, Lyft, M-Pesa, market friction, market microstructure, mobile money, multi-sided market, Network effects, Productivity paradox, profit maximization, purchasing power parity, QR code, ride hailing / ride sharing, sharing economy, Silicon Valley, Snapchat, Steve Jobs, Tim Cook: Apple, transaction costs, two-sided market, Uber for X, Victor Gruen, winner-take-all economy

As Rochet and Tirole realized in their pioneering paper, “[M]any, if not most markets with network externalities are characterized by the presence of two distinct sides whose ultimate benefit stems from interacting through a common platform.”7 The French economists pointed to the general significance of indirect network effects. A network effect is indirect when the value of a matchmaker to one group of customers depends on how many members of a different group participate. FIGURE 2-1 Mentions of “network effect(s)” and “first-mover advantage,” 1950–2008 Note: Both Ngrams are case-insensitive. The Ngram for “network effect(s)” includes both the singular and plural. The Ngram for “first-mover advantage” includes both the hyphenated and unhyphenated forms. The units for both axes are per 10 million, e.g., a value of 32 for “network effect(s)” indicates that 32 bigrams per 10 million bigrams (two-word phrases) in the Google Book database were “network effects.” The importance of indirect network effects is obvious, at least in retrospect, when a business has two distinct types of customers who desire to interact with each other.

The new economics of multisided platforms has revealed why that, and a lot of other business advice, is often wrong when it comes to most businesses that have what economists call network effects, in which adding customers attracts other customers.2 The Great Network Effects Mistake Economists started the serious study of network effects in the early 1970s. That work gained momentum in the 1980s. By the time entrepreneurs were starting dot-coms in the mid-1990s, there was an extensive academic literature. Business writers had latched onto the concept. Simple versions of network effects seeped into popular writings along with simplistic strategic advice. Unfortunately, right around the time dot-commers in Silicon Valley were being told they should build market share as quickly as possible, Rochet and Tirole in Toulouse were realizing that network effects were much more complicated, and different in practice, than many economists had thought.

A better two-sided strategy made the difference. Mastering Multifaceted Network Effects It turns out that networks effects are far more pervasive and complex than economists and business strategists thought they were before 2000. Rochet and Tirole’s deep insight that year was that businesses in a diverse range of industries faced indirect network effects. The way they built their businesses, designed their products, ran their operations, and priced their offerings were heavily influenced by these network effects. These businesses operated multisided platforms. Economists, including ourselves, then started studying how these firms and industries worked in fact. It soon became apparent that much of the received wisdom about network effects was wrong. The first-mover advantage and winner-take-all theories, for example, were shaky at best.


pages: 510 words: 120,048

Who Owns the Future? by Jaron Lanier

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3D printing, 4chan, Affordable Care Act / Obamacare, Airbnb, augmented reality, automated trading system, barriers to entry, bitcoin, book scanning, Burning Man, call centre, carbon footprint, cloud computing, commoditize, computer age, crowdsourcing, David Brooks, David Graeber, delayed gratification, digital Maoism, Douglas Engelbart, en.wikipedia.org, Everything should be made as simple as possible, facts on the ground, Filter Bubble, financial deregulation, Fractional reserve banking, Francis Fukuyama: the end of history, George Akerlof, global supply chain, global village, Haight Ashbury, hive mind, if you build it, they will come, income inequality, informal economy, information asymmetry, invisible hand, Jacquard loom, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Khan Academy, Kickstarter, Kodak vs Instagram, life extension, Long Term Capital Management, Marc Andreessen, Mark Zuckerberg, meta analysis, meta-analysis, Metcalfe’s law, moral hazard, mutually assured destruction, Network effects, new economy, Norbert Wiener, obamacare, packet switching, Peter Thiel, place-making, Plutocrats, plutocrats, Ponzi scheme, post-oil, pre–internet, race to the bottom, Ray Kurzweil, rent-seeking, reversible computing, Richard Feynman, Richard Feynman, Ronald Reagan, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, smart meter, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, Ted Nelson, The Market for Lemons, Thomas Malthus, too big to fail, trickle-down economics, Turing test, Vannevar Bush, WikiLeaks, zero-sum game

CHAPTER 13 Coercion on Autopilot Specialized Network Effects Rewarding and Punishing Network EffectsNetwork effects” are feedback cycles that can make a network become ever more influential or valuable.* A classic example is found in the rise of Facebook. It attracted people because of the people already on it, a little like the old joke about someone being famous for being famous. *Network effects were an obsession for those interested in the pre-digital phone system. They have become an even greater obsession in the age of digital networks. Metcalf’s Law is a famous claim that a network becomes as valuable as the square of the number of its nodes. That means value climbs with an insane, ever-increasing pitch as a network grows. The economist W. Brian Arthur pioneered the understanding of economic network effects. To understand how Siren Servers work, it’s useful to divide network effects into those that are “rewarding” and those that are “punishing.”

To understand how Siren Servers work, it’s useful to divide network effects into those that are “rewarding” and those that are “punishing.” Siren Servers gain dominance through rewarding network effects, but keep dominance through punishing network effects. Here’s a classic example of a rewarding network effect: A cliché in the advertising world is that in the old days you knew you were wasting half of your advertising budget, but you didn’t know which half. For instance, you’d spend tens of millions of dollars on TV and print ads, and somehow there would be a benefit, but you never knew exactly how or why. Surely many of the ads were playing when people were going to the bathroom, laying waste to your precious spend. An oft-repeated trope goes like this: Because of all of Google’s data and placement algorithms, an advertiser can now finally know which half is waste.

This will happen to only a tiny token number of people, though. It is really you, the proprietor of the Siren Server, who will benefit above all others. At first, all you’ll have is rewarding network effect. That means that people will benefit from using your server because other people are using it. A virtuous cycle causes more and more people to use your offering. That’s not enough, however, if you want to build a world-class, persistent Siren Server. In addition, you have to inject some sort of punishing network effect. Make Others Pay for Entropy Once both rewarding and punishing network effects are taking hold, another crucial task is to make sure that risk is being radiated out to other people and institutions, and not accruing to your server. Sites like Pinterest invariably demand that users click through an agreement that places all responsibility for copyright violations or anything else squarely on the user.


pages: 472 words: 117,093

Machine, Platform, Crowd: Harnessing Our Digital Future by Andrew McAfee, Erik Brynjolfsson

3D printing, additive manufacturing, AI winter, Airbnb, airline deregulation, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, backtesting, barriers to entry, bitcoin, blockchain, book scanning, British Empire, business process, carbon footprint, Cass Sunstein, centralized clearinghouse, Chris Urmson, cloud computing, cognitive bias, commoditize, complexity theory, computer age, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Dean Kamen, discovery of DNA, disintermediation, distributed ledger, double helix, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, ethereum blockchain, everywhere but in the productivity statistics, family office, fiat currency, financial innovation, George Akerlof, global supply chain, Hernando de Soto, hive mind, information asymmetry, Internet of things, inventory management, iterative process, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, joint-stock company, Joseph Schumpeter, Kickstarter, law of one price, Lyft, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Marc Andreessen, Mark Zuckerberg, meta analysis, meta-analysis, moral hazard, multi-sided market, Myron Scholes, natural language processing, Network effects, new economy, Norbert Wiener, Oculus Rift, PageRank, pattern recognition, peer-to-peer lending, performance metric, Plutocrats, plutocrats, precision agriculture, prediction markets, pre–internet, price stability, principal–agent problem, Ray Kurzweil, Renaissance Technologies, Richard Stallman, ride hailing / ride sharing, risk tolerance, Ronald Coase, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Pinker, supply-chain management, TaskRabbit, Ted Nelson, The Market for Lemons, The Nature of the Firm, Thomas L Friedman, too big to fail, transaction costs, transportation-network company, traveling salesman, two-sided market, Uber and Lyft, Uber for X, Watson beat the top human players on Jeopardy!, winner-take-all economy, yield management, zero day

For the simple reason that many of the people with whom they wanted to exchange messages already used WhatsApp, so they too had to adopt it. This is a clear example of what economists call a “network effect”: the fact that some goods, like WhatsApp, become more valuable to each user as more people use them. The economics of network effects are central to understanding business success in the digital world and were worked out in a series of papers in the 1980s,‡‡ which is, not coincidentally, when modern computer networks and digital software started becoming especially important economically. Network effects are also called demand-side economies of scale,§§ and as the WhatsApp example shows, they can be extremely compelling—so compelling that in 2014, Facebook paid $22 billion to acquire the company.

To see the importance of network effects, imagine an app, call it “WhatsWrong,” that was identical in all its functionality and user experience design to WhatsApp, except it had zero users. How much do you think Facebook, or anyone else, would pay for WhatsWrong? WhatsApp shows that network effects arise in part because of the choices made by platform creators. If the app’s developers had decided to make their creation easily interoperable with established SMS networks, users of these networks would have switched over to WhatsApp for cost reasons only, if at all. As the app grew in popularity, however, SMS users increasingly felt left out, so they became more likely to turn their backs on the old messaging technology in favor of the new one. And as more and more of them did this, the network effects grew stronger.

Third, switching costs make it attractive to invest heavily in growing the network in the early stages of adoption, to bring on more users and riders. Uber’s investors are making the bet that the (two-sided) network effects and switching costs are large enough to make it worth investing billions of dollars to encourage adoption of the platform by both riders and drivers. Their strategy is complicated by the fact that geographically distinct markets each have their own local network effects. If you’re hailing a ride in Beijing, it makes little difference if Uber has lots of drivers in New York or New Delhi. The battle isn’t one big winner-take-all contest, but hundreds of separate ones, with only weak network effects across different geographies. They’re winning some and losing others. As it works to build its platform, Uber has two huge advantages. The first is a set of deep-pocketed and patient investors, who are willing to cover Uber’s costs while it scales.


pages: 375 words: 88,306

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism by Arun Sundararajan

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3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, basic income, bitcoin, blockchain, Burning Man, call centre, collaborative consumption, collaborative economy, collective bargaining, commoditize, corporate social responsibility, cryptocurrency, David Graeber, distributed ledger, employer provided health coverage, Erik Brynjolfsson, ethereum blockchain, Frank Levy and Richard Murnane: The New Division of Labor, future of work, George Akerlof, gig economy, housing crisis, Howard Rheingold, information asymmetry, Internet of things, inventory management, invisible hand, job automation, job-hopping, Kickstarter, knowledge worker, Kula ring, Lyft, Marc Andreessen, megacity, minimum wage unemployment, moral hazard, moral panic, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, peer-to-peer rental, profit motive, purchasing power parity, race to the bottom, recommendation engine, regulatory arbitrage, rent control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart contracts, Snapchat, social software, supply-chain management, TaskRabbit, The Nature of the Firm, total factor productivity, transaction costs, transportation-network company, two-sided market, Uber and Lyft, Uber for X, universal basic income, Zipcar

As Burnham further clarifies about OpenBazaar in his blog post, “There is no way for a central authority to leverage network effect market power to extract rents from the participants.”5 At a time when most venture capitalists seem to be plowing money into sharing economy platforms that are able to do precisely what Burnham claimed OpenBazaar made impossible (i.e., “leverage network effect market power to extract rents from the participants”), why would a visible and successful venture capitalist like USV want to invest in a company aimed at furthering a technology that is not only, in a sense, “off the grid,” but is also open-source and committed to “zero fees.” Burnham explains further: This begs the question of how OB1 can be a for profit business that will generate a return on the investment we are announcing today. How can a business that is consciously architected to undo network effect defensibility, one that is tearing down the walls and filling in the moats that every paper on market based competition has insisted are necessary for success … succeed.

But it’s fascinating: there’s a real chance that the economic models of crowd-based capitalism may actually be able to distribute production across millions of smaller providers without having to sacrifice significantly on the gains from scale that 20th-century organizations enjoyed. In contrast, it seems unequivocally clear that demand-side economies of scale will become more prevalent as crowd-based capitalism gathers steam. A particular kind of network effect—the two-sided network effect—governs many economic aspects of platforms. As Thomas Eisenmann, Geoffrey Parker, and Marshall Van Alstyne explain in an influential Harvard Business Review article: With two-sided network effects, the platform’s value to any given user largely depends on the number of users on the network’s other side. Value grows as the platform matches demand from both sides. For example, video game developers will create games only for platforms that have a critical mass of players, because developers need a large enough customer base to recover their upfront programming costs.

In contrast, it is completely conceivable that all of Uber’s drivers in New York could collectively switch to a different platform (or start one of their own), eventually taking all of the demand with them. Now let’s contrast the network effects of Uber with those enjoyed by Airbnb. Again, this is a market in which supply has to be built out market by market, in thousands of different cities and towns. But the “network” benefits from hosts in Paris extend far beyond the Paris consumers. This is because unlike local transport, short-term accommodation is sought primarily by travelers rather than by local residents. You favor a platform that can get you accommodation anywhere in the world, rather than one that specializes in one city. Thus, on the Airbnb platform, network effects are more resilient. In a sense, the “fractal” structure of the network effects in both these examples makes their economics more complex than those of traditional two-sided markets, potentially making them either stronger or weaker.


pages: 193 words: 47,808

The Flat White Economy by Douglas McWilliams

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access to a mobile phone, banking crisis, Big bang: deregulation of the City of London, bonus culture, Chuck Templeton: OpenTable, cleantech, cloud computing, computer age, correlation coefficient, Edward Glaeser, en.wikipedia.org, Erik Brynjolfsson, eurozone crisis, George Gilder, hiring and firing, income inequality, informal economy, knowledge economy, loadsamoney, low skilled workers, mass immigration, Metcalfe’s law, Network effects, new economy, offshore financial centre, Pareto efficiency, Peter Thiel, Productivity paradox, Robert Metcalfe, Silicon Valley, smart cities, special economic zone, Steve Jobs, working-age population, zero-sum game

In my experience, supereconomies of scale have tended to mean that large changes tend to be delayed while incremental improvements tend to be accelerated to keep ahead of competition. The other economic factor that affected the timing with which the digital economy bore fruit is its sensitivity to network effects. Network effects are a phenomenon common to communications systems. Essentially, the value of a network to an individual participant in that network increases with the number of participants in it. So a single telephone is of no use on its own – it only gains some value when there is a second phone. And as the value of each phone increases, the more phones tend to become available to contact on the network, until there are so many other connections that the value of an additional connection is negligible. Network effects were first developed as a concept by the President of Bell Telephones in making his case for a monopoly in 1908, but the ideas were developed and refined in the 1980s and 1990s.

Robert Metcalfe, one of the co-inventors of the Ethernet, was the progenitor of Metcalfe’s Law – that the value of a communications network varied with the square of the number of connections in the network. This idea was vigorously promoted by the economic guru George Gilder2 during the 1990s. Where there are network effects, investment typically doesn’t take place until there is a critical mass of potential users. Network effects tend to cause investment to be held back in a similar fashion to supereconomies of scale, although in the case of the latter, the tendency to delay investment is moderated by the possibility of gaining first-mover advantage. It is the combination of supereconomies of scale and network effects that meant that the economic exploitation of the digital technologies took place on a different, tardier timetable than that which had been predicted by those who only understood the technological issues.3 Online retail and marketing Internet usage in most Western economies really took off during the first decade of the 21st century.

‘London Key Facts and Statistics’ produced by the Association of London Councils claims that London is one of the world’s most diverse cities ethnically,29 quoting ONS neighbourhood statistics based on the 2011 Census. It also claims that “London has the largest number of community languages spoken in Europe. Over 300 languages are spoken in London schools”. Not only did London have a long-established skill base in advertising and marketing, but it had a massive supply of diverse and creative young people, many of them looking for work. Once the impediments of those supereconomies of scale and the network effects described earlier had been overcome, and once online retail and marketing began to take off, London was in prime position towards the end of the 21st century’s first decade. It all percolated together and hey presto, we had the Flat White Economy. CHAPTER 3 What is the Flat White Economy and where is it based? The epicentre of the Flat White Economy is the London postal district known as EC1V.


pages: 218 words: 44,364

The Starfish and the Spider: The Unstoppable Power of Leaderless Organizations by Ori Brafman, Rod A. Beckstrom

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Atahualpa, barriers to entry, Burning Man, creative destruction, disintermediation, experimental economics, Firefox, Francisco Pizarro, jimmy wales, Kibera, Lao Tzu, Network effects, peer-to-peer, pez dispenser, shareholder value, Silicon Valley, Skype, The Wisdom of Crowds, union organizing

How hard is it to start an online classified ad site? Not very. Size matters. The small rule. RULE 2: The Network Effect The network effect is the increase in the overall value of the network with the addition of each new member. Each additional telephone or fax machine makes all the other phones or fax machines in the world more worthwhile. Historically, creating the network effect could be tough. The fax network had to be built one expensive fax machine at a time. Starfish organizations, however, are particularly well positioned to take advantage of the network effect. For some of the most successful starfish organizations, like Skype and craigslist, it costs absolutely nothing to add a new customer. While it used to cost millions or billions to create a significant network effect, for many starfish organizations the cost has gone down to zero.

Buyers were reluctant to switch to a new auction site where sellers didn't have a proven track record; they preferred to stay at eBay. Likewise, sellers with established positive ratings on eBay had a huge incentive to stay on the site rather than go elsewhere and start anew. For one thing, they were able to fetch premium prices based on their established reputations. They also had an incentive to stay where the buyers were. In addition, eBay benefited from what's called the "network effect." Say there's only one telephone in the world. It's not going to be worth much, right? After all, who are you going to call? But when there are two telephones, their value goes up dramatically. Each additional telephone adds value to the overall phone system. Likewise, eBay's network becomes more valuable with each new user rating. One user rating doesn't do anyone much good. But millions of ratings on millions of users have immense value.

While it used to cost millions or billions to create a significant network effect, for many starfish organizations the cost has gone down to zero. Often without spending a dime, starfish organizations create communities where each new member adds value to the larger THE NEW WORLD network. With every new eMule user, there's more music to be shared. Every new site on the World Wide Web makes the whole network richer with information. Companies like eBay have used the network effect not only to survive but to thrive: buyers and sellers have stayed loyal to the site because of the value of network. RULE 3: The Power of Chaos As you read this, parents worldwide are beseeching their kids to clean their rooms. "How can you get anything done in this mess?" they ask. Similarly, the conventional thinking is that to run an organization you'd better be organized and structured. But in the decentralized world, messy kids can rejoice. It pays to be chaotic.


pages: 270 words: 79,180

The Middleman Economy: How Brokers, Agents, Dealers, and Everyday Matchmakers Create Value and Profit by Marina Krakovsky

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Affordable Care Act / Obamacare, Airbnb, Al Roth, Black Swan, buy low sell high, Chuck Templeton: OpenTable, Credit Default Swap, cross-subsidies, crowdsourcing, disintermediation, diversified portfolio, experimental economics, George Akerlof, Goldman Sachs: Vampire Squid, income inequality, index fund, information asymmetry, Jean Tirole, Kenneth Arrow, Lean Startup, Lyft, Marc Andreessen, Mark Zuckerberg, market microstructure, Martin Wolf, McMansion, Menlo Park, Metcalfe’s law, moral hazard, multi-sided market, Network effects, patent troll, Paul Graham, Peter Thiel, pez dispenser, ride hailing / ride sharing, Robert Metcalfe, Sand Hill Road, sharing economy, Silicon Valley, social graph, supply-chain management, TaskRabbit, The Market for Lemons, too big to fail, trade route, transaction costs, two-sided market, Uber for X, ultimatum game, Y Combinator

Because buyers usually want to be where sellers are, and sellers usually want to be where buyers are, a two-sided network with an abundance of participants on one side tends to attract more comers on the other side. In the language of economics—and increasingly of tech investors—two-sided markets usually create “indirect network effects.”36 As one side grows, the network becomes more attractive to the other side, and as the other side grows, it attracts more users who want to connect with that side. This positive feedback loop promotes rapid growth once you reach critical mass. That’s why tech investors love network effects. But this same growth curve means two-sided markets are extremely hard to get off the ground, as Thiers found out firsthand: how do you get a sitter to sign up for a service that doesn’t have a single parent, and likewise, how do you get a parent to sign up for a service that has no sitters?

In fact, without a good system in place to keep diners accountable, OpenTable would have a hard time getting restaurants to become customers in the first place. So Templeton and his team had a strong incentive to create rules to minimize no-shows. Rules for proper behavior are a crucial element of any middleman business that hopes to attract enough partners on both sides. In writing about SitterCity in the Bridge chapter, I pointed out that two-sided markets benefit from network effects, whereby buyers want to be where sellers are and sellers want to be where buyers are. But network effects aren’t just about quantity (the more the merrier)—usually, buyers care about the quality of sellers, too, and sellers care something about the quality of buyers.10 If you go on a dating site or a singles event, for example, you don’t just care about how many potential partners there will be, but also whether they’re the sort of people you want to meet.

Brian Arthur, “Competing Technologies, Increasing Returns, and Lock-In By Historical Events,” The Economic Journal 99, no. 394 (March 1989). A less academic account of these ideas by the same author is W. Brian Arthur, “Increasing Returns and the New World of Business,” Harvard Business Review 74, no. 4 (July/August 1996): 100–109. 36.These are called “indirect” because they refer to what is happening on the other side; direct network effects occur if users care how many other users are on the same side as they are. In addition, not all two-sided markets produce positive indirect network effects, and growth on one side can actually be a turnoff to the other side. For example, advertisers want to be where many readers in their target audience are, but readers aren’t nearly as eager to see ads, so a media company can often attract a larger audience if it doesn’t show ads. Whether the media company makes more money that way, though, is another story: the company might be better off taking ads, investing the ad revenue into higher quality, which can attract more readers. 37.For one discussion of this challenge, see David S.


pages: 222 words: 70,132

Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy by Jonathan Taplin

1960s counterculture, 3D printing, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, American Legislative Exchange Council, Apple's 1984 Super Bowl advert, back-to-the-land, barriers to entry, basic income, battle of ideas, big data - Walmart - Pop Tarts, bitcoin, Brewster Kahle, Buckminster Fuller, Burning Man, Clayton Christensen, commoditize, creative destruction, crony capitalism, crowdsourcing, data is the new oil, David Brooks, David Graeber, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, equal pay for equal work, Erik Brynjolfsson, future of journalism, future of work, George Akerlof, George Gilder, Google bus, Hacker Ethic, Howard Rheingold, income inequality, informal economy, information asymmetry, information retrieval, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kickstarter, labor-force participation, life extension, Marc Andreessen, Mark Zuckerberg, Menlo Park, Metcalfe’s law, Mother of all demos, move fast and break things, move fast and break things, natural language processing, Network effects, new economy, Norbert Wiener, offshore financial centre, packet switching, Paul Graham, Peter Thiel, Plutocrats, plutocrats, pre–internet, Ray Kurzweil, recommendation engine, rent-seeking, revision control, Robert Bork, Robert Gordon, Robert Metcalfe, Ronald Reagan, Sand Hill Road, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, smart grid, Snapchat, software is eating the world, Steve Jobs, Stewart Brand, technoutopianism, The Chicago School, The Market for Lemons, Tim Cook: Apple, trade route, transfer pricing, trickle-down economics, Tyler Cowen: Great Stagnation, universal basic income, unpaid internship, We wanted flying cars, instead we got 140 characters, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator

Thiel says, “It’s always a red flag when entrepreneurs talk about getting 1% of a $100 billion market.” He wanted to invest in monopolies, not competitive businesses. 2. Build businesses that have “network effects.” Thiel’s first two major investments, PayPal and Facebook, both benefit from having millions of users who want to connect with each other. When PayPal was just a payment system for Palm Pilot, it was a failure. As soon as it became the standard payment system for eBay, it got the network-effect wind at its back. 3. Economies of scale are critical. Google is pretty much unassailable in search-engine advertising because it has huge economies of scale. This leads to the conclusion that there will be very few winners in each sector of tech. The combination of scale and network effects makes it very hard to dislodge the winners, especially if you are in a business like tech, which is so lightly regulated. 4.

The brand promise also helps you defend yourself against government intrusion. Google’s original “Don’t be evil” brand promise gave them a patina of social entrepreneurship that helps protect them from accusations of monopoly power tactics. As John Seely Brown has pointed out, the end of the decentralized Web that Engelbart and the PARC visionaries had imagined occurs at this point, when “we moved from products to platforms, which let the network effect play out in a hub and spoke model.” From this point on the economies of scale enjoyed by a platform whose users are measured in the billions becomes the ultimate metric for success. Thiel understood this, and from PayPal, the original founding group began to spread through Silicon Valley after eBay’s $1 billion acquisition of the company. Even companies not funded by Thiel adopted his unique view of capitalism.

North Dakota that “the lack of a physical presence in a state is sufficient grounds to exempt a corporation from having to pay sales and use taxes to a state.” For Bezos, who studied the growth of the Internet while at Shaw, a light went on. He began to imagine an online retailer that could totally disrupt the local bookstore business. His principles were very similar to Thiel’s four guidelines. First he would build a proprietary online platform (even going so far as to patent “one-click” ordering). Then he would harness the network effect, using user recommendations to build individual taste profiles of every customer. He would also create economies of scale by buying in bulk from publishers and negotiating the lowest prices, which individual bookstores could not match. In this effort he could use the wholesaler Ingram in order to list those titles he was not buying from publishers, thereby dramatically expanding the number of books he could offer on Amazon and still avoid charging sales tax.


pages: 169 words: 56,250

Startup Communities: Building an Entrepreneurial Ecosystem in Your City by Brad Feld

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barriers to entry, cleantech, cloud computing, corporate social responsibility, Grace Hopper, job satisfaction, Kickstarter, labour mobility, Lean Startup, minimum viable product, Network effects, Peter Thiel, place-making, pre–internet, Richard Florida, Ruby on Rails, Silicon Valley, Silicon Valley startup, smart cities, software as a service, Steve Jobs, text mining, Y Combinator, zero-sum game, Zipcar

As more and more startups in an area can share the costs of specialized inputs, the average cost per startup drops for the specialized inputs. This provides direct economic benefit to companies located within a startup community. Another economic concept, network effects, explains why geographic concentration yields further advantage. Network effects operate in systems where the addition of a member to a network enhances value for existing users. The Internet, Facebook, and Twitter are examples in which network effects operate powerfully. These services may have some value to you if there are just 100 other users. However, these networks are immensely more useful if there are 100 million other users that you can connect with. Startup communities similarly feature strong network effects. For example, an area with 10 great programmers provides a valuable pool of labor talent for a startup. However, an additional 1,000 amazing programmers in the same area is vastly more valuable to startups, especially if programmers share best practices with other programmers, inspire one another, or start new companies.

However, an additional 1,000 amazing programmers in the same area is vastly more valuable to startups, especially if programmers share best practices with other programmers, inspire one another, or start new companies. External economies of scale lower certain costs; meanwhile, network effects make co-location more valuable. The second explanation of startup communities, horizontal networks, comes from sociology. In her PhD work at MIT, AnnaLee Saxenian (currently Dean of the UC Berkeley School of Information) noticed that external economies do not fully explain the development and adaptation of startup communities. In particular, in her seminal book Regional Advantage: Culture and Competition in Silicon Valley and Route 128 (1994) Saxenian noted that two hotbeds for high-tech activity—Silicon Valley and Boston’s Route 128—looked very similar in the mid-1980s.

Yet just a decade later, Silicon Valley gained a dominant advantage over Route 128. External economies alone did not provide an answer. Saxenian set out to resolve the puzzle of why Silicon Valley far outpaced Route 128 from the mid-1980s to mid-1990s. Saxenian persuasively argues that a culture of openness and information exchange fueled Silicon Valley’s ascent over Route 128. This argument is tied to network effects, which are better leveraged by a community with a culture of information sharing across companies and industries. Saxenian observed that the porous boundaries between Silicon Valley companies, such as Sun Microsystems and HP, stood in stark contrast to the closed-loop and autarkic companies of Route 128, such as DEC and Apollo. More broadly, Silicon Valley culture embraced a horizontal exchange of information across and between companies.


pages: 370 words: 105,085

Joel on Software by Joel Spolsky

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barriers to entry, c2.com, commoditize, George Gilder, index card, Jeff Bezos, knowledge worker, Metcalfe's law, Network effects, new economy, PageRank, Paul Graham, profit motive, Robert X Cringely, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, slashdot, Steve Ballmer, Steve Jobs, the scientific method, thinkpad, VA Linux, web application

(I'll talk about how to do that in the next chapters.) Another question about displacing competitors has to do with network effects and lock-in: Ben & Jerry's Amazon No network effect, weak customer lock-in Strong network effect, strong customer lock-in A network effect is a situation where the more customers you have, the more customers you will get. It's based on Metcalfe's Law:1 The value of a network is equal to the number of users squared. A good example is eBay. If you want to sell your old Patek Philippe watch, you're going to get a better price on eBay, because there are more buyers there. If you want to buy a Patek Philippe watch, you're going to look on eBay, because there are more sellers there. Another extremely strong network effect is created by proprietary chat systems like ICQ or AOL Instant Messenger. If you want to chat with people, you have to go where they are, and ICQ and AOL have the most people by far.

If you want to chat with people, you have to go where they are, and ICQ and AOL have the most people by far. Chances are, your friends are using one of those services, not one of the smaller ones like MSN Instant Messenger. With all of Microsoft's muscle, money, and marketing skill, they are just not going to be able to break into auctions or instant messaging, because the network effects there are so strong. __________ 1. See www.mgt.smsu.edu/mgt487/mgtissue/newstrat/metcalfe.htm. Lock-in is the characteristic of the business that makes people not want to switch. Nobody wants to switch their Internet provider, even if the service isn't very good, because of the hassle of changing your email address and notifying everyone. People don't want to switch word processors if their old files can't be read by the new word processor.

But when the three months are up, if you don't want to continue with the service, you have no choice but to contact every single bill provider and ask them to change the billing address back to your house. The sheer chore of doing this is likely to prevent you from switching away from PayMyBills.com—better just to let them keep sucking $8.95 out of your bank account every month. Gotcha! If you are going into a business that has natural network effects and lock-in, and there are no established competitors, then you better use the Amazon model, or somebody else will, and you simply won't be able to get a toehold. Quick case study. In 1998, AOL was spending massively to grow at a rate of a million customers every five weeks. AOL has nice features, like chat rooms and instant messaging, that provide stealth lock-in. Once you've found a group of friends you like to chat with, you are simply not going to switch Internet providers.


pages: 292 words: 85,151

Exponential Organizations: Why New Organizations Are Ten Times Better, Faster, and Cheaper Than Yours (And What to Do About It) by Salim Ismail, Yuri van Geest

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23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, bioinformatics, bitcoin, Black Swan, blockchain, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, Dean Kamen, dematerialisation, discounted cash flows, distributed ledger, Edward Snowden, Elon Musk, en.wikipedia.org, ethereum blockchain, Galaxy Zoo, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, market design, means of production, minimum viable product, natural language processing, Netflix Prize, Network effects, new economy, Oculus Rift, offshore financial centre, p-value, PageRank, pattern recognition, Paul Graham, peer-to-peer, peer-to-peer model, Peter H. Diamandis: Planetary Resources, Peter Thiel, prediction markets, profit motive, publish or perish, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, subscription business, supply-chain management, TaskRabbit, telepresence, telepresence robot, Tony Hsieh, transaction costs, Tyler Cowen: Great Stagnation, urban planning, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

Examples of companies that have successfully exposed their data this way are the Ford Company, Uber, IBM Watson, Twitter and Facebook. We can’t emphasize the following strongly enough: the world that is emerging is very different from the one we’ve known. Power is becoming easier to acquire but harder to keep. Thanks to strong viral and social network effects that allow startups to scale rapidly, it is now easier than ever before to start new companies and disrupt industries. But when it comes to social networks, the reverse is also true. Facebook, for example, is an incumbent, and its network effects and lock-in make it hard to usurp—underscoring the great advantage a platform has over a product or service. In her book, The End of Competitive Advantage: How to Keep Your Strategy Moving as Fast as Your Business, Rita Gunther McGrath illustrates that we can only obtain what she calls Transient Competitive Advantages via platforms and purpose, community, and culture.

Key attributes of Engagement include: Ranking transparency Self-efficacy (sense of control, agency and impact) Peer pressure (social comparison) Eliciting positive rather than negative emotions to drive long-term behavioral change Instant feedback (short feedback cycles) Clear, authentic rules, goals and rewards (only reward outputs, not inputs) Virtual currencies or points Properly implemented, Engagement creates network effects and positive feedback loops with extraordinary reach. The biggest impact of engagement techniques is on customers and the entire external ecosystem. However, these techniques can also be used internally with employees to boost collaboration, innovation and loyalty. For the Millennial generation, gaming is a way of life. Today, more than seven hundred million people around the world play online games—159 million in the U.S. alone—and most play for more than an hour each day.

Indeed, what might seem like the least serious tool in a company’s user and employee engagement program often proves to be one of its most powerful in terms of finding and training the individuals it needs to reach the next level. Although a comparatively minor issue as far as traditional enterprises are concerned, engagement proves to be critical for ExOs. It is a key element for scaling the organization into the community and crowd and for creating external network effects. No matter how promising its product or premise, unless an ExO is able to optimize the engagement of its community and crowd, it will wither and fade. Why Important? Dependencies or Prerequisites • Increases loyalty • Amplifies ideation • Converts crowd to community • Leverages marketing • Enables play and learning • Provides digital feedback loop with users • MTP • Clear, fair and consistent rules without conflicts of interest Passion and Purpose.


pages: 344 words: 96,020

Hacking Growth: How Today's Fastest-Growing Companies Drive Breakout Success by Sean Ellis, Morgan Brown

Airbnb, Amazon Web Services, barriers to entry, bounce rate, business intelligence, business process, correlation does not imply causation, crowdsourcing, DevOps, Elon Musk, game design, Google Glasses, Internet of things, inventory management, iterative process, Jeff Bezos, Khan Academy, Lean Startup, Lyft, Mark Zuckerberg, market design, minimum viable product, Network effects, Paul Graham, Peter Thiel, Ponzi scheme, recommendation engine, ride hailing / ride sharing, side project, Silicon Valley, Silicon Valley startup, Skype, Snapchat, software as a service, Steve Jobs, subscription business, Uber and Lyft, Uber for X, working poor, Y Combinator, young professional

For example, if you refer your next-door neighbor to the app, that will have no impact on your own user experience. But many companies have some degree of network effect potential that they can and should tap, even if it’s not obvious on the surface. For example, with Dropbox, the more files I have stored, the more likely I will invite people to join Dropbox to collaborate on them, while the more people I know who use Dropbox, the easier file sharing is going to be. That’s why doing the legwork to learn about how your customers use your product and where potential loops can be created and optimized is essential for tapping into viral growth driven through network effects. Eventbrite is a company that has created a powerful viral loop by tapping its network effect potential. The company is a hub for event promotion that makes money from taking a cut of ticket sales made through the site, and quite cleverly built in a social-driven loop by encouraging ticket buyers to share with their friends that they’re going to an event.

User experience experts call tricks to get users to take an action they normally would not take dark patterns, and while some of these dark patterns may work in the short term, the backlash from users is a long-term drag on growth. The negative press and bad feelings these kinds of tricks stir up can even be enough to torpedo the best products—we’ve seen it happen. Here are a number of best practices for experimenting with creating loops that will help you avoid such pitfalls. CONSIDER THE POTENTIAL TO TAP NETWORK EFFECTS The best loops are ones in which users are motivated to help sign up more users because doing so will improve their own experience of the product, such as with Facebook or LinkedIn. Network effect products have a great natural advantage with viral growth for this reason; they get better the more people are using them, so people are inclined to urge others to come on board. Social networks and messaging apps are obvious examples, as are big marketplaces that connect buyers directly with sellers, like eBay and Etsy, because more people using the site quite simply means: more potential customers for me as a seller and selection for me as a buyer.

When the team noticed auction owners promoting the PayPal service as an easy way for winners to pay, they created AutoLink, a tool that automatically added the PayPal logo and a link to sign up to all of their active auction listings. This tool tripled the number of auctions using PayPal on eBay and ignited its viral growth on the platform.4 LinkedIn, which had struggled to gain traction in its first year, saw their growth begin to skyrocket in late 2003, when the engineering team worked out an ingenious way for members to painlessly upload and invite their email contacts stored in their Outlook address book, kicking network effects growth into high gear.5 And in each of these cases, growth was achieved not with traditional advertising, but rather with a dash of programming smarts and on a shoestring budget. Approaches like these to building, growing, and retaining a customer base that relied not on traditional marketing plans, a pricey launch, and a big ad spend, but rather on harnessing software development to build marketing into products themselves, were proving both extraordinarily powerful and incredibly cost effective.


pages: 190 words: 53,409

Success and Luck: Good Fortune and the Myth of Meritocracy by Robert H. Frank

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, Amazon Mechanical Turk, American Society of Civil Engineers: Report Card, attribution theory, availability heuristic, Branko Milanovic, Capital in the Twenty-First Century by Thomas Piketty, carried interest, Daniel Kahneman / Amos Tversky, David Brooks, deliberate practice, en.wikipedia.org, endowment effect, experimental subject, framing effect, full employment, hindsight bias, If something cannot go on forever, it will stop - Herbert Stein's Law, income inequality, invisible hand, labor-force participation, labour mobility, lake wobegon effect, loss aversion, minimum wage unemployment, Network effects, Paul Samuelson, Report Card for America’s Infrastructure, Richard Thaler, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Rory Sutherland, selection bias, side project, sovereign wealth fund, Steve Jobs, The Wealth of Nations by Adam Smith, Tim Cook: Apple, ultimatum game, Vincenzo Peruggia: Mona Lisa, winner-take-all economy

The upshot is that if an economic opportunity arises anywhere in the networked world, ambitious entrepreneurs are quickly able to discover and exploit it. Modern communications technology has also reinforced powerful network effects that have increased the rewards to top performers. Those effects helped explain the growing dominance of the Windows PC platform during the late 1980s. Once Microsoft’s Windows graphical user interface reached parity with earlier rival Apple’s Macintosh, the numerical superiority of Windows users became a decisive advantage. Software developers concentrated their efforts on the Windows platform because more users meant more sales. And the greater availability of software titles, in turn, lured still more users to Windows, creating a positive feedback loop in the form of a network effect that drove Apple to the brink of bankruptcy. Network effects sometimes permit one firm’s ephemeral advantage to defeat a rival’s otherwise superior offering, as apparently happened in the battle between Betamax and VHS several decades ago.

Another popular use of VCRs at the time was for people to send home videos to their children’s grandparents. But that worked only if both households used the same format, so here was an additional positive feedback loop that reinforced the reasons for choosing VHS. In the meantime, Sony had managed to extend Betamax recording times. But by then the downward spiral was well underway, and Betamax was doomed. Network effects merit special emphasis because they are perhaps the most important source of randomness in high-stakes winner-take-all contests. One reason for reading a book or seeing a film is to enjoy the experience of discussing it with others. Opportunities for such exchanges are of course more numerous when you read best-selling titles or watch popular films. But of the thousands of entries released in any given year, only a relative handful find their way onto the most widely circulated best-seller lists.

(This was a period during which overall sales nearly doubled, so sales of these slow-moving titles were growing substantially in absolute terms.) The market shares of top offerings have also been growing in the publishing and film industries, according to Elberse. In some cases, they’ve been gaining ground because social media have amplified their attractiveness. Here again, we see the influence of network effects. Simple arithmetic ensures that Face-book exchanges are far more likely to be stimulated by posts on best-selling titles. Another factor is that new technology has done little to relieve an important market constraint—the scarcity of people’s time and energy. No one could possibly examine each of the million-plus offerings in Apple’s app store. And as the Swarth-more psychologist Barry Schwartz argued in his 2004 book, The Paradox of Choice, most people find it unpleasant to sift through a plethora of options.5 Many people sidestep that problem by focusing on only the most popular entries in each category.


pages: 161 words: 44,488

The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology by William Mougayar

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Airbnb, airport security, Albert Einstein, altcoin, Amazon Web Services, bitcoin, Black Swan, blockchain, business process, centralized clearinghouse, Clayton Christensen, cloud computing, cryptocurrency, disintermediation, distributed ledger, Edward Snowden, en.wikipedia.org, ethereum blockchain, fault tolerance, fiat currency, fixed income, global value chain, Innovator's Dilemma, Internet of things, Kevin Kelly, Kickstarter, market clearing, Network effects, new economy, peer-to-peer, peer-to-peer lending, prediction markets, pull request, QR code, ride hailing / ride sharing, Satoshi Nakamoto, sharing economy, smart contracts, social web, software as a service, too big to fail, Turing complete, web application

It is neither communism nor a version of cyberpunk fiction. Decentralization boosts capitalism by creating new layers of work production and value creation. It is granted that a blockchain will move value. But go further and start imagining multiple blockchains interacting with one another, all of them trading value with one another, and you will be led to a composite of network effects, potentially more significant than the previous generation of network effects. It will be the equivalent of a huge overlay of decentralized services that are open and accessible to anyone. Maybe the blockchain will lead us to the not-so utopian view of Nobel Prize winner, economist, and philosopher, Friedrich Hayek. He believed that the path to a functioning economy—or society—was decentralization, and asserted that a decentralized economy complements the dispersed nature of information spread throughout society.1 WHAT HAPPENED TO THE DECENTRALIZED INTERNET?

Furthermore, many industries are decentralized already, to an extent that many people outside of these industries do not appreciate, but they are decentralized in an inefficient way—a way that requires each company to maintain its own infrastructure around managing users, transactions, and data, and to reconcile with the systems of other companies every time it needs to interact. Consolidation around a single market leader would, in fact, make these industries more efficient. But neither the competitors of the likely leader nor antitrust regulators are willing to accept that outcome, leading to a stalemate. Until now. With the advent of decentralized databases that can technologically replicate the network effect gains of a single monopoly, everyone can join and align for their benefit, without actually creating a monopoly with all the negative consequences that it brings. This is the story that arguably drives the interest in consortium chains in finance, blockchain applications in the supply chain industry, and blockchain-based identity systems. They all use decentralized databases to replicate the gains of everyone being on one platform without the costs of having to agree on who gets to control that platform and then put up with them if they choose to try to abuse their monopoly position.

The blockchain has ten characteristics, and they all need to be understood in a holistic manner. NOTES 1. Bitcoin: A Peer-to-Peer Electronic Cash System, https://bitcoin.org/en/bitcoin-paper. 2. Bitcoin “maximalism” refers to the opinion that solely supports Bitcoin at the expense of all other blockchain or cryptocurrency related projects, because maximalists believe we only a need a single blockchain, and single currency in order to achieve desired network effects benefits. 3. The Untapped Potential of Corporate Narratives. http://edgeperspectives.typepad.com/edge_perspectives/2013/10/the-untapped-potential-of-corporate-narratives.html. 4. Myerson, Roger B. (1991). Game Theory: Analysis of Conflict, Harvard University Press. 5. Leslie Lamport, Robert Shostak, and Marshall Pease, The Byzantine Generals Problem. http://research.microsoft.com/en-us/um/people/lamport/pubs/byz.pdf. 6.


pages: 675 words: 141,667

Open Standards and the Digital Age: History, Ideology, and Networks (Cambridge Studies in the Emergence of Global Enterprise) by Andrew L. Russell

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barriers to entry, borderless world, Chelsea Manning, computer age, creative destruction, Donald Davies, Edward Snowden, Frederick Winslow Taylor, Hacker Ethic, Howard Rheingold, Hush-A-Phone, interchangeable parts, invisible hand, John Markoff, Joseph Schumpeter, Leonard Kleinrock, means of production, Menlo Park, Network effects, new economy, Norbert Wiener, open economy, packet switching, pre–internet, RAND corporation, RFC: Request For Comment, Richard Stallman, Ronald Coase, Ronald Reagan, Silicon Valley, Steve Crocker, Steven Levy, Stewart Brand, technoutopianism, Ted Nelson, The Nature of the Firm, Thomas L Friedman, Thorstein Veblen, transaction costs, web of trust

Interfaces between various components of computer hardware provide many familiar examples of compatibility standards, such as Universal Serial Bus and Ethernet ports. Of these three categories, my primary focus in here is the third category: the creation of compatibility standards for communication networks. Scholars who have studied the interconnection of various components of communication networks often use three concepts – infrastructure, platforms, and network effects – to describe the important role of standards that enable compatibility and interoperability. The utility of these concepts lies in their connotations of stability, support, and external benefits that standards can generate. They emphasize the potential for a heap of standardized components to combine into a cohesive and flexible network that can, in turn, sustain more complex social and economic activity.43 The second fundamental question posed above – who makes standards?

Russell, “Industrial Legislatures: The American System of Standardization,” in International Standardization as a Strategic Tool (Geneva: International Electrotechnical Commission, 2006). 43 National Telecommunications and Information Administration, The National Information Infrastructure: An Agenda for Action (1993), http://www.ibiblio.org/nii (accessed January 4, 2012); Michael L. Katz and Carl Shapiro, “Systems Competition and Network Effects,” The Journal of Economic Perspectives 8 (1994): 93–115; Richard R. John, “Recasting the Information Infrastructure for the Industrial Age,” in Alfred D. Chandler, Jr. and James Cortada, eds., A Nation Transformed by Information: How Information Has Shaped the United States from Colonial Times to the Present (New York: Oxford University Press, 2000); Philip J. Weiser, “Law and Information Platforms,” Journal of Telecommunications and High Technology Law 1 (2002): 1–35; Steven W.

These committees were important in their own era because they maintained fluidity in the dynamic industrial economy of the late nineteenth century: by defining standards, they facilitated the existence of multiple sources of supply and thus provided a means for small- and medium-sized industrial firms to avoid the specter of monopoly. As subsequent chapters in this book will show, these committees were also important in later eras because they created institutional and ideological precedents that computer and telecommunications engineers used in the latter decades of the twentieth century as they, too, sought to generate network effects and a competitive market structure. The history of industrial standards in the late nineteenth century, and my specific claim that the production of these standards fits within a conceptual middle ground between markets and hierarchies, might strike some readers as something of a detour from the gradual evolution of communication technologies of the digital age. After all, many standards for American telephone and telegraph networks in the nineteenth century were established within the corporate hierarchies of AT&T and Western Union, and the self-conscious movement for open systems and open standards did not begin until the 1970s.


pages: 398 words: 108,889

The Paypal Wars: Battles With Ebay, the Media, the Mafia, and the Rest of Planet Earth by Eric M. Jackson

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bank run, business process, call centre, creative destruction, disintermediation, Elon Musk, index fund, Internet Archive, iterative process, Joseph Schumpeter, market design, Menlo Park, Metcalfe’s law, money market fund, moral hazard, Network effects, new economy, offshore financial centre, Peter Thiel, Robert Metcalfe, Sand Hill Road, shareholder value, Silicon Valley, Silicon Valley startup, telemarketer, The Chicago School, the new new thing, Turing test

They simply could not afford to pay the new fees given that most of their buyers lurked on eBay. If nothing else, Yahoo’s collapse provided some insight into the relative strength of PayPal and eBay’s network effects. PayPal’s payments network was strong enough to survive the forced upgrade process, although our competitor did make up some ground by undercutting our pricing. EBay’s older auctions network, though, was far more powerful. It allowed Whitman to raise prices and still grow following the introduction of a minor fee system from Yahoo. PayPal may have enjoyed a modest network effect, but by banishing Yahoo auctions eBay had gone one step further and established itself as a person-to-person marketplace monopolist. Whenever Luke Nosek turned up in the product department after a long stretch in seclusion, he tended to have either a sagacious idea with him or, just as likely, a wacky scheme.

X.com, just like dotBank, launched its payments service with many features designed solely to spur user growth. PayPal had a race on its hands, and it became clear there would be no prize for second place. Peter Thiel often claimed that growth was the most critical objective for a business like Confinity. Our CEO maintained that creating a successful payments service could only happen if we achieved something called a network effect. An interactive, inter-connected system, he explained, could exist only if it conferred value on the people who voluntarily chose to join it. The more people participating in it, the more beneficial the network would become since all the members could interact together. Hence a large, established network is very valuable to enter and very costly to leave; in essence it locks in its members and prevents would-be competitors from getting off the ground.

So, for PayPal to grow rapidly and expand all over the Internet, the quickest way to do that is to first grow on eBay!” Luke went on to explain that since dotBank and X.com were now competing with Confinity, Peter and the management team believed that we needed to find the fastest way possible to scale up PayPal’s customer base. If we could increase our number of accounts to reach critical mass before our competitors, the resulting network effect would freeze out any opponents. Potential users would not waste time signing up for multiple accounts with different payment services if PayPal were ubiquitous. But if we failed and another service outpaced us, then there probably would be nothing we could do to catch up. Although stopping short of defining how many users constituted critical mass, the management team did agree that customer acquisition had to take on a higher importance than profitability in the short run.


pages: 281 words: 95,852

The Googlization of Everything: by Siva Vaidhyanathan

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1960s counterculture, activist fund / activist shareholder / activist investor, AltaVista, barriers to entry, Berlin Wall, borderless world, Burning Man, Cass Sunstein, choice architecture, cloud computing, computer age, corporate social responsibility, correlation does not imply causation, creative destruction, data acquisition, death of newspapers, don't be evil, Firefox, Francis Fukuyama: the end of history, full text search, global village, Google Earth, Howard Rheingold, informal economy, information retrieval, John Markoff, Joseph Schumpeter, Kevin Kelly, knowledge worker, libertarian paternalism, market fundamentalism, Marshall McLuhan, means of production, Mikhail Gorbachev, moral panic, Naomi Klein, Network effects, new economy, Nicholas Carr, PageRank, pirate software, Ray Kurzweil, Richard Thaler, Ronald Reagan, side project, Silicon Valley, Silicon Valley ideology, single-payer health, Skype, social web, Steven Levy, Stewart Brand, technoutopianism, The Nature of the Firm, The Structural Transformation of the Public Sphere, Thorstein Veblen, urban decay, web application, zero-sum game

Wagner’s argument about user behavior could be valid if boycotting or migrating from Google did not incur significant downgrades in service by losing the advantages of integration with other Google services. Google’s argument also ignores the “network effect” in communication markets: a service increases in value as more people use it.15 A telephone that is connected to only one other person has very limited value compared with one connected to 250 million people. YouTube is more valuable as a video platform because it attracts more contributors and viewers than any other comparable service. The more users it attracts, the more value each user derives from using it, and thus the more users it continues to attract. Network effects tend toward standardization and thus potential monopoly. The network effect for most of Google’s services is not the same exponential effect we saw with the proliferation of the telephone or fax machine.

If only one person in the world used Gmail, it would still be valuable to her, because it can work well with every other standard e-mail interface. But if only a few people used Google for Web searching, 20 R END E R UNTO CAESA R Google would not have the data it needs to improve the search experience. Google is better because it’s bigger, and it’s bigger because it’s better. This is an arithmetic, rather than geometric, network effect, but it matters nonetheless. Opting out or switching away from Google services degrades one’s ability to use the Web. It may seem as if I’m arguing that Google is a monopoly and needs to be treated as such, broken up using the antimonopoly legislation and regulations developed over the late nineteenth and early twentieth centuries. But because Google is sui generis, business competition and regulation demand fresh thinking.

Although Google’s contextual advertising and instant auctions often serve the interests of small firms, its freedom to set such rates at any level it desires allows it to crowd out some of the small firms that have grown to depend on Google for their most valuable advertising outlets—including small firms that are Google’s potential competitors. That’s mean, but it’s not illegal. If Google’s adver- REN D E R UNTO CA ESA R 29 tising dominance and revenues are a legal problem at all, it’s because of a touchy issue called cross-subsidization. Google can use its prominence in people’s lives—the network effect— and its surplus revenues to support its other ventures—its online document business, for example, which is likely to lose trivial money for the company. This process is not yet a direct threat to Microsoft, which can withstand a few thousand customers sneaking off to the “cloud” instead of using Word on their own laptops. But it poses a serious threat to small, creative companies that offer Web-based word processors, such as Zoho, Thinkfree, Writely, and Ajaxwrite.


pages: 25 words: 5,789

Data for the Public Good by Alex Howard

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23andMe, Atul Gawande, Cass Sunstein, cloud computing, crowdsourcing, Hernando de Soto, Internet of things, lifelogging, Network effects, openstreetmap, Silicon Valley, slashdot, social software, social web, web application

“Data by itself isn’t useful. You don’t go and download data and slather data on yourself and get healed,” he said. “Data is useful when it’s integrated with other stuff that does useful jobs for doctors, patients and consumers.” What Lies Ahead There are four trends that warrant special attention as we look to the future of data for public good: civic network effects, hybridized data models, personal data ownership and smart disclosure. Civic Network Effects Community is a key ingredient in successful open government data initiatives. It’s not enough to simply release data and hope that venture capitalists and developers magically become aware of the opportunity to put it to work. Marketing open government data is what repeatedly brought federal Chief Technology Officer Aneesh Chopra and Park out to Silicon Valley, New York City and other business and tech hubs.


pages: 238 words: 73,824

Makers by Chris Anderson

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3D printing, Airbnb, Any sufficiently advanced technology is indistinguishable from magic, Apple II, autonomous vehicles, barriers to entry, Buckminster Fuller, Build a better mousetrap, business process, commoditize, Computer Numeric Control, crowdsourcing, dark matter, David Ricardo: comparative advantage, death of newspapers, dematerialisation, Elon Musk, factory automation, Firefox, future of work, global supply chain, global village, industrial robot, interchangeable parts, Internet of things, inventory management, James Hargreaves, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, Kickstarter, Lean Startup, manufacturing employment, Mark Zuckerberg, means of production, Menlo Park, Network effects, profit maximization, QR code, race to the bottom, Richard Feynman, Richard Feynman, Ronald Coase, Rubik’s Cube, self-driving car, side project, Silicon Valley, Silicon Valley startup, Skype, slashdot, South of Market, San Francisco, spinning jenny, Startup school, stem cell, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, supply-chain management, The Nature of the Firm, The Wealth of Nations by Adam Smith, transaction costs, trickle-down economics, Whole Earth Catalog, X Prize, Y Combinator

By simply bringing the Web’s culture and collaboration to the process of making, they’re combining to build something on a scale we’ve never seen from DIY before. What the Web taught us was the power of “network effects”: when you connect people and ideas, they grow. It’s a virtual circle—more people combined create more value, which in turn attracts even more people, and so on. That’s what has driven the ascent of Facebook, Twitter, and practically every other successful company online today. What Makers are doing is taking the DIY movement online—“making in public”—which introduces network effects on a massive scale. In short, the Maker Movement shares three characteristics, all of which, I’d argue, are transformative: 1. People using digital desktop tools to create designs for new products and prototype them (“digital DIY”). 2.

Growth continues at about 75 to 100 percent per year, which is common for open-source hardware companies like ours. We’ve been profitable from the first year (it’s actually not that hard in the hardware business—just charge more than your costs!), but try to reinvest as much of the profits as possible into building new factory lines. Because we’re online, we’re global from the start and tend to grow more quickly than traditional manufacturing companies because of the network effects of online word of mouth. But because we’re making hardware, which costs money and takes time to make, we don’t show the hockey-stick exponential growth curve of the hottest Web companies. So, as a business, we’re a hybrid: the simple business model and cash-flow advantages of traditional manufacturing, with the marketing and reach advantages of a Web company. We’re still a small business, but the difference between our kind of small business and the dry cleaners and corner shops that make up the majority of micro-enterprise in the country is that we’re Web-centric and global.

Think of the tens of thousands of apps that support and reinforce Android, an open (mostly) mobile operating system. Or the hundreds of plug-ins and utilities designed to work with WordPress, the open-source blogging platform. In each case, openness built a constituency for the product’s continued success. The fact that others could copy it didn’t matter, because all that goodwill had created a network effect that was far harder to copy than simply code. But what if someone wants to rip us off anyway? Well, it depends on what you mean by “rip us off.” If someone else decides to use our files, make no significant modifications or improvements, and just manufacture them and compete with us, they’ll have do so much more cheaply than we can to get traction in the marketplace. If they can do so, at the same or better quality, then that’s great: the consumer wins and we can stop making that product and focus on those that add more value (we don’t want to be in the commodity manufacturing business).


pages: 265 words: 69,310

What's Yours Is Mine: Against the Sharing Economy by Tom Slee

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4chan, Airbnb, Amazon Mechanical Turk, asset-backed security, barriers to entry, Berlin Wall, big-box store, bitcoin, blockchain, citizen journalism, collaborative consumption, congestion charging, Credit Default Swap, crowdsourcing, data acquisition, David Brooks, don't be evil, gig economy, Hacker Ethic, income inequality, informal economy, invisible hand, Jacob Appelbaum, Jane Jacobs, Jeff Bezos, Khan Academy, Kibera, Kickstarter, license plate recognition, Lyft, Marc Andreessen, Mark Zuckerberg, move fast and break things, move fast and break things, natural language processing, Netflix Prize, Network effects, new economy, Occupy movement, openstreetmap, Paul Graham, peer-to-peer, peer-to-peer lending, Peter Thiel, pre–internet, principal–agent problem, profit motive, race to the bottom, Ray Kurzweil, recommendation engine, rent control, ride hailing / ride sharing, sharing economy, Silicon Valley, Snapchat, software is eating the world, South of Market, San Francisco, TaskRabbit, The Nature of the Firm, Thomas L Friedman, transportation-network company, Uber and Lyft, Uber for X, ultimatum game, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Zipcar

For several years Apple’s iPod and Google’s YouTube had no serious competitors. Many of the sources of increasing returns for digital marketplaces are lumped under the term “network effects”: each new user of a service makes that service more valuable. Social media companies obviously benefit from network effects: you join the social media platform where the people you want to meet hang out. But there are other, less obvious forms of increasing returns: Google learns from every search carried out on its platform and so has a continuing advantage over its rivals (such as they are); advertisers want to be on the search engine that most people frequent, so the leading search engine will attract the most advertising money to feed its further growth. Other network effects are familiar from the brick-and-mortar world: a successful corporate brand can communicate familiarity and dependability and so grow faster.

Or, as is the case with Amazon, a growing business provides money that can be re-invested in building more efficient infrastructure, driving the next cycle of competitive advantage. Not that network effects continue without limit. New technologies do come along to challenge existing ones such as music streaming companies challenging Apple’s iTunes Store. Also, cultural instincts don’t just bind us all together on Facebook, they drive us apart too. What teen wants to be on the same social networking site as their parents? So Snapchat and Instagram become the social networks for the next generation, and new entrants (Yoho, Whisper, WhatsApp, Kik) try to create new identities that will appeal to a new demographic. Faced with generational changes in tastes, the best thing that this generation’s company can do is sometimes to buy its challengers, as Facebook has done by buying Instagram and WhatsApp. Network effects are not unique to the Internet, but the Internet provides an environment in which they can become particularly powerful.


pages: 278 words: 83,468

The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses by Eric Ries

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3D printing, barriers to entry, call centre, Clayton Christensen, clean water, cloud computing, commoditize, Computer Numeric Control, continuous integration, corporate governance, experimental subject, Frederick Winslow Taylor, Lean Startup, Marc Andreessen, Mark Zuckerberg, Metcalfe’s law, minimum viable product, Network effects, payday loans, Peter Thiel, pets.com, Ponzi scheme, pull request, risk tolerance, selection bias, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, stealth mode startup, Steve Jobs, the scientific method, Toyota Production System, transaction costs

By contrast, a marketplace company that matches buyers and sellers such as eBay will have a different growth model. Its success depends primarily on the network effects that make it the premier destination for both buyers and sellers to transact business. Sellers want the marketplace with the highest number of potential customers. Buyers want the marketplace with the most competition among sellers, which leads to the greatest availability of products and the lowest prices. (In economics, this sometimes is called supply-side increasing returns and demand-side increasing returns.) For this kind of startup, the important thing to measure is that the network effects are working, as evidenced by the high retention rate of new buyers and sellers. If people stick with the product with very little attrition, the marketplace will grow no matter how the company acquires new customers.

In 2004, that market had hundreds of millions of consumers actively participating worldwide. However, the majority of the customers who were using IM products were not paying for the privilege. Instead, large media and portal companies such as AOL, Microsoft, and Yahoo! operated their IM networks as a loss leader for other services while making modest amounts of money through advertising. IM is an example of a market that involves strong network effects. Like most communication networks, IM is thought to follow Metcalfe’s law: the value of a network as a whole is proportional to the square of the number of participants. In other words, the more people in the network, the more valuable the network. This makes intuitive sense: the value to each participant is driven primarily by how many other people he or she can communicate with. Imagine a world in which you own the only telephone; it would have no value.

The top three networks controlled more than 80 percent of the overall usage and were in the process of consolidating their gains in market share at the expense of a number of smaller players.2 The common wisdom was that it was more or less impossible to bring a new IM network to market without spending an extraordinary amount of money on marketing. The reason for that wisdom is simple. Because of the power of network effects, IM products have high switching costs. To switch from one network to another, customers would have to convince their friends and colleagues to switch with them. This extra work for customers creates a barrier to entry in the IM market: with all consumers locked in to an incumbent’s product, there are no customers left with whom to establish a beachhead. At IMVU we settled on a strategy of building a product that would combine the large mass appeal of traditional IM with the high revenue per customer of three-dimensional (3D) video games and virtual worlds.


pages: 357 words: 99,684

Why It's Still Kicking Off Everywhere: The New Global Revolutions by Paul Mason

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back-to-the-land, balance sheet recession, bank run, banking crisis, Berlin Wall, capital controls, centre right, citizen journalism, collapse of Lehman Brothers, collective bargaining, creative destruction, credit crunch, Credit Default Swap, currency manipulation / currency intervention, currency peg, eurozone crisis, Fall of the Berlin Wall, floating exchange rates, Francis Fukuyama: the end of history, full employment, ghettoisation, illegal immigration, informal economy, land tenure, low skilled workers, mass immigration, means of production, megacity, Mohammed Bouazizi, Naomi Klein, Network effects, New Journalism, Occupy movement, price stability, quantitative easing, race to the bottom, rising living standards, short selling, Slavoj Žižek, Stewart Brand, strikebreaker, union organizing, We are the 99%, Whole Earth Catalog, WikiLeaks, Winter of Discontent, women in the workforce, working poor, working-age population, young professional

The network’s basic law was explained by Bell Telephone boss Theodore Vail as early as 1908: the more people who use the network, the more useful it becomes to each user. This is known as the ‘network effect’: what it describes is the creation, out of two people’s interaction, of a ‘third thing’ which comes for free. Because network theory originated in the boardroom, this ‘third thing’ has tended to be identified in terms of economic value. But, in recent years, it has become clear it can provide much more than that. There’s another difference: when it was first theorized by Vail’s technologists, the ‘network effect’ seemed like a by-product, a happy accident. Today we are conscious users and promoters of the network effect. Everyone who uses information technology understands that they are—whether at work, on Facebook, on eBay or in a multiplayer game—a ‘node’ on a network: not a foot-soldier, not a bystander, not a leader, but a multitasking version of all three.

Vail’s customers probably had no idea that, by buying and using telephones, they were enhancing the technology’s value for others and creating spin-off effects for Bell’s other businesses (what are now termed ‘network externalities’). Nowadays, many of us have a very clear understanding of all this. The result is that, in the past ten years, the ‘network effect’ has blasted its way out of corporate economics and into sociology. The most obvious impact has been on the media and ideology. Long before people started using Twitter to foment social unrest, mainstream journalists noticed—to their dismay—that the size of one’s public persona or pay cheque carried no guarantee of popularity online. People’s status rises and falls with the reliability and truthfulness of what they contribute. This is a classic network effect—but it is not measurable as profit and loss. If you look at the full suite of information tools that were employed to spread the revolutions of 2009–11, it goes like this: Facebook is used to form groups, covert and overt—in order to establish those strong but flexible connections.

I. 46 Len-len 193–96, 209 Liberal Democrats 43–44, 46 liberalizers 31 Libya 25, 31, 119; National Transitional Council 178 Life and Fate (Grossman) 129 Lilico, Andrew 121 link-shorteners 75 Linux 139–40 @littlemisswilde 41–42, 44, 45, 135–36, 138 living conditions, urban slums 196–99 London: anti-capitalist demonstrations 33; arrests 61–62; Day X, 24 November 2010 41–42, 46–48; the Dubstep Rebellion 48–52; Fortnum & Mason 60–61; HM Revenue and Customs building 51; Hyde Park 60; Millbank riot 42–44; Millbank Tower 43; Museum Tavern 1; National Gallery teach-in 53, 53–54; Oxford Circus 60; Palladium Theatre 51; Parliament Square 49, 51, 52–53; Piccadilly Circus 58; police–student confrontation 50–51; Regent Street 58; Ritz Hotel 60; Tate Modern 53; trade-union demonstration, March 2011 57–61; Trafalgar Square 47; Victoria Street 50; Victorinox 59 London School of Oriental and African Studies, occupation of 44–46 López, Fernando 166–67, 170 Lopez, Gina 200–2 Lopez Inc. 200–2 Loubere, Leo 174 Loukanikos (riot dog) 94, 96 L’Ouverture, Toussaint 149 LulzSec 151 McIntyre, Jody 51 McPherson, James 182 Madison, Wisconsin revolt 184–87 Madrid 33 Mahalla uprising, 2008 10, 71 Maher, Ahmed 83 Mahfouz, Asmaa, @AsmaaMahfouz 11, 177 Mahmoud (Zamalek Sporting Club ultra) 16–17 Makati, Manila 204–6 malnutrition 9 Mandelson, Peter 17, 26, 114 Manila 33; Estero de Paco 200–2; Estero de San Miguel 196–99; Makati 204–6; waterways 200–2 manipulated consciousness 29–30 Manufacturing Consent (Chomsky and Herman) 28–29 Mao Tse Tung 46 Marxism 141–45 Marx, Karl 46, 141–45, 174, 187, 188–89, 190, 192 Masai with a mobile, the 133–34 Masoud, Tarek 27 Masry Shebin El-Kom textile factory 22–23 mass culture 29–30 Matrix, The (film) 29 Meadows, Alfie 51 media, the 28–29 @mehri912 34 Meltdown (Mason) 31–32 memes 75, 150–52, 152 Merkel, Angela 96, 98, 99, 112 Michas, Takis 103 Middle East: balance of power 178; Facebook usage 135; failure of specialist to understand 25–27 Milburn, Alan 114 Miliband, Ed 58, 60, 188 Millbank riot 42–44 Millennium Challenge 2002 82–83 Miller, Henry 128 misery 209 mobile telephony 75–76, 133–34 modernism 28 mortgage-backed securities 106–8 Moses, Jonathan 48 Mousavi, Mir-Hossein 33–34 movement without a name 66 Mubarak, Alaa 17–18 Mubarak, Gamal 8, 10, 17–18, 26 Mubarak, Hosni 9, 10, 14, 15, 18–19, 19–20, 26, 31 Murdoch, Rupert 31, 106, 148–49 Muslim Brotherhood 21, 177 NAFTA 166–67 Napoleon III 172, 191 Nasser, Gamal Abdel 19 National Gallery teach-in 53, 53–54 nationalism 124 Native Americans 162, 163 Negri, Toni 42 Netanyahu, Binyamin 180 network animals 147 networked individualism 130, 130–33, 141 networked protests 81–82, 85 networked revolution, the 79–85; erosion of power relations 80–81; informal hierarchies 83; networked protests 81–82; network relationships 81; swarm tactics 82–83 network effect, the 2, 74–75, 77; erosion of power relations 80–81; strength 83; usefulness 84 network relationships 81 Nevins, Allan 182 New Journalism 3 News Corporation 148—49 News of the World 49; phone hacking scandal 61, 148–49 New Unrest, social roots of 65–66, 85; demographics of revolt 66–73; information tools 75–76; the networked revolution 79–85; organizational format 77–78; technology and 74–79; the urban poor 70–72 New York Times 170 1984 (Orwell) 30, 129 Nomadic Hive Manifesto, The 53–54 @norashalaby 13 North Africa: demographics of revolt 66; students and the urban poor 71 Obama, Barack 72, 116–18, 120, 122, 162, 167, 170, 180, 183, 187 OccupiedLondon blog 88–89 Occupy Wall Street movement, the 139, 144, 187, 210 Office for National Statistics 115 Ogden-Nussbaum, Anna, @eponymousthing 184 Oklahoma 153, 153–56 Oldouz84 36, 37 Olives, Monchet 202–4 online popularity 75 On the Jewish Question (Marx) 143 Open Source software 139–40 Operation Cast Lead 33 organizational format, changing forms of 77–78 Organisation of Labour, The (Blanc) 187 organized labour 71–72, 143 Ortiz, Roseangel 161 Orwell, George 30, 129, 208, 210 Owen, Robert 142 Palafox, Felino 204–5 Palamiotou, Anna 97 Palestine 25, 121, 179, 180 Palin, Sarah 181, 182 PAME (Greek trade union) 90 Papaconstantinou, George 91, 97 Papandreou, George 88, 96 Papayiannidis, Antonis 103 Paris 39; 1968 riots 46; revolution of 1848 171, 172 Paris Commune, the 1, 72–73, 84, 132 PASOK 89, 91, 98, 99 Paulson, Hank 110 Petrache, Ruben 203–4 Philippines: Calauan, Laguna Province 202–4; Estero de Paco, Manila 200–2; Estero de San Miguel, Manila 196–99, 205–6, 206–9; Gapan City 193–96; Makati, Manila 204–6; New People’s Army 203 Philippines Housing Development Corporation 198 philosophy 29 phone hacking scandal 61, 148–49 Picasso, Pablo 127, 128, 132 Pimco 170 Poland 172 police car protester (USA) 4 Policy Exchange think tank 55 political mainstream, youth disengagement from 89–90 popular culture 65, 176 Porter, Brett 154, 155, 156 Port Huron Statement, the 129–30, 145 Portugal 92, 112, 188 postmodernism 28 poverty 121–22, 210, 211 Powell, Walter 77 power, refusal to engage with 3 power relations, erosion of 80–81 Procter & Gamble 23 propaganda of the deed 62 property 48 property bubble collapse 106–8 protectionism 124 protest, changing forms of 54–57 pro-Western dictators, support for 31 Prussia 191 Puente 165 Putnam, Robert 134 Quantitative Easing II 120–23 radicalization 33, 37, 47–48 radical journalists 149 Ramírez, Leticia 165 Real Estate Tax Authority Workers (Egypt) 19 Really Free School, the 1–2 @rebeldog_ath 96 reciprocity 77 Reed Elsevier 146 Reider, Dimi 179 Research and Destroy group 38–39 revolt, demographics of 66, 66–73 revolutionary wave 65 revolution, definition 79–80 revolutions: 1848 171–73, 173–75, 191, 192; 1917 173; 1968 173; 1989 173 Reynalds, Jeremy 159–60, 162–63 rice crops 195 Riches, Jessica, @littlemisswilde 41–42, 44, 45, 135–36, 138 Rimbaud, Arthur 132 River Warriors 201 Roads to Freedom (Sartre) 129 Road to Wigan Pier, The (Orwell) 208 Romer, Christina 117 Roosevelt, Franklin D. 169–70 Rove, Karl 30–31, 32 Rowan, Rory 54 Said, Edward 26–27 Said, Khaled 11, 148 @Sandmonkey 13 Sandra (Joy Junction resident) 160 Santa Cruz, University of California 37–39 Sarkozy, Nicolas 91–92, 98 @sarrahsworld 11–12, 14, 135 Sartre, Jean-Paul 129 Saudi Arabia 121 savings, and investment 107 Savio, Mario 4 SB1070 (USA) 164, 165–66, 166–67 self-esteem, and consumption 80–81 self-interest 111 self-reliance 68 self, the, social networks impact on 136–38 Sennett, Richard 68, 80–81, 131 Sentimental Education (Flaubert) 171 el-Shaar, Mahmoud 22 Shafiq, Mohammed 20–22 Shalit, Gilad 179 shared community 84 Sharp, Gene 83 Sharpton, Al 184 Shirky, Clay 138, 139, 140, 146 Sinclair, Cameron 199, 208 Sioras, Dr Ilias 90–91 Situationist movement 46–47 Situationist Taliban 1 slum-dwellers 68; numbers 198 social capital 134 social democracy 145 social housing 199 Socialist International 19–20 social justice 177, 191, 192, 209, 210 social media 7, 74–75, 77; collective mental arena 137; lack of control 37; power of 34–35; role of 56; and the spread of ideas 151 social micro-history 173 social networks 77, 82; impact of 147; impact on activism 138–41; and the self 136–38 social-republicanism 187 solidaristic slum, the 207 Solidarity 42 ‘Solidarity Forever’ (song) 42 Soviet Union 28 Spain 66, 104, 105, 188 Spanish Civil War 209–10 species-being 143 @spitzenprodukte (art activist) 1 spontaneous horizontalists 44–46 spontaneous replication 55 Starbucks Kids 79 Steinbeck, John 153, 155, 159, 163, 164, 169 Stephenson, Paul 52 Stiglitz, Joseph 118 Strategy Guide (Sharp) 83 Strauss-Kahn, Dominique 188 strongman threat, the 177–78 student occupations 37–39, 44–46, 53, 53–54 students: economic attack on 38; expectations 67–68; population 70 Sudan 25 Suez Canal Port Authority 19 Supreme Council of the Armed Forces (SCAF) (Egypt) 18, 20 surveillance 148 swarm tactics 82–83 swine flu epidemic 9 Switzerland 123 syndicalism 175–76 synthesis, lack of 57 Syria 25 tactics 54–57 Tahrir Square, Cairo 6, 69, 89, 139; chants 191, 211; Day of Rage, 28 May 15–17; demonstration, 25 January 10–14; numbers 13; Twitter feeds 13; volunteer medics 20–22 Taine, Hippolyte 73 Tantawi, General 19 Tarnac Nine, the 189 Tea Party, the 117–18, 124–25, 180–81 tear gas 93–94, 100–1 technology 65, 66, 74–79, 85, 133–36, 138–39; and the 1848 revolutions 173–74 Tehran, Twitter Revolution 34–37 teleology 131, 152 Tent City jail, Arizona 164–67 Territorial Support Group 50 Thatcher, Margaret 106 @3arabawy 10, 22, 71 Third Way, the 31 Time magazine 36 Tim (human rights activist) 1–2 Tim (Joy Junction resident) 160 Tocqueville, Alexis de 192 totalitarianism 147–48 toxic debt 110–11 trade wars 122, 124–25 transnational culture 69 Transparency International 119 Trichet, Jean-Claude 112 Truman Show, The (film) 29 trust 57 Tunisia: Army 178; economic growth 119; inflation 121; organized workforce 72; revolution 10, 11, 25–26; unemployment 119 Turkle, Sherry 136 Twitpic 75 Twitter and tweets 3, 74, 137–38; #wiunion 184, 185; @Ghonim 13; @mehri912 34; @norashalaby 13; @rebeldog_ath 96; @Sandmonkey 13; Egyptian revolution 13, 14; importance of 135–36; Iranian revolution and 33–37; Madison, Wisconsin revolt 184; news dissemination 75; real-time organization 75; reciprocity 77; user numbers 135; virtual meetings 45 Twitter Revolution, Iran 33–37, 78, 178 Ukraine 177–78 UK Uncut 54–57, 58, 61 ultra-social relations 138 unemployment: America 159–63; Egypt 119; Spain 105; Tunisia 119; youth 66, 105, 119–20 UN-Habitat 199 Unison 57 United Nations, The Challenge of Slums 198–99 United States of America: agriculture 154–56; Albuquerque 159, 159–63; Arizona 164–67, 183; armed struggle 181–83; Bakersfield, California 168–70; budget cuts 156, 161, 167, 170; California 168–70; campus revolts, 1964 4; Canadian River 159; cattle prices 156; collapse of bipartisan politics 116–19; culture wars 179, 180–84; current-account deficit 107; debt 118; deportations 166; devaluation 123; Dodd–Frank Act 167; the Dust Bowl 154–55; economic decline 183–84; economic growth 170; Federal budget 156, 161; fiscal management 183; fiscal stimulus 117–18; fruit pickers 169; hamburger trade 156; healthcare bill 180, 183; homeless children 160; homelessness 159–63; Indiana 116–17, 125; Interstate 40 157, 170; job market 161; Joy Junction, Albuquerque 159–63; Madison, Wisconsin revolt 184–87; minimum wage workers 158; the Mogollon Rim 163; motels 157–58, 162–63; the New Deal 169–70; Oklahoma 153, 153–56; Phoenix, Arizona 164–67; police car protester 4; political breakdown, 1850s 182–83; property bubble 106–8; Quantitative Easing II 120–23; radical blogosphere 184; the religious right 118; repossessions 168; Route 66 157–59; San Joaquin valley 169; SB1070 164, 165–66, 166–67; State Department 178; states’ rights 183; student occupation movement 37–39; the Tea Party 117–18, 124–25, 180–81, 186; Tent City jail, Arizona 164–67; Tucson, Arizona 182; undocumented migrants 164–67; unemployment 159–63; wages 108; war spending 162; welfare benefits 162, 170 Unite Union 55 university fees 44, 47, 50, 54 urban poor 70–72 urban slums 191; Calauan, Laguna Province 202–4; clearance policies 198–99; education levels 207; Estero de Paco, Manila 200–2; Estero de San Miguel, Manila 196–99, 205–6, 206–9; Gapan City, Philippines 193–96; improvement policies 199, 205–6; internet access 207; labour force 208; living conditions 196–99; Moqattam, Cairo 6–10; population numbers 198 Vail, Theodore 74 Vanderboegh, Mike 181 Van Riper, Lieutenant General Paul 82 Venizelos, Evangelos 97–98 Vietnam War 129 virtual meetings 45 virtual societies 134 Vodafone 54–55 Vradis, Antonis 87–89 wages 108, 112 Walker, Scott 184 Walorski, Jackie 116–17 Walt, Stephen M. 26 war, threat of 178 Warwick University, Economics Conference 67–68 Washington Times 35 Wasim (Masry Shebin El-Kom delegate) 23 water supplies 194 wave creation 78 wealth, monopolization of 108 We Are Social 148 Weeks, Lin, @weeks89 184 Wellman, Barry 130 Wertheim, Margaret 136 White House, the 92 ‘Why the Tunisian revolution won’t spread’ (Walt) 26 WikiLeaks 140 Wikipedia 46, 140 wikis 140–41 #wiunion 184, 185 Wobblies 176 Women’s liberation 132 Woods, Alan 33 Woollard, Edward 43 working class 68, 71–72, 79–80, 145; culture 72; revolutions, 1848 172–73 World of Yesterday, The (Zweig) 128 World Trade Organization 122 Yemen 25, 119, 121 youth 68; alienation 62; British 41–42, 44, 53–54; culture 70; disconnected 190; disengagement from political mainstream 89–90; radicalization 33, 37, 47–48; unemployment 66, 119–20 YouTube 75; Egyptian revolution on 11, 14, 15; Iranian revolution on 34, 35 Zamalek Sporting Club, ultras 16–17 Zapatistas 1 Zekry, Musa 5–6, 7, 23–24 Zola, Emil 191 Zweig, Stefan 128, 132–33, 152, 176 Copyright This revised and updated second edition first published by Verso 2013 First published by Verso 2012 © Paul Mason 2012, 2013 All rights reserved The moral rights of the author have been asserted Verso UK: 6 Meard Street, London W1F 0EG US: 20 Jay Street, Suite 1010, Brooklyn, NY 11201 www.versobooks.com Verso is the imprint of New Left Books ISBN: 978-1-781-68245-6 (e-book) British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress Typeset in Fournier by MJ Gavan, Truro, Cornwall Printed by ScandBook AB, Sweden

Remix: Making Art and Commerce Thrive in the Hybrid Economy by Lawrence Lessig

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Amazon Web Services, Andrew Keen, Benjamin Mako Hill, Berlin Wall, Bernie Sanders, Brewster Kahle, Cass Sunstein, collaborative editing, commoditize, disintermediation, don't be evil, Erik Brynjolfsson, Internet Archive, invisible hand, Jeff Bezos, jimmy wales, Kevin Kelly, Larry Wall, late fees, Mark Shuttleworth, Netflix Prize, Network effects, new economy, optical character recognition, PageRank, peer-to-peer, recommendation engine, revision control, Richard Stallman, Ronald Coase, Saturday Night Live, SETI@home, sharing economy, Silicon Valley, Skype, slashdot, Steve Jobs, The Nature of the Firm, thinkpad, transaction costs, VA Linux, yellow journalism

This is a consequence of network effects: the more who join, the more valuable the resource is for everyone. There are many contexts in which this network effect is true. Think, for example, about the English language. Every time someone in China struggles to learn English or a school in India continues to push English as a primary language, all of us English speakers benefit. But 80706 i-xxiv 001-328 r4nk.indd 153 8/12/08 1:55:26 AM REMI X 154 in neither of these cases—with AOL or English—are people joining the movement because it is a movement. People join because it gives them something they want. In each case, there is a resource that is shared among everyone within the community—information about the market, computer resources to make VOIP work better, the network effect from a popular network.

There’s a trust-building exercise there that doesn’t traditionally happen, because companies are inherently private because historically, competition was the first order of concern of companies. Therefore privacy [or secrecy], for the purpose of giving you a leg up on your competitors, has always been a kind of a central building block of corporate behavior. And, in a world where openness and network effects are likely to decide the winner, you now have to break down that perception. You want to build a company whose first value is not privacy but, instead, disclosure. Some companies go even further. Brewster Kahle describes the decision of the search company Alexa. [W]e wanted to build a new-generation search engine, which is sort of what Alexa and the Internet Archive strove to do in ’96. It turns out that we were wrong, that the world didn’t need a fundamentally different kind of search engine, because the search engines were going along okay.

And then that repository became the CDDB.” 80706 i-xxiv 001-328 r4nk.indd 237 8/12/08 1:55:57 AM 238 REMI X All this typing was done voluntarily. People wanted their machines to know what the tracks were; they were happy to share with others the information they typed into their machines. And Kan and Scherf built the tools to aggregate the results of this voluntary work “with the best intentions in the world. They were not trying to make any money off of it. They really wanted to make just a social network and get all the network effects.” They built a commons for others to add to; volunteers demonstrated the “grace of the commons” through the contributions they made. But, Marglin explained to me, as more and more people began to rely upon this database to identify their CDs, Kan and Scherf began to realize “very quickly that they had a beast on their hands because: one, in order to be any good, the software would have to do a lot more reconciling than they first expected . . . and two, the amount of server space that they would need in order to take in, not only all the lookups, but . . . all the submissions, was just going to overwhelm them.”21 So the founders of CDDB started looking for a way to make sure their creation would survive.


pages: 330 words: 91,805

Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism by Robin Chase

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3D printing, Airbnb, Amazon Web Services, Andy Kessler, banking crisis, barriers to entry, basic income, Benevolent Dictator For Life (BDFL), bitcoin, blockchain, Burning Man, business climate, call centre, car-free, cloud computing, collaborative consumption, collaborative economy, collective bargaining, commoditize, congestion charging, creative destruction, crowdsourcing, cryptocurrency, decarbonisation, don't be evil, Elon Musk, en.wikipedia.org, ethereum blockchain, Ferguson, Missouri, Firefox, frictionless, Gini coefficient, hive mind, income inequality, index fund, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jane Jacobs, Jeff Bezos, jimmy wales, job satisfaction, Kickstarter, Lean Startup, Lyft, means of production, megacity, Minecraft, minimum viable product, Network effects, new economy, Oculus Rift, openstreetmap, optical character recognition, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, smart cities, smart grid, Snapchat, sovereign wealth fund, Steve Crocker, Steve Jobs, Steven Levy, TaskRabbit, The Death and Life of Great American Cities, The Future of Employment, The Nature of the Firm, transaction costs, Turing test, turn-by-turn navigation, Uber and Lyft, Zipcar

Meanwhile, every driver has a cell phone in his or her pocket that could make electronic payments. But some platforms for participation deliver infrastructure and significant network effects. In other words, the value of the service goes up the more people participate. Zipcar, for example, is useful if there is just one car parked near your house, but when people in another city make it possible for you to rent cars there too, there is added value to you, albeit a marginal one. For BlaBlaCar, on the other hand, all the value is derived from network effects: Ridesharing only works when lots of people are participating. These network effects are powerful and can make it very hard for a new entrant to enter the market and go up against an established company with a very large network. The pinnacle in a pure capitalist economy is creating so many barriers to entry that no one else can really compete.

What I failed to appreciate back then was the much larger movement made possible by the Internet. Zipcar was a trailblazer. When you can connect and share assets, people, and ideas, everything changes, not just how you rent a car. Google, eBay, Facebook, OKCupid, YouTube, Waze, Airbnb, WhatsApp, Duolingo—all are part of this transformation of capitalism. Web 2.0, the sharing economy, crowdsourcing, collaborative production, collaborative consumption, and network effects are simply terms we’ve created along the way in an effort to capture what is going on. Attributing all this to “the Internet” misses the building blocks and therefore the ability to replicate this type of activity in a more controlled way. There is one structure that underlies all these—excess capacity + a platform for participation + diverse peers—and it is fundamentally changing the way we work, build businesses, and shape economies.

Then, the profits of all the failed companies, along with the difference in efficiency between the manual and the automated business, accrue to the center. And, it learns. If managed correctly, it becomes a recursive learning machine that just gets more effective with every measured mistake. This is what I’ve called miracle #2, exponential learning. As the platform starts to really perform, the tendency is for larger platforms to eat smaller ones because of network effects: We all want to use the short-term rental service with the broadest possible range of rooms advertised, or be on the social network that has most of our friends on it. The winners keep winning and tend to wind up with monopolistic power. She continues: It soon grows beyond replacement. Just look at how even after [Microsoft] management wasted billions of dollars on Bing, it is still failing against [Google], while [Google] never even missed a quarter.


pages: 455 words: 133,322

The Facebook Effect by David Kirkpatrick

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Andy Kessler, Burning Man, delayed gratification, demand response, don't be evil, global village, happiness index / gross national happiness, Howard Rheingold, Jeff Bezos, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Network effects, Peter Thiel, rolodex, Sand Hill Road, sharing economy, Silicon Valley, Silicon Valley startup, Skype, social graph, social software, social web, Startup school, Steve Ballmer, Steve Jobs, Stewart Brand, the payments system, The Wealth of Nations by Adam Smith, Whole Earth Review, winner-take-all economy, Y Combinator

He started saying that the goal of Thefacebook was “to help people understand the world around them.” They loved to talk about how Thefacebook showed what economists call “network effects.” And it did, just as have many of the great communications and software innovations of the last hundred years. A product or service is said to have a network effect when its value grows greater to all users each time one new user joins. Since every incremental user thus in effect strengthens the service, growth tends to lead to more growth, in a virtuous cycle. That was surely the case with Thefacebook, just as it was with instant messaging, AOL, the Internet itself, and even the telephone. Businesses or technologies with network effects tend to grow steadily and to have a durable market presence. While they wanted working at Thefacebook to be seen as cool—that helped in recruiting—the product was another matter.

It’s been a joke around the Facebook offices for years that the company seeks “total domination.” But the reason it’s funny is that it evokes a surprising truth. Zuckerberg realized a long time ago that most users are not going to take the time to create multiple profiles for themselves on multiple social networks. He also knew from his endless bull sessions at Harvard and in Palo Alto about “network effects” that once consolidation begins on a communications platform it can accelerate and become a winner-take-all market. People will join and use the communications tool that the largest number of other people already use. He therefore made it a goal to create a tool not for the United States but for the world. The objective was to overwhelm all other social networks wherever they are—to win their users and become the de facto standard.

The software service called TweetDeck enables this already, among others. Just two days after the Stream API announcement, I had dinner in New York with Sean Parker, who spent a good portion of our time together that night denouncing it. “It’s the greatest strategic gamble the company has ever made and will ever make,” he said in his intense rapid cadence. “Opening the stream to the world has the possibility of breaking the company’s network effect. As a closed network the switching costs are incredibly high and everybody’s forced to play in Facebook’s sandbox. But when you open the stream to the world you open the possibility of better Facebook clients that can process all the same data that Facebook itself can.” These words were still ringing in my ears a week later when I sat alone with Zuckerberg for a long interview in a corner conference room near his desk in Palo Alto.


pages: 527 words: 147,690

Terms of Service: Social Media and the Price of Constant Connection by Jacob Silverman

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23andMe, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, airport security, Amazon Mechanical Turk, augmented reality, basic income, Brian Krebs, California gold rush, call centre, cloud computing, cognitive dissonance, commoditize, correlation does not imply causation, Credit Default Swap, crowdsourcing, don't be evil, drone strike, Edward Snowden, feminist movement, Filter Bubble, Firefox, Flash crash, game design, global village, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, information retrieval, Internet of things, Jaron Lanier, jimmy wales, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, late capitalism, license plate recognition, life extension, lifelogging, Lyft, Mark Zuckerberg, Mars Rover, Marshall McLuhan, mass incarceration, meta analysis, meta-analysis, Minecraft, move fast and break things, move fast and break things, national security letter, Network effects, new economy, Nicholas Carr, Occupy movement, optical character recognition, payday loans, Peter Thiel, postindustrial economy, prediction markets, pre–internet, price discrimination, price stability, profit motive, quantitative hedge fund, race to the bottom, Ray Kurzweil, recommendation engine, rent control, RFID, ride hailing / ride sharing, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, Snapchat, social graph, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, TaskRabbit, technoutopianism, telemarketer, transportation-network company, Turing test, Uber and Lyft, Uber for X, universal basic income, unpaid internship, women in the workforce, Y Combinator, Zipcar

It made sense to erect the scaffolding of a traditional, profile-based social network around that. Google+ offered a familiar shape and central input for the kind of scattered but all-encompassing data collection that Google had been doing for years. Both aesthetically and in terms of privacy features (its “Circles,” which allowed users to tailor their updates to narrow audiences, was soon copied by Facebook), Google+ seemed a worthy social network on its own. But Facebook had network effects on its side—who would join Google+ if it seemed like an also-ran where nobody wanted to hang out? Google then had a challenge: how to get the hundreds of millions of people using its other products, like Search, Gmail, Docs, and YouTube, to embrace Google+. And it was a problem they desperately needed to solve, since Facebook’s huge, active membership and its use of Like buttons and other tracking tools meant that it had a glut of information that advertisers wanted.

As the artist Fatima Al Qadiri has said, “There’s no such thing at the most recent update. It immediately becomes obsolete.” Why, then, do we do it? If it’s so easy to become cynical about social media, to see amid the occasionally illuminating exchanges or the harvesting of interesting links (which themselves come in bunches, in great indigestible numbers of browser tabs) that we are part of an unconquerable system, why go on? One answer is that it’s a by-product of the network effect: the more people who are part of a network, the more one’s experience can seem impoverished by being left out. Everyone else is doing it. A billion people on Facebook, hundreds of millions scattered between these other networks—who wants to be on the outside? Who wants to miss a birthday, a friend’s big news, a chance to sign up for Spotify, or the latest bit of juicy social intelligence? And once you’ve joined, the updates begin to flow, the small endorphin boosts of likes and repins becoming the meager rewards for all that work.

Twitter is work, Facebook is work. Words are being written, content produced and shared, ads sold against it. A welter of data, some of it structured by us, is produced, and this has value. Yes, this work is often voluntary. You put in what you want, and if you don’t like that Facebook is profiting off of your relationships and communication with friends and your very identity, then you can quit. But the flip side of network effects—of a network rising in value and utility as more people join it—is that there can be a real social cost to opting out. And professional cost, too. Engagement in social media and other digital products has become required for many white-collar jobs, representing another way in which the work/life divide is broken down. The digital work of producing for Tumblr or Pinterest, then, becomes part of the work for producing for one’s day job.


pages: 397 words: 112,034

What's Next?: Unconventional Wisdom on the Future of the World Economy by David Hale, Lyric Hughes Hale

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affirmative action, Asian financial crisis, asset-backed security, bank run, banking crisis, Basel III, Berlin Wall, Black Swan, Bretton Woods, capital controls, Cass Sunstein, central bank independence, cognitive bias, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, corporate social responsibility, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, Daniel Kahneman / Amos Tversky, debt deflation, declining real wages, deindustrialization, diversification, energy security, Erik Brynjolfsson, Fall of the Berlin Wall, financial innovation, floating exchange rates, full employment, Gini coefficient, global reserve currency, global village, high net worth, Home mortgage interest deduction, housing crisis, index fund, inflation targeting, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Just-in-time delivery, Kenneth Rogoff, labour market flexibility, labour mobility, Long Term Capital Management, Mahatma Gandhi, Martin Wolf, Mexican peso crisis / tequila crisis, Mikhail Gorbachev, money market fund, money: store of value / unit of account / medium of exchange, mortgage tax deduction, Network effects, new economy, Nicholas Carr, oil shale / tar sands, oil shock, open economy, passive investing, payday loans, peak oil, Ponzi scheme, post-oil, price stability, private sector deleveraging, purchasing power parity, quantitative easing, race to the bottom, regulatory arbitrage, rent-seeking, reserve currency, Richard Thaler, risk/return, Robert Shiller, Robert Shiller, Ronald Reagan, sovereign wealth fund, special drawing rights, technology bubble, The Great Moderation, Thomas Kuhn: the structure of scientific revolutions, Tobin tax, too big to fail, total factor productivity, trade liberalization, Washington Consensus, Westphalian system, women in the workforce, yield curve

He reviews the process by which the dollar displaced the British pound as the dominant global currency during the early decades of the twentieth century. He then analyzes the prerequisites to be a reserve currency in the modern era. They are that the currency be widely available outside its home economy, that it be fully convertible, that it be supported by a large economy, and that it have a developed financial system. When these factors converge, they generate network effects in which the greater the number of people that are using the currency, the more beneficial it becomes for the users, and the more dominant it becomes. He thinks that the euro is not fully competitive with the dollar because there is no market for European government debt. Instead, investors have to choose between the debts of individual nation-states, of which the largest debtor is Italy. The yen suffers from the low interest rates in Japan and growing investor concern about the credit quality of Japanese government debt.

In short, US dollar security markets are highly convenient for individual, corporate, and official or government users around the world. These attributes largely explain the role of the US currency as the primary vehicle for holding foreign exchange reserves, as the most widely traded currency in international private trade and capital transactions, and as the leading currency in global foreign exchange transactions. 9. Network effects. As explained earlier, the US dollar did not start out as the world’s reserve currency. Much as English did not intentionally become the world’s most widely spoken language, the dollar did not become the world’s leading reserve currency by deliberate policy. The supremacy of the dollar is, like the supremacy of the English language, the result of gradual usage and experience. Like a common language, the US dollar enjoys what economists call “network externalities”—the greater the number of people who transact using dollars, the more beneficial this is to users, and the more dominant it becomes.

Like a common language, the US dollar enjoys what economists call “network externalities”—the greater the number of people who transact using dollars, the more beneficial this is to users, and the more dominant it becomes. Consequently, the US dollar deposit, loan, and funding markets outside the United States are far larger than those of any other currency traded outside its home borders; this effectively underwrites the continued financing of trade and capital transactions in dollars around the world. To undermine these network effects and simultaneously create a truly viable alternative reserve currency would therefore require both a dramatic shock to the dollar and the ready availability of a realistic alternative. However, a major erosion of any of the nine conditions listed above could undermine confidence in the US dollar, threatening its role as a currency for international transactions and as a reserve currency. Feasible Alternatives to the US Dollar Having established the nine characteristics required of an international reserve currency, we may now ask what alternatives there might be to the US dollar, either now or in the medium-term future.


pages: 339 words: 88,732

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson, Andrew McAfee

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, access to a mobile phone, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, American Society of Civil Engineers: Report Card, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, basic income, Baxter: Rethink Robotics, British Empire, business intelligence, business process, call centre, Chuck Templeton: OpenTable, clean water, combinatorial explosion, computer age, computer vision, congestion charging, corporate governance, creative destruction, crowdsourcing, David Ricardo: comparative advantage, digital map, employer provided health coverage, en.wikipedia.org, Erik Brynjolfsson, factory automation, falling living standards, Filter Bubble, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, full employment, game design, global village, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, intangible asset, inventory management, James Watt: steam engine, Jeff Bezos, jimmy wales, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Khan Academy, knowledge worker, Kodak vs Instagram, law of one price, low skilled workers, Lyft, Mahatma Gandhi, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Mars Rover, mass immigration, means of production, Narrative Science, Nate Silver, natural language processing, Network effects, new economy, New Urbanism, Nicholas Carr, Occupy movement, oil shale / tar sands, oil shock, pattern recognition, Paul Samuelson, payday loans, price stability, Productivity paradox, profit maximization, Ralph Nader, Ray Kurzweil, recommendation engine, Report Card for America’s Infrastructure, Robert Gordon, Rodney Brooks, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Simon Kuznets, six sigma, Skype, software patent, sovereign wealth fund, speech recognition, statistical model, Steve Jobs, Steven Pinker, Stuxnet, supply-chain management, TaskRabbit, technological singularity, telepresence, The Bell Curve by Richard Herrnstein and Charles Murray, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Tyler Cowen: Great Stagnation, Vernor Vinge, Watson beat the top human players on Jeopardy!, winner-take-all economy, Y2K

Networks and Standards: The Value of Scale Thirdly, the increased importance of networks (like the Internet or credit card networks) and interoperable products (like computer components) can also create winner-take-all markets. Just as low marginal costs create economies of scale on the production side, networks can create ‘demand side economies of scale’ that economists sometimes call network effects. We see them at work when users prefer products or services that other people are flocking to. If your friends keep in touch via Facebook, that makes Facebook more attractive to you, too. If you then join Facebook, the site becomes more valuable to your friends as well. Sometimes network effects are indirect. You can make a phone call equally well to someone using an iPhone or an Android phone. But the total number of users on a given platform influences app developers: the bigger network of users will tend to attract more developers, or encourage app developers to invest more in a given platform.

Its servers use the map, these updates, and a set of sophisticated algorithms to generate driving directions. If Andy wants to drive to Erik’s at 8:45 a.m. on a Tuesday, Waze is not going to put him on the highway. It’s going to keep him on surface streets where traffic is comparatively light at that hour. That Waze gets more useful to all of its members as it gets more members is a classic example of what economists call a network effect—a situation where the value of a resource for each of its users increases with each additional user. And the number of Wazers, as they’re called, is increasing quickly. In July of 2012 the company reported that it had doubled its user base to twenty million people in the previous six months.3 This community had collectively driven more than 3.2 billion miles and had typed in many thousands of updates about accidents, sudden traffic jams, police speed traps, road closings, new freeway exits and entrances, cheap gas, and other items of interest to their fellow drivers.

The more apps available for a given phone, the greater its appeal to users. Thus, your benefits from buying one or the other will be affected by the number of other users who buy the same product. When Apple’s app ecosystem is strong, buyers will want to buy into that platform, attracting even more developers. But the opposite dynamic can unravel a dominant standard, as it almost did for the Apple Macintosh platform in the mid-1990s. Like low marginal costs, network effects can create both winner-take-all markets and high turbulence.18 The Social Acceptability of Superstars In addition to the technical changes that have increased digitization, telecommunication, networks, and other factors that create superstar products and companies, there are more aspects at work in boosting superstar compensation for individuals. In some cases, cultural barriers to very large pay packages have fallen.


pages: 523 words: 111,615

The Economics of Enough: How to Run the Economy as if the Future Matters by Diane Coyle

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accounting loophole / creative accounting, affirmative action, bank run, banking crisis, Berlin Wall, bonus culture, Branko Milanovic, BRICs, call centre, Cass Sunstein, central bank independence, collapse of Lehman Brothers, conceptual framework, corporate governance, correlation does not imply causation, Credit Default Swap, deindustrialization, demographic transition, Diane Coyle, disintermediation, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, Financial Instability Hypothesis, Francis Fukuyama: the end of history, George Akerlof, Gini coefficient, global supply chain, Gordon Gekko, greed is good, happiness index / gross national happiness, Hyman Minsky, If something cannot go on forever, it will stop - Herbert Stein's Law, illegal immigration, income inequality, income per capita, industrial cluster, information asymmetry, intangible asset, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Jane Jacobs, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, knowledge economy, labour market flexibility, light touch regulation, low skilled workers, market bubble, market design, market fundamentalism, megacity, Network effects, new economy, night-watchman state, Northern Rock, oil shock, Pareto efficiency, principal–agent problem, profit motive, purchasing power parity, railway mania, rising living standards, Ronald Reagan, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, South Sea Bubble, Steven Pinker, The Design of Experiments, The Fortune at the Bottom of the Pyramid, The Market for Lemons, The Myth of the Rational Market, The Spirit Level, transaction costs, transfer pricing, tulip mania, ultimatum game, University of East Anglia, web application, web of trust, winner-take-all economy, World Values Survey, zero-sum game

They form what economists refer to as a “general purpose technology” because they affect the organization of the economy in a wide-ranging way, like steam or electricity or rail in the past.20 One widespread effect has been to increase the scope of economies of scale, as there are many industries in which it is now possible to reach a much larger number of consumers at very little additional cost, thanks to the possibilities of online marketing and distribution. Network effects have amplified this dynamic. So in many industries, the structure has evolved into a small number of very large firms competing across all products and services, and often globally, and a large number of small businesses supplying particular niches. Software is a clear example: it costs Microsoft almost nothing to supply one additional copy of its software, as almost all the cost is upfront development.

Some aspects of this are matters for the companies and their shareholders: if they are not as productive as their competitors, there is no wider social issue. Other aspects are matters of public concern, however. In particular, the drive to increase in size in order to take advantage of economies of scale is an issue. There has been a sharp divide among experts on competition policy between those who think that it’s good for consumers that Microsoft is so big, because this means lower prices and the benefits of network effects, and those who think it’s bad for consumers because it hasn’t been possible for new or better operating systems and browsers to serve more consumers.26 There are merits in both sets of arguments. As someone who was a UK competition regulator for eight years in the 2000s, I’ve come to the conclusion that too many companies are simply too big and too similar. Innovation is being stifled. More important, there is a concentration of power in the hands of some big companies.

., 127–28 Calculus of Consent, The: Logical Foundations of Constitutional Democracy (Buchanan and Tullock), 242 call centers, 131, 133, 161 Cameron, David, 288 capitalism: China and, 234; communism and, 96, 182–83, 209–13, 218, 226, 230, 239–40; community and, 27, 51, 65, 117–18, 137, 141, 152–54; cultural effects of, 25–29, 230–38; current crisis of, 6–9; democracy and, 230–38; Engels on, 14; fairness and, 134, 137, 149; growth and, 268, 275, 290, 293, 297; happiness and, 25–29, 33, 45, 53–54; historical perspective on, 3, 6, 14; institutions and, 240; market failure and, 226–30; Marx on, 14; measurement and, 182; mercantile economy and, 27–28; nutrition and, 10; profit–oriented, 18; Protestant work ethic and, 13–14; protests against, 211–13; rethinking meaning of, 9; social effects of, 25–26; values and, 209–13, 218, 226, 230–32, 235–36; well-being and, 137–39 carbon prices, 70–71 celebrities, 33 charitable giving, 33, 141 Checkpoint Charlie, 147 China, 161, 262, 280; capitalism and, 234; carbon emissions and, 63; changed demographic structure of, 90; convergence and, 122; declining population in, 98; energy use in, 63, 65; global manufacturing and, 149; inequality and, 125–26; Mao and, 10; middle class of, 125–26; as next major power, 94; one–child policy and, 95–96; population growth and, 95–96; purchasing power parity (PPP) and, 306n19; rise in wealth of, 81, 122–23, 125, 212; savings and, 87, 94, 100, 108; wage penalties and, 133; World Bank influence and, 163 cities, 308n29; face-to-face contact and, 165–68; size and, 165–66; structural changes in, 165–70; urban clustering and, 166 City of London, 147, 221 Clemens, Michael, 81 climate change, 5–7, 17, 24, 90, 238; carbon prices and, 70–71; Copenhagen summit and, 62, 64–65, 68, 162, 292; domestic dissent and, 66–71; future and, 75–83; geological history and, 69; global warming and, 57, 64, 66, 68; greenhouse gases and, 23, 29, 35, 59, 61–63, 68, 70–71, 83; Himalayan glaciers and, 66–67; incandescent light bulbs and, 59–60; InterAcademy Council and, 66–67; Intergovernmental Panel on Climate Change (IPCC) and, 59, 66–69, 82, 297; Kyoto Protocol and, 62–64; lack of consensus on, 66–71; Montreal Protocol and, 59; policy dilemma of, 58–62; policy recommendations for, 267, 280, 297; politics and, 62–65; social welfare and, 71–75; technology and, 59–60, 198 Coachella Value Music Festival, 197 Cobb, John, 36 Coca Cola, 150 coherence, 49 Cold War, 93, 112, 147, 209, 213, 239, 252 Collier, Paul, 77–78, 80, 82 Commerzbank, 87 Commission on the Measurement of Economic Performance and Social Progress, 37–38 communism: Berlin Wall and, 182, 226, 239; capitalism and, 96, 182–83, 209–13, 218, 226, 230, 239–40; Cold War and, 93, 112, 147, 209, 213, 239, 252; fall of, 209–13, 226, 239–40, 252; Iron Curtain and, 183, 239, 252; Leipzig marches and, 239; one-child policy and, 95–96; Velvet Revolution and, 239 community: civic engagement and, 140–41; globalization and, 148–49; intangible assets and, 149–52, 157, 161 (see also trust); public service and, 295; Putnam on, 140–41, 152–54 commuting, 45–47 Company of Strangers, The (Seabright), 148–49, 213–14 comprehensive wealth, 81–82, 202–3, 208, 271–73 consumerism, 22, 34, 45, 138 consumption: conspicuous, 11, 22, 45, 236; consumerism and, 22, 34, 45, 138; cutting, 61; downgrading status of, 11; downshifting and, 11, 55; Easterlin Paradox and, 39–44; global per capita, 72; of goods and services, 7, 10, 24, 35–36, 40, 82, 99, 161, 188, 191, 198, 214, 218, 228–29, 282; green lifestyle and, 55, 61, 76, 289, 293; growth and, 280, 295; happiness and, 22, 29, 40, 45; hedonic treadmill and, 40; increasing affluence and, 12; institutions and, 254, 263; Kyoto Protocol and, 63–64; measurement and, 181–82, 198; missing markets and, 229; natural resources and, 8–12, 58, 60, 79–82, 102, 112, 181–82; nature and, 58–61, 71–76, 79, 82; posterity and, 86, 104–5, 112–13; reduction of, 105; Slow Movement and, 27; trends in, 138; trilemma of, 13–14, 230–36, 275; values and, 229, 236 convergence, 5, 122 Copenhagen summit, 62, 64–65, 68, 162, 292 Crackberry, 205 Crafts, Nicholas, 156–57 credit cards, 2, 21, 136, 138, 283 Csikszentmilhalyi, Mihaly, 45–49 Cultural Contradictions of Capitalism, The (Bell), 230, 235–36 Czechoslovakia, 239 Daly, Herman, 36 Damon, William, 48 Dasgupta, Partha, 61, 73, 77–78, 80, 82 David, Paul, 156 Dawkins, Richard, 118 debit cards, 2 decentralization, 7, 159, 218, 246, 255, 275, 291 defense budgets, 93 democracy, 2, 8, 16, 312n19; capitalism and, 230–38; culture and, 230–38; fairness and, 141; growth and, 268–69, 285–89, 296–97; institutions and, 242–43, 251–52, 262; nature and, 61, 66, 68; posterity and, 106; trust and, 175; values and, 230–35 Denmark, 125 Dickens, Charles, 131 Diener, Ed, 48, 49 Discourse on the Origin and Basis of Inequality among Men (Rousseau), 114 distribution, 29, 306n22; Asian influence and, 123; bifurcation of social norms and, 231–32; consumerism and, 22, 34, 45, 138; Easterlin Paradox and, 39–44; fairness and, 115–16, 123–27, 134, 136; food and, 10, 34; of goods and services, 7, 10, 24, 35–36, 40, 82, 99, 161, 188, 191, 198, 214, 218, 228–29, 282; income, 34, 116, 123–27, 134, 278; inequality and, 123 (see also inequality); institutions and, 253; measurement and, 181, 191–99, 202; paradox of prosperity and, 174; policy recommendations for, 276, 278; posterity and, 87, 94; trust and, 151, 171; unequal countries and, 124–30; values and, 226 Dorling, Danny, 224, 307n58, 308n34 Douglas, Michael, 221 downshifting, 11, 55 downsizing, 175, 246, 255 drugs, 44, 46, 137–38, 168–69, 191, 302n47 Easterlin, Richard, 39 Easterlin Paradox, 39–44 eBay, 198 Economics of Ecosystems and Biodiversity project, The (TEEB), 78–79 economies of scale, 253–58 Economy of Enough, 233; building blocks for, 12–17; first ten steps for, 294–98; growth and, 182; happiness and, 24; institutions and, 250–51, 258, 261–63; living standards and, 13, 65, 78–79, 106, 113, 136, 139, 151, 162, 190, 194, 267; Manifesto of, 18, 267–98; measurement and, 182, 186–88, 201–7; nature and, 59, 84; Ostrom on, 250–51; posterity and, 17, 85–113; values and, 217, 233–34, 238; Western consumers and, 22 (see also consumption) Edinburgh University, 221 efficiency, 2, 7; evidence–based policy and, 233–34; fairness and, 126; Fama hypothesis and, 221–22; happiness and, 9, 29–30, 61; institutions and, 245–46, 254–55, 261; limits to, 13; nature and, 61–62, 69, 82; network effects and, 253, 258; productivity and, 13 (see also productivity); trilemma of, 13–14, 230–36, 275; trust and, 158–59; values and, 210, 215–16, 221–35 Ehrlich, Paul, 70 e-mail, 252, 291 “End of History, The” (Fukuyama), 239 Engels, Friedrich, 14 Enlightenment, 7 Enron, 145 environmentalists. See nature European Union, 42, 59, 62, 162–63, 177, 219 Evolution of Cooperation, The (Axelrod), 118–19 “Evolution of Reciprocal Altruism, The” (Trivers), 118 externalities, 15, 70, 80, 211, 228–29, 249, 254 Facebook, 289 face-to-face contact, 7, 147, 165–68 fairness: altruism and, 118–22; antiglobalization and, 115; bankers and, 115, 133, 139, 143–44; behavioral econoics and, 116–17, 121; bonuses and, 87–88, 115, 139, 143–44, 193, 221, 223, 277–78, 295; capitalism and, 134, 137, 149; consequences for growth, 135–36; criticism of poor and, 142; democracy and, 141; emotion and, 118–19, 137; game theory and, 116–18, 121–22; government and, 121, 123, 131, 136; gratitude and, 118; growth and, 114–16, 121, 125, 127, 133–37; happiness and, 53; health issues and, 137–43; high salaries and, 130, 143–44, 193, 223, 277–78, 286, 296; inequality and, 115–16, 122–43; innate sense of, 114–19; innovation and, 121, 134; morals and, 116–20, 127, 131, 142, 144, 221; philosophy and, 114–15, 123; politics and, 114–16, 125–31, 135–36, 140–44; productivity and, 131, 135; Putnam on, 140–41; self-interest and, 114–22; social corrosiveness of, 139–44; social justice and, 31, 43, 53, 65, 123, 164, 224, 237, 286; statistics and, 115, 138; superstar effect and, 134; sustainability and, 115; technology and, 116, 131–34, 137; tit-for-tat response and, 118–19; trilemma of, 13–14, 230–36, 275; trust and, 139–44, 150, 157, 162, 172, 175–76; ultimatum game and, 116–17; unequal countries and, 124–30; wage penalties and, 133; well-being and, 137–43; World Values Survey and, 139 Fama, Eugene, 221–22 faxes, 252 Federal Reserve, 145 Ferguson, Niall, 100–101 financial crises: actions by governments and, 104–12; bubbles and, 3 (see also bubbles); capitalism and, 6–9 (see also capitalism); contracts and, 149–50; crashes and, 3, 28, 161, 244, 283; current, 54, 85, 90–91, 145; debt legacy of, 90–92; demographic implosion and, 95–100; goodwill and, 150; government debt and, 100–104; Great Depression and, 3, 28, 35, 61, 82, 150, 208, 281; growth debt and, 85–86; historical perspective on, 3–4; institutional blindness to, 87–88; intangible assets and, 149–50; intrusive regulatory practices and, 244; pension burden of, 92–95; as political crisis, 8–9; statistics of, 145; stimulus packages and, 91, 100–103, 111; structural change and, 25; total cost of current, 90–91; trust and, 88–89 (see also trust); weightless activities and, 150; welfare burden of, 92–95 Financial Times, 257 Fitzgerald, F.


pages: 403 words: 111,119

Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist by Kate Raworth

3D printing, Asian financial crisis, bank run, basic income, battle of ideas, Berlin Wall, bitcoin, blockchain, Branko Milanovic, Bretton Woods, Buckminster Fuller, call centre, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, choice architecture, clean water, cognitive bias, collapse of Lehman Brothers, complexity theory, creative destruction, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, dematerialisation, Douglas Engelbart, Douglas Engelbart, en.wikipedia.org, energy transition, Erik Brynjolfsson, ethereum blockchain, Eugene Fama: efficient market hypothesis, experimental economics, Exxon Valdez, Fall of the Berlin Wall, financial deregulation, Financial Instability Hypothesis, full employment, global supply chain, global village, Henri Poincaré, hiring and firing, Howard Zinn, Hyman Minsky, income inequality, Intergovernmental Panel on Climate Change (IPCC), invention of writing, invisible hand, Isaac Newton, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, land reform, land value tax, Landlord’s Game, loss aversion, low skilled workers, M-Pesa, Mahatma Gandhi, market fundamentalism, Martin Wolf, means of production, megacity, mobile money, Mont Pelerin Society, Myron Scholes, neoliberal agenda, Network effects, Occupy movement, off grid, offshore financial centre, oil shale / tar sands, out of africa, Paul Samuelson, peer-to-peer, planetary scale, price mechanism, quantitative easing, randomized controlled trial, Richard Thaler, Ronald Reagan, Second Machine Age, secular stagnation, shareholder value, sharing economy, Silicon Valley, Simon Kuznets, smart cities, smart meter, South Sea Bubble, statistical model, Steve Ballmer, The Chicago School, The Great Moderation, the map is not the territory, the market place, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, too big to fail, Torches of Freedom, trickle-down economics, ultimatum game, universal basic income, Upton Sinclair, Vilfredo Pareto, wikimedia commons

No need for fines or rewards to encourage compliance: the little green footprints artfully amplified an existing social norm.60 Network effects also influence social behaviour, as illustrated by the power of a prominent example. In October 2011, Brazil’s former president Lula da Silva went public with news of his throat cancer, saying he believed it was due to smoking cigarettes. Over the following four weeks, there was a national surge in Google searches for information about quitting smoking – far greater than similar searches made on World No Tobacco Day or even on New Year’s Day, when resolutions to quit are common. Likewise, when the UK reality TV star Jade Goody went public with her diagnosis of cervical cancer in 2009, there was a 43% increase in women making appointments to be tested.61 Those cases acted as warnings, but network effects can inspire too. Thanks to the courageous stance of the Pakistani educational activist Malala Yousafzai, millions of girls worldwide have been inspired by ‘the Malala effect’ to demand and cherish their right to an education.

Trickle-down economics may be a chimera, but trickle-down behaviourism is very real.’34 What is the implication for economic policy aiming to influence how we behave? Economists have traditionally sought to change people’s behaviour by changing the relative price of things, be it through a tax on sugar or a discount on solar panels. But such price signals often fail to achieve their expected results, Ormerod points out, because they can be drowned out by far stronger network effects, thanks to social norms and expectations of what others in the network are doing.35 At the same time, it may be possible to harness such interdependence for behavioural change, as we will see. From calculating to approximating Homo sapiens clearly can’t match the infallibility of rational economic man. That much has been agreed upon since the 1950s when Herbert Simon broke rank with his fellow economists and started to study how people actually behaved, finding their rationality to be severely ‘bounded’.

Thanks to the courageous stance of the Pakistani educational activist Malala Yousafzai, millions of girls worldwide have been inspired by ‘the Malala effect’ to demand and cherish their right to an education. Such effects work on a local scale too. Researchers in West Bengal, India found that when women started being appointed to lead village councils for the first time, local teenage girls began to have higher aspirations for their education and themselves, as did their parents. No prices, no payments, just pride.62 Nudges and network effects often work because they tap into underlying norms and values – such as duty, respect and care – and those values can be activated directly. That’s what researchers in the US discovered when they set out to explore how to prompt pro-environmental behaviour. They set up signs at a petrol station inviting passing motorists to have a free tyre check, offering either financial, safety or environmental reasons for doing so.


pages: 290 words: 87,549

The Airbnb Story: How Three Ordinary Guys Disrupted an Industry, Made Billions...and Created Plenty of Controversy by Leigh Gallagher

Airbnb, Amazon Web Services, barriers to entry, Bernie Sanders, cloud computing, crowdsourcing, don't be evil, Donald Trump, East Village, Elon Musk, housing crisis, iterative process, Jeff Bezos, Jony Ive, Justin.tv, Lyft, Marc Andreessen, Mark Zuckerberg, medical residency, Menlo Park, Network effects, Paul Buchheit, Paul Graham, performance metric, Peter Thiel, RFID, Sand Hill Road, Saturday Night Live, sharing economy, side project, Silicon Valley, Silicon Valley startup, South of Market, San Francisco, Startup school, Steve Jobs, TaskRabbit, the payments system, Tony Hsieh, Y Combinator, yield management

The 3 percent host-booking fee basically covers payment processing only; if anything, Airbnb subsidizes hosts with not just the fee but also its free-professional-photography policy and many other forms of coddling, from mailing out free mugs to featuring stories about some of the hosts on its website to flying certain hosts to its occasional launch events and annual conventions. Airbnb’s business is fundamentally about leveraging a network effect: the more people who list on Airbnb, the more inherently attractive the platform becomes to anyone who wants to travel, because there are more choices; and the more people who travel, the more appealing it becomes for people to list on it, because there are more customers. In Airbnb’s case, because its product is travel and the very act of using it involves moving from point A to point B, it is a global network effect enabled by fast and cheap cross-pollination: when a traveler from France uses Airbnb in New York, he or she is more likely to go back to France and consider hosting, or to talk up the company to his or her friends, sparking awareness and ultimately leading to more listing activity in that market.

But when they tried to open the site, they realized it had crashed—and they hadn’t brought their slide deck. “It was mostly us staring at each other for an hour,” Chesky later said. Maples did not invest. The founders had another problem leading up to the DNC, which was supply: no one wanted to list his or her home if no one else was going to book it; and with few homes listed, no one would use the site. They weren’t going to be able to get off the ground, let alone trigger any kind of “network effect,” where the more people use something, the more valuable it becomes—leading even more people to use it. Their preliminary outreach showed them people either didn’t want to rent their homes or thought they were being asked to participate in some kind of weird social experiment. Chesky may not always have known what angels or slide decks were, but he and his cofounders always had a very good instinct for using the media, and, much like that first October weekend, they knew that success or failure lay in their ability to drum up news coverage.

These two points are often continents away from each other, yet new markets are seeded quickly, cheaply, and organically, without staffers or teams ever having to set foot in them. This is a big difference between Airbnb and, say, Uber, which has to physically launch each new market with a heavy investment of fresh marketing, employees, and other resources. The vast majority of Airbnb’s growth, both travelers and listings, has come through these travel patterns and this global network effect. You can look at Airbnb’s size and scale in a number of ways. The easiest is those 140 million “guest arrivals” since its inception. Its 3 million active listings—80 percent of which are outside North America—makes Airbnb the largest provider of accommodations in the world, bigger than any hotel chain. (With its acquisition of Starwood, Marriott International has the largest inventory of any hotel company, with 1.1 million rooms.)


pages: 294 words: 82,438

Simple Rules: How to Thrive in a Complex World by Donald Sull, Kathleen M. Eisenhardt

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

Affordable Care Act / Obamacare, Airbnb, asset allocation, Atul Gawande, barriers to entry, Basel III, Berlin Wall, carbon footprint, Checklist Manifesto, complexity theory, Craig Reynolds: boids flock, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversification, drone strike, en.wikipedia.org, European colonialism, Exxon Valdez, facts on the ground, Fall of the Berlin Wall, haute cuisine, invention of the printing press, Isaac Newton, Kickstarter, late fees, Lean Startup, Louis Pasteur, Lyft, Moneyball by Michael Lewis explains big data, Nate Silver, Network effects, obamacare, Paul Graham, performance metric, price anchoring, RAND corporation, risk/return, Saturday Night Live, sharing economy, Silicon Valley, Startup school, statistical model, Steve Jobs, TaskRabbit, The Signal and the Noise by Nate Silver, transportation-network company, two-sided market, Wall-E, web application, Y Combinator, Zipcar

To grow, shared-economy companies have to keep both sides of the market—sellers and buyers—happy. And growing matters, because these companies face what are known as network effects—in other words, the positively reinforcing cycle in which more buyers attract more sellers and vice versa. Network effects can create exploding growth for the first company or two in a market sector, but they can also make success impossible for later and slower ones. For Airbnb to succeed, the company needed lots of good hosts to attract guests, and lots of good guests to attract hosts. The challenge was to get this chicken-and-egg cycle of network effects going. Joe and Brian brought in Nate Blecharczyk (Joe’s former roommate) as the company’s technical founder. Because of the success they’d had renting out their apartment space during the San Francisco design conference, they made it a rule to focus their young business on cities hosting conferences and festivals, with the rationale that these events attract lots of attendees on tight budgets.

., [>], [>], [>] Montsma, Sandrine, [>] Moss, Brandon, [>] “myth of requisite complexity,” [>]–[>], [>]–[>] Nader, Eduardo, [>] Nansen, Fridtjof, [>] Napoleon, [>] National Academy of Sciences, [>] National Oceanic and Atmospheric Agency. See NOAA whale-watching rules development natural selection and simple rules, [>]–[>] negotiating agreements, [>]–[>], [>]–[>] Netflix breaking rules/House of Cards, [>]–[>] data and, [>], [>] development/rules, [>]–[>], [>] human resource policy and, [>] network effects, [>]–[>] New York Times, [>] Newton, Sir Isaac, [>]–[>], [>] NOAA whale-watching rules development economics/whales decline, [>]–[>] negotiation approach and, [>]–[>], [>] n southern resident killer whales and, [>]–[>] whale-protecting rule, [>], [>]–[>] n Norgay, Tenzing, [>] Oakland Athletics/rule breaking, [>]–[>] Obama, Barack, [>]–[>] Okhuysen, Gerardo, [>]–[>] 1/N principle/Talmudic advice, [>]–[>], [>] n Oslejs, Janis Primekss/concrete and, [>]–[>], [>], [>]–[>] simple rules program, [>]–[>] overfitting, [>]–[>], [>]–[>] n Papinian, [>], [>] n Pasteur, Louis, [>] Paul III (pope), [>] PayPal, [>] Perlow, Leslie, [>], [>] personal issues/simple rules bottlenecks and, [>]–[>] charisma example, [>]–[>] crafting simple rules/research, [>]–[>] depression management example, [>]–[>] dieting example, [>], [>], [>], [>] measuring impact and, [>] moving needles and, [>]–[>], [>] n negotiating rules, [>]–[>] online dating example, [>]–[>] Pixar, [>]–[>], [>] n platitudes vs. rules, [>], [>], [>], [>] poker players/rules examples, [>]–[>] Pollan, Michael, [>], [>], [>] Primekss concrete, [>]–[>], [>], [>]–[>] printing press invention/significance, [>] prioritizing rules description, [>], [>] overview/examples, [>]–[>], [>]–[>] prison and bail decisions, [>], [>] problem types, [>]–[>] process rules description, [>] See also coordination rules; how-to rules; timing rules property rights, [>] rail system (Brazil), [>]–[>] rail system development (Tokyo), [>]–[>] Reynolds, Craig, [>]–[>] Rockefeller Foundation, [>] Rogers, Kenny, [>] Rome (ancient), [>]–[>] Rothschild, Nathan Mayer, [>]–[>] rule breaking California’s climate/gardening (Emily), [>]–[>] Netflix/House of Cards, [>]–[>] Oakland Athletics, [>]–[>] Scott vs.


pages: 468 words: 124,573

How to Build a Billion Dollar App: Discover the Secrets of the Most Successful Entrepreneurs of Our Time by George Berkowski

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

Airbnb, Amazon Web Services, barriers to entry, Black Swan, business intelligence, call centre, crowdsourcing, en.wikipedia.org, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, iterative process, Jeff Bezos, Jony Ive, Kickstarter, knowledge worker, Lean Startup, loose coupling, Marc Andreessen, Mark Zuckerberg, minimum viable product, move fast and break things, move fast and break things, Network effects, Oculus Rift, Paul Graham, QR code, Ruby on Rails, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, software as a service, software is eating the world, Steve Jobs, Steven Levy, Y Combinator

Chapter 31 Killer Product Expansion When the best mobile-app companies scale, their products do not stand still. These companies constantly seek a new way to delight users more, become even more sticky or launch inventive ways to make it easier for users to spend more money. At scale, the product challenge is slightly different. It’s not just about launching ‘simple’ features. Real product innovation involves taking advantage of the scale you already have, of leveraging network effects to become even more powerful. Network effects are massive: passengers use Uber because it has more cars than the competitors; drivers work for Uber because it has more passengers than the other apps. It’s a system that feeds off itself, one that reinforces itself. Merchants use the Square register app because it’s simple, beautiful and gives them the ability to process credit cards. But now customers use the Square Wallet app to pay in a store because increasing numbers of merchants use the register app that enables Square Wallet payments.

According to Harvard University professors Diana Tamir and Jason Mitchell, sharing information about ourselves is intrinsically rewarding and gives us a few squirts of dopamine every time we do it.14 When coming up with your big idea or big problem to solve, think about whether it is inherently social, or whether it could be made social, thus rendering it a lot more disruptive and a lot more powerful. People love to share rich content – such as photos, news and magazine articles – and this builds very strong network effects. A great example is Instagram. One of the main ways it drove growth from the very first day was by allowing users to simultaneously share their photos on Facebook and Twitter from the moment the photo was taken using the Instagram app. This massively increased the reach of the new app to big social networks – with very compelling photo content. This promotion of the Instagram app on Twitter and Facebook led people to its website to download the app.

But it did have a basic user registration function, allowed you to add friends, and also allowed you to send messages to those friends that disappeared after 10 seconds. The app was very much an MVP, a minimum viable product. They invited a bunch of college and high school students to use it, and they invited their friends. Their user-acquisition metric was self-sustaining (because of the inherent network effect of users inviting their friends). Their user activation (effectively creating an account) converted at close to 100 per cent because it was a super-simple registration (just a user name and password). Their retention started growing as users began messaging one another and sending snaps (or photos), and their referral metric was off the charts because it was baked into the app (the app works better when you invite more friends to it).


The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory by Kariappa Bheemaiah

accounting loophole / creative accounting, Ada Lovelace, Airbnb, algorithmic trading, asset allocation, autonomous vehicles, balance sheet recession, bank run, banks create money, Basel III, basic income, Ben Bernanke: helicopter money, bitcoin, blockchain, Bretton Woods, business process, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, cashless society, cellular automata, central bank independence, Claude Shannon: information theory, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, complexity theory, constrained optimization, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, David Graeber, deskilling, Diane Coyle, discrete time, distributed ledger, diversification, double entry bookkeeping, ethereum blockchain, fiat currency, financial innovation, financial intermediation, Flash crash, floating exchange rates, Fractional reserve banking, full employment, George Akerlof, illegal immigration, income inequality, income per capita, inflation targeting, information asymmetry, interest rate derivative, inventory management, invisible hand, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, knowledge economy, labour market flexibility, large denomination, liquidity trap, London Whale, low skilled workers, M-Pesa, Marc Andreessen, market bubble, market fundamentalism, Mexican peso crisis / tequila crisis, money market fund, money: store of value / unit of account / medium of exchange, mortgage debt, natural language processing, Network effects, new economy, Nikolai Kondratiev, offshore financial centre, packet switching, Pareto efficiency, pattern recognition, peer-to-peer lending, Ponzi scheme, precariat, pre–internet, price mechanism, price stability, private sector deleveraging, profit maximization, QR code, quantitative easing, quantitative trading / quantitative finance, Ray Kurzweil, Real Time Gross Settlement, rent control, rent-seeking, Satoshi Nakamoto, Satyajit Das, savings glut, seigniorage, Silicon Valley, Skype, smart contracts, software as a service, software is eating the world, speech recognition, statistical model, Stephen Hawking, supply-chain management, technology bubble, The Chicago School, The Future of Employment, The Great Moderation, the market place, The Nature of the Firm, the payments system, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, too big to fail, trade liberalization, transaction costs, Turing machine, Turing test, universal basic income, Von Neumann architecture, Washington Consensus

The company is responsible for moving millions of dollars in investment and does so with a team of only 22 personnel. Almost every operation including fundraising, recruiting, engineering, systems operations, product development, customer service, marketing, inbound deal processing, and deal closing is done in code. Of the 22 personnel, 16 are coders or have coding experience. (Slayton, 2014). As digitization leads to massive increases in efficiency and network effects, markets are getting more Schumpeterian in the sense that those market players who are capable of digitizing business models are capable of overtaking existing incumbents and gaining larger portions of market share. In The Wealth of Nations, Adam Smith famously said that the division of labor is limited by the extent of the market. Thus, as digitization overcomes the physical barriers to access markets, we notice that it is creating room for specializations that address granular subdivisions in existing and niche markets.

Furthermore, there are interoperability issues between banks and clients: banks require a complete view of a company’s transaction flow to provide value services at key points of the value chain. However, as a large number of the processes are still manual in nature, there are a spate of platforms that provide individual solutions but with low interoperability. This lack of interoperability reduces transparency, creates a higher risk of fraud and higher fees, and does not allow for the development of network effects that can transform the industry. In order to respond to these limitations, an increasing number of institutions have opted for the use of open account transactions, where the exporter supplies the goods and the importer pays for them on reception or based on pre-agreed payment conditions. In recent times, open trade accounting has become increasingly popular and currently makes up 90% of global trade (Euro Banking Association, 2016).

This event has to be proved by the electronic reconciliation of data produced by the Swift TSU (trade services utility). 5 essDOCS is a UK-based trade services company that provides paperless trade documentation services, such as Electronic Bills of Lading (eB/Ls), Electronic Barge Nominations & Documents, Bank Payment Obligations plus (BPO+), eDocs, eDocumentary Collections, Electronic Bunker Receipts, etc. 6 SWIFT's Trade for Corporates, the MT798, offers corporates the use of established interbank industry standards in trade finance through structured messages. 4 99 Chapter 3 ■ Innovating Capitalism In spite of these changes, the complexity of regulation from border to border has meant that the interoperability problem still remains an issue and large-scale network effects remain elusive. Banks have adapted by providing online portals which allows their clients to replace paper documentation flows with digital data flows and provide added value services such as invoice matching, forecasting, and balance sheet and cash flow analysis. But even these changes have been insufficient in addressing the problem. The existence of this prevailing setback has resulted in new entrants trying to find solutions, which in turn has increased competition.


pages: 215 words: 55,212

The Mesh: Why the Future of Business Is Sharing by Lisa Gansky

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Airbnb, Amazon Mechanical Turk, Amazon Web Services, banking crisis, barriers to entry, carbon footprint, Chuck Templeton: OpenTable, cloud computing, credit crunch, crowdsourcing, diversification, Firefox, fixed income, Google Earth, industrial cluster, Internet of things, Kickstarter, late fees, Network effects, new economy, peer-to-peer lending, recommendation engine, RFID, Richard Florida, Richard Thaler, ride hailing / ride sharing, sharing economy, Silicon Valley, smart grid, social web, software as a service, TaskRabbit, the built environment, walkable city, yield management, young professional, Zipcar

We knew that people enjoyed sharing photos of events, and shaped our offer accordingly. At the time, people would share photo albums with on average five or six of their friends and family. Someone would go to a party, take a bunch of pictures, and share them. Friends and family members would see how fabulous they looked in a photo, and then buy the print, often signing up for an account of their own. We would pay to acquire one customer and get five for free. The “network effect,” as it’s known, was a new phenomenon then, but has grown dramatically in the years since. Newer photo services, such as Olapic, allow shots from anyone who attends an event, such as a wedding, to be uploaded in a single place and shared on social networking sites. panning for gold. or meet my friend, the filter. In social networks, certain people act as “discoverers.” I am one in particular domains.

See Social networking starting Mesh company Sweet Spot trends influencing growth of trust building Millennial generation Mobile networks digital translation to physical and flash branding as foundation of the Mesh share-based business operation users, increase in Modular design Mohsenin, Kamran Movie rentals online, Mesh companies Mozilla Firefox Music-based businesses, Mesh companies Natural ecosystem, relationship to Mesh ecosystem Netflix annual sales as information business Mesh strategy perfection recommendation engine recommendations Network effect Niche markets for maintaining/servicing products Mesh companies opening, reason for sharing as North Portland Tool Library (NPTL) Ofoto Olapic Ombudsman Open Architecture Network Open Design Open innovation service provider Open networks advantages of Architecture for Humanity communal IP concept and marketing products openness versus proprietary approach and product improvement software development OpenTable O’Reilly, Tim Ostrom, Elinor Own-to-Mesh model car-sharing services profits, generation from retirees as customers Partnerships characteristics of corporations and Mesh companies income generation from in Mesh ecosystem unexpected value of Patagonia recycled textiles of Walmart partnership Paul, Sunil Payne, Steven Peer-to-peer lending.

Croix Falls Cinema SAP Schneeveis, Bob School of Everything (SoE) Seely Brown, John Self-storage listings, Mesh companies SellaBand Seventymm Share-based business during holidays mobile networks as foundation and niche markets shareability, compatible services See also The Mesh Shea, Lucy Sinclair, Cameron Sivers, Derek Skinnipopcorn SmartyPig smava Social lending. See Loans/social lending Social networking importance to the Mesh Mesh companies negative events, broadcasting on on Netflix network effect privacy, importance of and product improvement for word-of-mouth advertising See also Facebook Software getting for startup Mesh open development Software as a service (SaaS) Sourcemap SpareFoot Spride Share Standardization of products Starting a Mesh company capital needs customers, identifying define/redefine/scale stages first mover advantage marketing primary questions serendipity as factor shareable assets, identifying software, ASP model Stohr, Kate Supply chain forward and reverse integration reverse supply chain Sustainable design Swishing Taxi Magic TCHO Technology, Mesh-friendly Mesh companies TED Prize thinkspace thredUP adaptability of case study Tool sharing, Mesh companies Toyota, broken trust Transaction fees Transparency and adaptability “age of radical transparency,” and trust building Transportation efficiency communities developed for See also Bike sharing; Car sharing Travel-related services, Mesh companies Trials Tripkick Trust building basics of broken trust, examples of and customer complaints customer misbehavior, dealing with by delighting customers discoverers as trust agents lost trust, rebuilding maintaining trust negative events, impact on and privacy practices proprietary versus open control reviews, keeping perspective social networks, role of starting slow, necessity of and transparency trials/samples for “virtuous circle of trust,” Tryvertising Twitter Tylenol tragedy Upcycling Mesh companies Vacation Rentals by Owner (VRBO) Virgin Corporation, Mesh strategy Volkswagen, idea solicitation on Web Walmart customer data, use of greening of integration with suppliers Mesh possibilities for waste, created by Waste disposal and climate change as resource underutilization Waste management government initiatives for Mesh companies in Mesh ecosystem in natural ecosystem raw materials, sharing recycling and reuse services reverse value chain yield management See also Recycling and reuse services Water Legacy Wattzon.com Westmill Wind Farm Co-operative WhipCar Wilcox, Ronald Wilhelm, Eric Williamson, Oliver Wine cooperatives, Mesh companies Word of mouth, power of Work-space sharing, Mesh companies World of Goods Yelp Yield management Zipcar customer experience with Mesh model for partners Zopa Zynga Table of Contents Title Page Copyright Page Dedication Introduction Chapter 1 - Getting to Know the Mesh Chapter 2 - The Mesh Advantage Chapter 3 - Mesh Design Chapter 4 - In with the Mesh Chapter 5 - In Mesh We Trust Chapter 6 - The Mesh as Ecosystem Chapter 7 - Open to the Mesh Chapter 8 - Mesh Inc.


pages: 138 words: 40,787

The Silent Intelligence: The Internet of Things by Daniel Kellmereit, Daniel Obodovski

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3D printing, Airbnb, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, business intelligence, call centre, Clayton Christensen, cloud computing, commoditize, connected car, crowdsourcing, data acquisition, en.wikipedia.org, Erik Brynjolfsson, first square of the chessboard, first square of the chessboard / second half of the chessboard, Freestyle chess, Google X / Alphabet X, Internet of things, lifelogging, Metcalfe’s law, Network effects, Paul Graham, Ray Kurzweil, RFID, Robert Metcalfe, self-driving car, Silicon Valley, smart cities, smart grid, software as a service, Steve Jobs, web application, Y Combinator, yield management

The last wire to disappear is the power cable — driven by advances in wireless power, energy harvesting, and power management. Finally, there is another important factor, which is the network effect. This tends to show exponential growth once you have a critical mass of intelligent items and connected items that are talking to one another. The law that affects this development is Metcalfe’s Law,32 which states that the value of a network is proportional to the square of the number of connected users of the system. This law is applicable not only to telecommunications networks and social networks, but also to connected things, like M2M nodes. Assuming such a network effect will take place, one can assume it will create huge value for the ecosystem. What this means for investors is that we are about to see an explosion of connected things and an explosion of data being generated.

This market is still highly fragmented and allows for high margins for system integrators, making many business cases less attractive than they could be. This market always reminds us of the mobile phone industry in the early days and the fragmentation issues that there were for a number of years. If a couple of players are able to design application platforms that allow for easy and cost-effective development and deployment of applications, these platforms would be able to benefit from massive network effects, like the ones we have seen around mobile platforms starting in 2006. Also, data analysis and workflow optimization will be an interesting growth market going forward. Because these markets are still immature at this point, companies that are able to become central market players will have a very attractive position. The last segment to be mentioned is end-to-end solutions providers. Being able to take the complexity out of solution design and become a comprehensive one-stop shop will be an attractive proposition for technology companies and system integrators.


pages: 903 words: 235,753

The Stack: On Software and Sovereignty by Benjamin H. Bratton

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1960s counterculture, 3D printing, 4chan, Ada Lovelace, additive manufacturing, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, basic income, Benevolent Dictator For Life (BDFL), Berlin Wall, bioinformatics, bitcoin, blockchain, Buckminster Fuller, Burning Man, call centre, carbon footprint, carbon-based life, Cass Sunstein, Celebration, Florida, charter city, clean water, cloud computing, connected car, corporate governance, crowdsourcing, cryptocurrency, dark matter, David Graeber, deglobalization, dematerialisation, disintermediation, distributed generation, don't be evil, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, Eratosthenes, ethereum blockchain, facts on the ground, Flash crash, Frank Gehry, Frederick Winslow Taylor, future of work, Georg Cantor, gig economy, global supply chain, Google Earth, Google Glasses, Guggenheim Bilbao, High speed trading, Hyperloop, illegal immigration, industrial robot, information retrieval, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, John Markoff, Jony Ive, Julian Assange, Khan Academy, liberal capitalism, lifelogging, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, peer-to-peer, performance metric, personalized medicine, Peter Eisenman, Peter Thiel, phenotype, Philip Mirowski, Pierre-Simon Laplace, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Robert Bork, Sand Hill Road, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, smart cities, smart grid, smart meter, social graph, software studies, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Startup school, statistical arbitrage, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, Superbowl ad, supply-chain management, supply-chain management software, TaskRabbit, the built environment, The Chicago School, the scientific method, Torches of Freedom, transaction costs, Turing complete, Turing machine, Turing test, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, Westphalian system, WikiLeaks, working poor, Y Combinator

This may insert machine control at almost any point, amplifying or diverting human control over any machine in which the User happens to be installed, or even of the whole infrastructural landscape in which those machines swarm together. For example, the integrated design of driverless cars includes navigation interfaces, computationally intensive and environmentally aware rolling hardware, and street systems that can stage the network effects of hundreds of thousands speeding robots at once. The next stable form of the “automobile” (a description that will become perhaps more and more accurate) may be as a mobile Cloud platform inside of which Users navigate the City layer of a larger Stack according to augmented scenery Interfacial overlays and powered by grids of electrons as well as bits. Planetary-scale computation involves the whole Earth from which silica, steel, and all manner of conflict minerals are drawn.

Those models may represent a rigorously discrete view of the platform's internal operations, its external environment, or, most likely, some combination of the internal and the external that measures platform performance according to metrics evaluating its outward-facing systems.10 6..  Platforms’ mediation of User-input information may result in an increase in the value of that information for the User. Platform network effects absorb and train that information, making it more visible, more structured, and more extensible for the individual User or in relation to other Users who make further use of it, thereby increasing its social value. At the same time, it is likely the platform itself that derives the most significant net profit from these circulations in total. Each time a User interacts with a platform's governing algorithms, it also trains those decision models, however incrementally, to better evaluate subsequent transactions.

Platforms that organize existing systems and information tend to achieve generative entrenchment more quickly than those that seek to introduce new systems from scratch. Users will make tactical use of some platform interfaces to link some existing systems, and in doing so they are incentivized to incorporate more of their own interests within these systems. Subsequent Users are incentivized to link their systems to benefit from the network effects set in motion by earlier Users, who in turn enjoy increasing network benefits as more User systems are incorporated over time. The platform is able to realize platform surplus value from this generative entrenchment. 15..  Platforms link actors, information, and events across multiple spatial and temporal scales at once. Platform ubiquity makes it more robust in relation to some threats, both intrinsic and extrinsic, and more vulnerable in relation to others.


pages: 361 words: 81,068

The Internet Is Not the Answer by Andrew Keen

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3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, augmented reality, Bay Area Rapid Transit, Berlin Wall, bitcoin, Black Swan, Bob Geldof, Burning Man, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, David Brooks, disintermediation, Donald Davies, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, full employment, future of work, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Metcalfe’s law, move fast and break things, move fast and break things, Nate Silver, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, Plutocrats, plutocrats, Potemkin village, precariat, pre–internet, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Robert Metcalfe, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, TaskRabbit, Ted Nelson, telemarketer, The Future of Employment, the medium is the message, the new new thing, Thomas L Friedman, Tyler Cowen: Great Stagnation, Uber for X, urban planning, Vannevar Bush, Whole Earth Catalog, WikiLeaks, winner-take-all economy, working poor, Y Combinator

Writing in the New York Times to explain “why Bitcoin matters,” Marc Andreessen—who now is the managing partner of Andreessen Horowitz, a $4 billion Silicon Valley venture fund with $50 million invested in Bitcoin-based startups like the virtual wallet Coinbase—argues that this new digital money represents “a classic network effect, a positive feedback loop.” As with the Web, Andreessen says, the more people who use the new currency, “the more valuable Bitcoin is for the people who use it.”107 “A mysterious new technology emerges, seemingly out of nowhere, but actually the result of two decades of intense research and development by nearly anonymous researchers,” writes Andreessen, predicting the historical significance of this networked currency. “What technology am I talking about? Personal computers in 1975, the Internet in 1993, and—I believe—Bitcoin in 2014.”108 What Silicon Valley euphemistically calls the “sharing economy” is a preview of this distributed capitalism system powered by the network effect of positive feedback loops. Investors like Andreessen see the Internet—a supposedly hyperefficient, “frictionless” platform for buyers and sellers—as an upgrade to the structural inefficiencies of the top-down twentieth-century economy.

This was followed by Friendster in 2002 and then, in 2003, by the Los Angeles–based MySpace, a social network with a music and Hollywood focus that, at its 2008 peak, when it was acquired by News Corporation for $580 million, had 75.9 million members.86 But Facebook, which until September 2006 was exclusively made up of high school and university students, offered a less cluttered and more intuitive interface than MySpace. So, having opened its doors to the world outside of schools and universities, the so-called Mark Zuckerberg Production quickly became the Internet’s largest social network, amassing 100 million members by August 2008. And then the network effect, that positive feedback loop that makes the Internet such a classic winner-take-all market, kicked in. By February 2010, the Facebook community had grown to 400 million members, who spent 8 billion minutes each day on a network already operating in 75 different languages.87 Facebook had become the world’s second most popular Internet site after Google, a position that it’s maintained ever since.

The Chapman University geographer Joel Kotkin has broken down what he calls this “new feudalism” into different classes, including “oligarch” billionaires like Thiel and Uber’s Travis Kalanick, the “clerisy” of media commentators like Kevin Kelly, the “new serfs” of the working poor and the unemployed, and the “yeomanry” of the old “private sector middle class,” the professionals and skilled workers in towns like Rochester who are victims of the new winner-take-all networked economy.81 The respected MIT economists Erik Brynjolfsson and Andrew McAfee, who are cautiously optimistic about what they call “the brilliant technologies” of “the Second Machine Age,” acknowledge that our networked society is creating a world of “stars and superstars” in a “winner-take-all” economy. It’s the network effect, Brynjolfsson and McAfee admit, reflecting the arguments of Frank and Cook—a consequence, they say, of the “vast improvements in telecommunications” and the “digitalization of more and more information, goods and services.” The Nobel Prize–winning Princeton economist Paul Krugman also sees a “much darker picture” of “the effects of technology on labor.” Throughout the second half of the twentieth century, Krugman says, workers competed against other workers for resources.


pages: 370 words: 102,823

Rethinking Capitalism: Economics and Policy for Sustainable and Inclusive Growth by Michael Jacobs, Mariana Mazzucato

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3D printing, balance sheet recession, banking crisis, basic income, Bernie Sanders, Bretton Woods, business climate, Carmen Reinhart, central bank independence, collaborative economy, complexity theory, conceptual framework, corporate governance, corporate social responsibility, creative destruction, credit crunch, Credit Default Swap, crony capitalism, David Ricardo: comparative advantage, decarbonisation, deindustrialization, dematerialisation, Detroit bankruptcy, double entry bookkeeping, Elon Musk, endogenous growth, energy security, eurozone crisis, factory automation, facts on the ground, fiat currency, Financial Instability Hypothesis, financial intermediation, forward guidance, full employment, G4S, Gini coefficient, Growth in a Time of Debt, Hyman Minsky, income inequality, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Internet of things, investor state dispute settlement, invisible hand, Isaac Newton, Joseph Schumpeter, Kenneth Rogoff, knowledge economy, labour market flexibility, low skilled workers, Martin Wolf, mass incarceration, Mont Pelerin Society, neoliberal agenda, Network effects, new economy, non-tariff barriers, paradox of thrift, Paul Samuelson, price stability, private sector deleveraging, quantitative easing, QWERTY keyboard, railway mania, rent-seeking, road to serfdom, savings glut, Second Machine Age, secular stagnation, shareholder value, sharing economy, Silicon Valley, Steve Jobs, the built environment, The Great Moderation, The Spirit Level, Thorstein Veblen, too big to fail, total factor productivity, transaction costs, trickle-down economics, universal basic income, very high income

Markets are ‘embedded’ in these wider institutional structures and social, legal and cultural conditions.38 In the modern world, as Polanyi pointed out, the concept of a ‘free’ market is a construct of economic theory, not an empirical observation.39 Indeed, he observed that the national capitalist market was effectively forced into existence through public policy—there was nothing ‘natural’ or universal about it.40 The orthodox notion of competition between firms is equally misleading. Many of the most important markets in modern capitalism are oligopolistic in form, characterised by economies of scale and ‘network effects’ that lead to concentration and benefit incumbents. But even where there is greater competition, capitalist businesses are not all the same, forced to behave in similar ways by the external forces of ‘the market’. On the contrary, as Lazonick shows, what we actually observe is persistent heterogeneity, both in businesses’ internal characteristics and in their reactions to different market circumstances.

Without strong policy, innovation activity tends to be focused towards the incumbent, dominant technologies, where returns on incremental improvements are easily observed and understood. However, the alignment of expectations on the likely shape of future energy networks and innovations can lead to a ‘tipping point’ where the nature and direction of mainstream innovation activity can switch quickly. This can become self-reinforcing through new network effects. So long as one network technology is dominant, products and services linked to the use of that network will receive the bulk of innovation activity and there will be less effort committed to developing an alternative; but if a new technology network becomes dominant then innovation activity can shift quickly. The recent rapid development of energy storage technologies in the wake of the growth of renewables—storage being a principal means to cope with the intermittency of solar and wind power—provides a powerful example.

Musk realised that fossil-driven networks are hard to dislodge given the vast existing network of petrol stations, and vested interests of car dealerships, that make driving a combustion-engine car so much the norm.22 Rather than trying to win this battle alone, Tesla decided to expand the new market by stimulating the innovative resources of all car companies. Since the industrial revolution, firms have frequently exploited this path-dependence in technology adoption and network effects in order to diffuse their innovations and create new markets.23 Toyota followed suit. A striking finding of recent research is that the potential spillovers from low-carbon innovation to other sectors—one of the factors which helps to drive overall growth—may be higher than for other technologies.24 Aghion et al. provide empirical evidence both for geographical knowledge spillovers (where a firm’s choice of innovation path is influenced by the practice of the countries where its researchers are located) and for path-dependence (where firms tend to direct innovation towards what they are already good at).25 Using data on 1 million patents and 3 million citations, Dechezleprêtre et al. suggest that spillovers from low-carbon innovation in the energy production and transportation sectors are more than 40 per cent greater than in conventional technologies.26 At the same time Acemoglu et al. provide a powerful theoretical case to suggest that once systems of clean innovation have been started up, they may be more productive than conventional alternatives based on existing technologies.27 The lesson for policy-makers and economists here is an important one.


pages: 391 words: 97,018

Better, Stronger, Faster: The Myth of American Decline . . . And the Rise of a New Economy by Daniel Gross

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, Affordable Care Act / Obamacare, Airbnb, American Society of Civil Engineers: Report Card, asset-backed security, Bakken shale, banking crisis, BRICs, British Empire, business process, business process outsourcing, call centre, Carmen Reinhart, clean water, collapse of Lehman Brothers, collateralized debt obligation, commoditize, creative destruction, credit crunch, currency manipulation / currency intervention, demand response, Donald Trump, Frederick Winslow Taylor, high net worth, housing crisis, hydraulic fracturing, If something cannot go on forever, it will stop - Herbert Stein's Law, illegal immigration, index fund, intangible asset, intermodal, inventory management, Kenneth Rogoff, labor-force participation, LNG terminal, low skilled workers, Mark Zuckerberg, Martin Wolf, Maui Hawaii, McMansion, money market fund, mortgage debt, Network effects, new economy, obamacare, oil shale / tar sands, oil shock, peak oil, Plutocrats, plutocrats, price stability, quantitative easing, race to the bottom, reserve currency, reshoring, Richard Florida, rising living standards, risk tolerance, risk/return, Silicon Valley, Silicon Valley startup, six sigma, Skype, sovereign wealth fund, Steve Jobs, superstar cities, the High Line, transit-oriented development, Wall-E, Yogi Berra, zero-sum game, Zipcar

The United States has demonstrated a unique ability to develop such working models. When you have a large installed user base, a product or service rolled out on it can gain scale more quickly, and its value can grow exponentially. The development of the U.S. economy over time highlights the power of network effects—the notion that the value of a network to its owner, and to each user, rises as more people join. When a country has the world’s largest economy, with a large population spread over a large landmass and possessed of excellent connections to the global economy, network effects can work wonders. As a launching pad for products and services with global scale, the United States has certain advantages: the world’s largest domestic market; the paths blazed overseas for decades by brands like Coca-Cola, Disney, and McDonald’s; and the use of English as a commercial, financial, advertising, and consuming lingua franca.

Again, one can take these distressing metrics as further evidence of relative decline, or one can look at it this way: the United States manages to do an incredibly large volume of e-commerce with only half its population fully wired in, and with many Americans accessing the Internet more slowly than people in Gyor and Szeged. As hyper-connected and wired as the U.S. economy already is, there is a great deal of room for improvement.5 Recall the power of network effects. From the telegraph to the railroad, infrastructure has always served to rope people, especially in rural areas, into the wider, larger system, enriching both the lives of the individuals and the companies that ply their trade on the new medium. It’s no different with the Internet. Faster connections mean more people are digital, doing transactions, watching content, able to take advantage of free things and become more efficient consumers themselves.

Take the High Line. The elevated freight rail line on the West Side of Manhattan was unused and in disrepair until a group of arty visionaries had the idea of turning it into a park. It has become a platform for billions of dollars of investment in stores and restaurants, condominiums, offices, and hotels. Not every place is New York, but many regions and many cities could benefit from the sort of network effects that New York enjoys. Many of the biggest metropolitan areas in the United States are remarkably unnetworked. Knitting physical space more tightly together in networks would help boost real estate values and encourage investment at a time when it is much needed. This process has already been happening, even as infrastructure enthusiasts wring their hands at the lack of investment. Contrary to the common view, significant investments and advancements have been made in recent years.


pages: 371 words: 108,317

The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future by Kevin Kelly

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3D printing, A Declaration of the Independence of Cyberspace, AI winter, Airbnb, Albert Einstein, Amazon Web Services, augmented reality, bank run, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, book scanning, Brewster Kahle, Burning Man, cloud computing, commoditize, computer age, connected car, crowdsourcing, dark matter, dematerialisation, Downton Abbey, Edward Snowden, Elon Musk, Filter Bubble, Freestyle chess, game design, Google Glasses, hive mind, Howard Rheingold, index card, indoor plumbing, industrial robot, Internet Archive, Internet of things, invention of movable type, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kickstarter, lifelogging, linked data, Lyft, M-Pesa, Marc Andreessen, Marshall McLuhan, means of production, megacity, Minecraft, multi-sided market, natural language processing, Netflix Prize, Network effects, new economy, Nicholas Carr, old-boy network, peer-to-peer, peer-to-peer lending, personalized medicine, placebo effect, planetary scale, postindustrial economy, recommendation engine, RFID, ride hailing / ride sharing, Rodney Brooks, self-driving car, sharing economy, Silicon Valley, slashdot, Snapchat, social graph, social web, software is eating the world, speech recognition, Stephen Hawking, Steven Levy, Ted Nelson, the scientific method, transport as a service, two-sided market, Uber for X, Watson beat the top human players on Jeopardy!, Whole Earth Review, zero-sum game

This perfect storm of cheap parallel computation, bigger data, and deeper algorithms generated the 60-years-in-the-making overnight success of AI. And this convergence suggests that as long as these technological trends continue—and there’s no reason to think they won’t—AI will keep improving. As it does, this cloud-based AI will become an increasingly ingrained part of our everyday life. But it will come at a price. Cloud computing empowers the law of increasing returns, sometimes called the network effect, which holds that the value of a network increases much faster as it grows bigger. The bigger the network, the more attractive it is to new users, which makes it even bigger and thus more attractive, and so on. A cloud that serves AI will obey the same law. The more people who use an AI, the smarter it gets. The smarter it gets, the more people who use it. The more people who use it, the smarter it gets.

“akin to building a rocket ship”: Caleb Garling, “Andrew Ng: Why ‘Deep Learning’ Is a Mandate for Humans, Not Just Machines,” Wired, May 5, 2015. In 2006, Geoff Hinton: Kate Allen, “How a Toronto Professor’s Research Revolutionized Artificial Intelligence,” Toronto Star, April 17, 2015. he dubbed “deep learning”: Yann LeCun, Yoshua Bengio, and Geoffrey Hinton, “Deep Learning,” Nature 521, no. 7553 (2015): 436–44. the network effect: Carl Shapiro and Hal R. Varian, Information Rules: A Strategic Guide to the Network Economy (Boston: Harvard Business Review Press, 1998). famous man-versus-machine match: “Deep Blue,” IBM 100: Icons of Progress, March 7, 2012. rather than competes against them: Owen Williams, “Garry Kasparov—Biography,” KasparovAgent.com, 2010. freestyle chess matches: Arno Nickel, Freestyle Chess, 2010.

., 70–71 and platform synergy, 122–25 and real-time on demand, 114–17 and renting, 117–18 and right of modification, 124–25 accountability, 260–64 Adobe, 113, 206 advertising, 177–89 aggregated information, 140, 147 Airbnb, 109, 113, 124, 172 algorithms and targeted advertising, 179–82 Alibaba, 109 Amazon and accessibility vs. ownership, 109 and artificial intelligence, 33 cloud of, 128, 129 and on-demand model of access, 115 as ecosystem, 124 and filtering systems, 171–72 and recommendation engines, 169 and robot technology, 50 and tracking technology, 254 and user reviews, 21, 72–73 anime, 198 annotation systems, 202 anonymity, 263–64 anthropomorphization of technology, 259 Apache software, 69, 141, 143 API (application programming interface), 23 Apple, 1–2, 123, 124, 246 Apple Pay, 65 Apple Watch, 224 Arthur, Brian, 193, 209 artificial intelligence (AI), 29–60 ability to think differently, 42–43, 48, 51–52 as accelerant of change, 30 as alien intelligence, 48 in chess, 41–42 and cloud-based services, 127 and collaboration, 273 and commodity consumer attention, 179 and complex questions, 47 concerns regarding, 44 and consciousness, 42 corporate investment in, 32 costs of, 29, 52–53 data informing, 39 and defining humanity, 48–49 and digital storage capacity, 265, 266–67 and emergence of the “holos,” 291 as enhancement of human intelligence, 41–42 and filtering systems, 175 of Google, 36–37 impact of, 29 learning ability of, 32–33, 40 and lifelogging, 251 networked, 30 and network effect, 40 potential applications for, 34–36 questions arising from, 284 specialized applications of, 42 in tagging book content, 98 technological breakthroughs influencing, 38–40 ubiquity of, 30, 33 and video games, 230 and visual intelligence, 203 See also robots arts and artists artist/audience inversion, 81 and augmented reality, 232 and authenticity, 70 and creative remixing, 209 and crowdfunding, 156–61 and low-cost reproduction, 87 and patronage, 72 public art, 232 attention, 168–69, 176, 177–89 audience, 88, 148–49, 155, 156–57 audio recording, 249.


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Exceptional People: How Migration Shaped Our World and Will Define Our Future by Ian Goldin, Geoffrey Cameron, Meera Balarajan

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Admiral Zheng, agricultural Revolution, barriers to entry, Berlin Wall, Branko Milanovic, British Empire, conceptual framework, creative destruction, demographic transition, Deng Xiaoping, endogenous growth, failed state, Fall of the Berlin Wall, Gini coefficient, global supply chain, guest worker program, illegal immigration, income inequality, income per capita, Intergovernmental Panel on Climate Change (IPCC), job automation, Joseph Schumpeter, knowledge economy, labor-force participation, labour mobility, Lao Tzu, life extension, low skilled workers, low-wage service sector, Malacca Straits, mass immigration, microcredit, Network effects, new economy, New Urbanism, old age dependency ratio, open borders, out of africa, price mechanism, purchasing power parity, Richard Florida, selection bias, Silicon Valley, Silicon Valley startup, Skype, spice trade, trade route, transaction costs, transatlantic slave trade, transatlantic slave trade, women in the workforce, working-age population

This migration stream eventually becomes self-sustaining, and as migrants maintain contact with family and friends at home, they create a “network effect” that increases the rate of migration even further. Networks relay information and resources that lower the risks for others to migrate, and a migration channel is opened up between source and destination locations through these networks. The continued movement of people through this channel strengthens the network and expands the number of people and locations it connects together. Over time and as migrant communities grow, networks can diminish in their significance as the connection between settled migrants and new arrivals from “home” weakens. Networks may eventually be used to discourage further migration if competition for migrant jobs in the destination country becomes more severe (see figure 4.2).41 Figure 4.2. Network effects of migration to a particular country.

Annual emigration rates, 1860-1913 (absolute deviations from trend) Figure 3.1. Immigration to the United States for selected years, 1900-1933 (thousands) Figure 3.2. Total number of Koreans in Japan, 1900-1944 (millions) Figure 3.3. European Immigrants into Argentina and Brazil after World War II (thousands) Figure 4.1. The relationship between socio-economic development and migration Figure 4.2. Network effects of migration to a particular country Figure 4.3. Age structure in Republic of Korea in 1960, 2000, and 2040 (projected) Figure 5.1. Patterns of global migration Figure 5.2. Low-skill migrants in Gulf Cooperation Council Countries Figure 5.3. The European Union, 2009 Figure 5.4. Propensity to migrate from A8 countries to the UK, 2005 Figure 5.5. Estimated number of world refugees (millions), 1960-2008 Figure 5.6.

.), Immigration Reconsidered: History, Sociology, and Politics. Oxford, UK: Oxford University Press, pp. 79–95. 38. Portes and Borocz, 1989: 612. 39. This general narrative of the migration process is drawn from Massey et al., 1993. 40. Castles, 1989: 106; George J. Borjas and Stephen G. Bronars. 1991. “Immigration and the Family,” Journal of Labour Economics 9(2): 123–148. 41. Gil S. Epstein. 2008. “Herd and Network Effects in Migration Decision-Making,” Journal of Ethnic and Migration Studies 34: 567–583. 42. Manolo I. Abella. 2004. “The Role of Recruiters in Labour Migration,” in Douglas S. Massey and J. Edward Taylor (eds.), International Migration: Prospects and Policies in a Global Market. Oxford, UK: Oxford University Press. 43. Ibid.: 201. 44. Ibid.: 201. 45. Stephen Castles. 2007. “Comparing the Experience of Five Major Emigration Countries,” Working Paper 7, International Migration Institute, James Martin 21st Century School, University of Oxford. 46.

From Airline Reservations to Sonic the Hedgehog: A History of the Software Industry by Martin Campbell-Kelly

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Apple II, Apple's 1984 Super Bowl advert, barriers to entry, Bill Gates: Altair 8800, business process, card file, computer age, computer vision, continuous integration, deskilling, Donald Knuth, Grace Hopper, information asymmetry, inventory management, John Markoff, John von Neumann, linear programming, Menlo Park, Network effects, popular electronics, RAND corporation, Robert X Cringely, Ronald Reagan, Silicon Valley, software patent, Steve Jobs, Steve Wozniak, Steven Levy, Thomas Kuhn: the structure of scientific revolutions

Backus and his team refined the system in response to feedback from users and released a new version in 1959. FORTRAN II contained 50,000 lines of code and took 50 programmeryears to develop. FORTRAN rapidly became the industry standard for scientific and engineering applications programming, and other manufacturers were forced to adopt it in order to compete with IBM. There was no conspiracy: FORTRAN was simply the first efficient and reliable programming language. What economists later called “network effects” made FORTRAN a standard language with little or no help from IBM. Users made software investments of tens of millions of lines of FORTRAN code, and when selecting a new computer—whether from IBM or another manufacturer—they needed a compatible FORTRAN system to protect their software investment, and also to share programs with others. (Though FORTRAN was the de facto standard for scientific programming, the data processing language COBOL later became an officially sanctioned standard.)

Profits were fed back into the development of software (then given away free) and product improvement, which had the effect of making System/360 more attractive to customers; the result was more sales and profits to be invested in further software development and product improvement, and so on. That virtuous circle gave IBM its 75 percent share of the mainframe market. By the time IBM unbundled its software, System/360 was already a standard platform, and independent software vendors produced software for the IBM platform in order to maximize their sales. These “network effects” further enhanced the desirability of the IBM mainframe. It should be noted that the success of System/360 was largely independent of its original technical merits. It was the mere fact that it was a standard platform that made it desirable. IBM’s market dominance could be explained only partially in terms of the economics of increasing returns. IBM was also subject to decreasing returns. For example, selling costs tended to rise at the margin, and IBM’s marketing resources and manufacturing facilities were constraints.

Bill Gates is not so much a wizard of technology as a wizard Not Only Microsoft 243 of precognition, of discerning the shape of the next game.”18 It is clear from The Road Ahead that what Gates calls “positive feedback” is an intuitive and informal equivalent to the increasing-returns model of the academic economists.19 We also know, from a memorandum dated June 1985 and subsequently published in a history of Apple Computer, that Gates was aware of the importance of network effects in establishing an operating-system standard.20 But until Microsoft opens its archives to independent scholars, we have only some tantalizing hints of the company’s strategic thinking and the extent to which Gates was responsible for it. In the meantime, another firm, Autodesk, has made its early strategic thinking publicly available in a book titled The Autodesk File.21 From 1987 to the present, Autodesk—manufacturer of the leading CAD package— has consistently been among the top ten players in the personal computer software industry.

The Future of Technology by Tom Standage

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air freight, barriers to entry, business process, business process outsourcing, call centre, Clayton Christensen, computer vision, connected car, corporate governance, creative destruction, disintermediation, distributed generation, double helix, experimental economics, full employment, hydrogen economy, industrial robot, informal economy, information asymmetry, interchangeable parts, job satisfaction, labour market flexibility, Marc Andreessen, market design, Menlo Park, millennium bug, moral hazard, natural language processing, Network effects, new economy, Nicholas Carr, optical character recognition, railway mania, rent-seeking, RFID, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, six sigma, Skype, smart grid, software as a service, spectrum auction, speech recognition, stem cell, Steve Ballmer, technology bubble, telemarketer, transcontinental railway, Y2K

In some ways, although it firms are the epitome of mass production, when it comes to standards they are still stuck in the craftsmen era, which explains in large part why they have been so amazingly profitable. Network effects make it even more attractive to control a technology, argue Carl Shapiro and Hal Varian, two economics professors, in Information Rules, still the best read on the network economy (Harvard Business School Press, 1998). If the value of a technology depends not just on its quality but also on the number of users, positive feedback can help one firm to dominate the market. For example, the more people are already connected to a data network using a particular transmission standard, the more people will see the point of hooking up to it. These network effects also explain why the it industry in the 1980s already started to move away from completely proprietary technology, the hallmark of the mainframe era.

Software is a service at heart, albeit an automated one, but it is sold much like a manufactured good. Customers have to pay large sums of money up front, bear much of the risk that a program may not work as promised and cannot readily switch vendors. it firms, for their part, have to spend a lot of resources on marketing and distribution, rather than concentrating on developing software that works well and is easy to use. Network effects and Wall Street make matters worse. In many markets it is a great advantage to be first, so vendors are tempted to release programs even if they are still riddled with bugs. And because equity analysts rightly consider software firms a risky investment, such firms must grow quickly to justify their relatively high share prices, pushing them to sell more programs than customers need. All this explains several peculiarities of the software business.

Collectively dubbed “ws splat” in geeky circles, these are now being adopted by the rest of the industry. This has raised hopes for a huge increase in their use in the next few 90 MAKE IT SIMPLE years (see Chart 3.2). Ronald 3.2 2.1 Towards ubiquity Schmelzer and Jason Web services, % of firms adopting Bloomberg at ZapThink, a 100 consultancy, think that web United 80 services are “nearing their tipStates EU ping point”, because they ben60 Asia efit from “the network effect: Pacific the adoption rate of the net40 work increases in proportion 20 to its utility”. In other words, FORECAST as with telephones or e-mail, 0 2002 03 04 05 06 07 08 09 10 a network with only a few Source: IDC people on it is not very useful; but as more people join it, it becomes exponentially more useful and thereby attracts even more members, and so on. Taking the idea of web services to its logical extreme, it is reasonable to ask why firms should continue to amass their own piles of Lego blocks, most of which will only duplicate the Lego blocks of business partners.


pages: 220 words: 73,451

Democratizing innovation by Eric von Hippel

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additive manufacturing, correlation coefficient, Debian, hacker house, informal economy, information asymmetry, inventory management, iterative process, James Watt: steam engine, knowledge economy, meta analysis, meta-analysis, Network effects, placebo effect, principal–agent problem, Richard Stallman, software patent, transaction costs, Vickrey auction

Free revealing may also increase an innovator’s profit in other ways. When an innovating user freely reveals an innovation, the direct result is to increase the diffusion of that innovation relative to what it would be if the innovation were either licensed at a fee or held secret. The innovating user may then benefit from the increase in diffusion via a number of effects. Among these are network effects. (The classic illustration of a network effect is that the value of each telephone goes up as more are sold, because the value of a phone is strongly affected by the number of others who can be contacted in the network.) In addition, and very importantly, an innovation that is freely revealed and adopted by others can become an informal standard that may preempt the development and/or commercialization of other versions of the innovation.

Active efforts by innovators to freely reveal—as opposed to sullen acceptance—are explicable because free revealing can provide innovators with significant private benefits as well as losses or risks of loss. Users who freely reveal what they have done often find that others then improve or suggest improvements to the innovation, to mutual benefit (Raymond 1999). Freely revealing users also may benefit from enhancement of reputation, from positive network effects due to increased diffusion of their innovation, and from other factors. Being the first to freely reveal a particular innovation can also enhance the benefits received, and so there can actually be a rush to reveal, much as scientists rush to publish in order to gain the benefits associated with being the first to have made a particular advancement. Innovation Communities (Chapter 7) Innovation by users tends to be widely distributed rather than concentrated among just a very few very innovative users.


pages: 280 words: 79,029

Smart Money: How High-Stakes Financial Innovation Is Reshaping Our WorldÑFor the Better by Andrew Palmer

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Affordable Care Act / Obamacare, algorithmic trading, Andrei Shleifer, asset-backed security, availability heuristic, bank run, banking crisis, Black-Scholes formula, bonus culture, break the buck, Bretton Woods, call centre, Carmen Reinhart, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, David Graeber, diversification, diversified portfolio, Edmond Halley, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, eurozone crisis, family office, financial deregulation, financial innovation, fixed income, Flash crash, Google Glasses, Gordon Gekko, high net worth, housing crisis, Hyman Minsky, implied volatility, income inequality, index fund, information asymmetry, Innovator's Dilemma, interest rate swap, Kenneth Rogoff, Kickstarter, late fees, London Interbank Offered Rate, Long Term Capital Management, loss aversion, margin call, Mark Zuckerberg, McMansion, money market fund, mortgage debt, mortgage tax deduction, Myron Scholes, negative equity, Network effects, Northern Rock, obamacare, payday loans, peer-to-peer lending, Peter Thiel, principal–agent problem, profit maximization, quantitative trading / quantitative finance, railway mania, randomized controlled trial, Richard Feynman, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, short selling, Silicon Valley, Silicon Valley startup, Skype, South Sea Bubble, sovereign wealth fund, statistical model, transaction costs, Tunguska event, unbanked and underbanked, underbanked, Vanguard fund, web application

Allowing for a default rate of 4 percent, and Lending Club’s servicing fees, the returns to investors were 9–10 percent, not too shabby given how low interest rates have been. Growth has been explosive. By December 2012, Lending Club had surpassed $1 billion in loans taken out since its launch in 2007. It had doubled that by the start of July 2013, hit the $3 billion mark by December of that year, and surpassed $6 billion by the end of September 2014. That sort of heft puts it well ahead of rivals. It also reflects what economists like to call “network effects.” A bigger marketplace attracts more borrowers and investors. It also increases liquidity for investors looking to sell off their loans before they mature. Lending Club is one among a whole series of peer-to-peer start-ups. Its biggest rival in the consumer arena is another San Francisco–based firm called Prosper, which stuttered for a few years but is also growing extremely fast. Across the Atlantic, Zopa, a London-based firm, can lay claim to being the industry pioneer: it has been going since 2005 and focuses on “prime” (that is, the most creditworthy) borrowers.

., 32 Keys, Benjamin, 48 Kharroubi, Enisse, 79 Kickstarter, 172 King, Stephen, 99 Klein, David, 182 Krugman, Paul, xv Lahoud, Sal, 166 Lang, Luke, 153, 161–162 Laplanche, Renaud, 179, 184, 188, 190, 193–194, 196–197 Latency, 53 Law of large numbers, 17 Layering, 57 Left-digit bias, 46 Lehman Brothers, x, 44, 65 Lending direct, 84 marketplace, 184 payday, 200 relationship-based, 11, 151, 206–208 secured, xiv, 76 unsecured, 206 See also Loans; Peer-to-peer lending Lending Club, 172, 179–180, 182–184, 187, 189, 194–195, 197 Leonardo of Pisa (Fibonacci), 19 Lerner, Josh, 59 Lethal pandemic, risk-modeling for demographic profile, 230 exceedance-probability curve, 231–232, 232 figure 3 historical data, 228–229 infectiousness and virulence, 229–230 location of outbreak, 230–231 Leverage, 51, 70–71, 80, 186, 188 Leverage ratio, 76–77 Lewis, Michael, 57 Liber Abaci or Book of Calculation (Fibonacci), 19 LIBOR (London Interbank Offered Rate), 41 Liebman, Jeffrey, 98 Life expectancy government reaction to, 128–129 projections of, 124–127, 126 figure 2 ratio of young to older people, 127–128 Life-insurance policies, 142 Life-settlements industry, 142–143 Life table, 20 Limited liability, 212 Liquidity, 12–14, 39, 185–186 List, John, 109 The Little Book of Behavioral Investing (Montier), 156 Lo, Andrew, 113–115, 117–123 Loans low-documentation, 48–49 secured, 76 small business, 181, 216 student, 164, 166–167, 169–171, 182 syndicated, 41 Victory Loans, 28 See also Lending; Peer-to-Peer lending Logistic regression, 201 London, early fire insurance in, 16–17 London, Great Fire of, 16 London Interbank Offered Rate (LIBOR), 41 Long-Term Capital Management, 123 Longevity, betting on, 143–144 Loss aversion, 136 Lotteries, 212, 213 Low-documentation loans, 48–49 Lumni, 165, 168, 175 Lustgarten, Anders, 111 Lynn, Jeff, 160–161 Mack, John, 180 Mahwah, New Jersey, 52, 53 Marginal borrowers assessment of, 216–217 behavioral finance and, 208–214 industrialization of credit, 206 microfinance and, 203 savings schemes, 209–214 small businesses, 215–219 unsecured lending to, 206 Wonga, 203, 205, 208 Marginal borrowers (continued) ZestFinance, 199, 202, 205–206 Maritime piracy, solutions to, 151–152 Maritime trade, role of in history of finance, 3, 7–8, 14, 17, 23 Market makers, 15–16, 55 MarketInvoice, 195, 207, 217–218 Marketplace lending, 184 Markowitz, Harry, 118 Massachusetts, use of inflation-protected bonds in, 26 Massachusetts, use of social-impact bonds in, 98 Matching engine, 52 Maturity transformation, 12–13, 187–188, 193 McKinsey & Company, ix, 42 Mercator Advisory Group, 203 Merrill, Charles, 28 Merrill, Douglas, 199, 201 Merrill Lynch, 28 Merton, Robert, 31, 113–114, 123–124, 129–132, 142, 145 Mian, Atif, 204 Michigan, University of, financial survey by, 134–135 Microfinance, 203 Micropayment model, 217 Microwave technology, 53 The Million Adventure, 213–214 Minsky, Hyman, 42 Minsky moment, 42 Mississippi scheme, 36 Mitchell, Justin, 166–167 Momentum Ignition, 57 Monaco, modeling risk of earthquake in, 227 Money, history of, 4–5 Money illusion, 73–74 Money laundering, 192 Money-market funds, 43, 44 Monkeys, Yale University study of loss aversion with, 136 Montier, James, 156–157 Moody, John, 24 Moody’s, 24, 235 Moore’s law, 114 Morgan Stanley, 188 Mortgage-backed securities, 49, 233 Mortgage credit by ZIP code, study of, 204 Mortgage debt, role of in 2007–2008 crisis, 69–70 Mortgage products, unsound, 36–37 Mortgage securitization, 47 Multisystemic therapy, 96 Munnell, Alicia, 129 Naked credit-default swaps, 143 Nature Biotechnology, on drug-development megafunds, 118 “Neglected Risks, Financial Innovation and Financial Fragility” (Gennaioli, Shleifer, and Vishny), 42 Network effects, 181 New York, skyscraper craze in, 74–75 New York City, prisoner-rehabilitation program in, 108 New York Stock Exchange (NYSE), 31, 52, 53, 61, 64 New York Times, Merrill Lynch ad in, 28 Noncorrelated assets, 122 Nonprofits, growth of in United States, 105–106 Northern Rock, x NYMEX, 60 NYSE Euronext, 52 NYSE (New York Stock Exchange), 31, 52, 53, 61, 64 OECD (Organization for Economic Co-operation and Development), 128, 147 Oldfield, Sean, 67–68, 80–84 OnDeck, 216–218 One Service, 94–95, 105, 112 Operating expense ratio, 188–189 Options, 15, 124 Order-to-trade ratios, 63 Oregon, interest in income-share agreements, 172, 176 Organization for Economic Co-operation and Development (OECD), 128, 147 Overtrading, 24 Packard, Norman, 60 Pandit, Vikram, 184 Park, Sun Young, 233 Partnership mortgage, 81 Pasion, 11 Pave, 166–168, 173, 175, 182 Payday lending Consumer Financial Protection Bureau, survey on, 200 information on applicants, acquisition of, 202 underwriting of, 201 PayPal, 219 Peak child, 127 Peak risk, 228 Peer-to-peer lending advantages of, 187–189 auction system, 195 big investors in, 183 borrowers, assessment of, 197 in Britain, 181 commercial mortgages, 181 CommonBond, 182, 184, 197 consumer credit, 181 diversification, 196 explained, 180 Funding Circle, 181–182, 189, 197 investors in, 195 Lending Club, 179–180, 182–184, 187, 189, 194–195, 197 network effects, 181 ordinary savers and, 184 Prosper, 181, 187, 195 RateSetter, 181, 187, 196 Relendex, 181 risk management, 195–197 securitization, 183–184, 196 Peer-to-peer lending (continued) small business loans, 181 SoFi, 184 student loans, 182 Zopa, 181, 187, 188, 195 Pensions, cost of, 125–126 Perry, Rick, 142–143 Peterborough, England, social-impact bond pilot in, 90–92, 94–95, 104–105, 112 Petri, Tom, 172 Pharmaceuticals, decline of investment in, 114–115 Piracy Reporting Centre, International Maritime Bureau, 151 Polese, Kim, 210 Poor, Henry Varnum, 24 “Portfolio Selection” (Markowitz), 118 Prediction Company, 60–61 Preferred shares, 25 Prepaid cards, 203 Present value of cash flows, 19 Prime borrowers, 197 Prince, Chuck, 50–51, 62 Principal-agent problem, 8 Prisoner rehabilitation programs, 90–91, 94–95, 98, 108, 112 Private-equity firms, 69, 85, 91, 105, 107 Projection bias, 72–73 Property banking crises and, xiv, 69 banking mistakes involving, 75–80 behavioral biases and, 72–75 dangerous characteristics of, 70–72 fresh thinking, need for, xvii, 80 investors’ systematic errors in, 74–75 perception of as safe investment, 76, 80 Prosper, 181, 187, 195 Provisioning funds, 187 Put options, 9, 82 Quants, 19, 63, 113 QuickBooks, 218 Quote stuffing, 57 Raffray, André-François, 144 Railways, affect of on finance, 23–25 Randomized control trials (RCTs), 101 Raphoen, Christoffel, 15–16 Raphoen, Jan, 15–16 RateSetter, 181, 187, 196 RCTs (randomized control trials), 101 Ready for Zero, 210–211 Rectangularization, 125, 126 figure 2 Regulation NMS, 61 Reinhart, Carmen, 35 Reinsurance, 224 Relendex, 181 Rentes viagères, 20 Repurchase “repo” transactions, 15, 185 Research-backed obligations, 119 Reserve Primary Fund, 44 Retirement, funding for anchoring effect, 137–138 annuities, 139 auto-enrollment in pension schemes, 135 auto-escalation, 135–136 conventional funding, 127–128 decumulation, 138–139 government reaction to increased longevity, 128–129 home equity, 139–140 life expectancy, projections of, 124–127, 126 figure 2 life insurance policies, cash-surrender value of, 142 personal retirement savings, 128–129, 132–133 replacement rate, 125 reverse mortgage, 140–142 savings cues, experiment with, 137 SmartNest, 129–131 Reverse mortgages, 140–142 Risk-adjusted returns, 118 Risk appetite, 116 Risk assessment, 24, 45, 77–78, 208 Risk aversion, 116, 215 Risk-based capital, 77 Risk-based pricing model, 176 Risk management, 55, 117–118, 123, 195–197 Risk Management Solutions, 222 Risk sharing, 8, 82 Risk-transfer instrument, 226 Risk weights, 77–78 Rogoff, Kenneth, 35 “The Role of Government in Education” (Friedman), 165 Roman Empire business corporation in, 7 financial crisis in, 36 forerunners of banks in, 11 maritime insurance in, 8 Rotating Savings and Credit Associations (ROSCAs), 209–210 Roulette wheel, use of in experiment on anchoring, 138 Royal Bank of Scotland, 186 Rubio, Marco, 172 Russia, mortgage market in, 67 S-curve, in diffusion of innovations, 45 Salmon, Felix, 155 Samurai bonds, 27 Satsuma Rebellion (1877), 27 Sauter, George, 58 Save to Win, 214 Savings-and-loan crisis in US (1990s), 30 Savings cues, experiment with, 137 Scared Straight social program, 101 Scholes, Myron, 31, 123–124 Science, Technology, and Industry Scoreboard of OECD, 147 Securities and Exchange Commission (SEC), 54, 56, 57, 58, 64 Securities markets, 14 Securitization, xi, 20, 37–38, 117–122, 183–184, 196, 236 Seedrs, 160–161 Sellaband, 159 Shared equity, 80–84 Shared-equity mortgage, 84 Shepard, Chris, xii–xiii Shiller, Robert, xv–xvi, 242 Shleifer, Andrei, 42, 44 Short termism, 58 SIBs.

., 32 Keys, Benjamin, 48 Kharroubi, Enisse, 79 Kickstarter, 172 King, Stephen, 99 Klein, David, 182 Krugman, Paul, xv Lahoud, Sal, 166 Lang, Luke, 153, 161–162 Laplanche, Renaud, 179, 184, 188, 190, 193–194, 196–197 Latency, 53 Law of large numbers, 17 Layering, 57 Left-digit bias, 46 Lehman Brothers, x, 44, 65 Lending direct, 84 marketplace, 184 payday, 200 relationship-based, 11, 151, 206–208 secured, xiv, 76 unsecured, 206 See also Loans; Peer-to-peer lending Lending Club, 172, 179–180, 182–184, 187, 189, 194–195, 197 Leonardo of Pisa (Fibonacci), 19 Lerner, Josh, 59 Lethal pandemic, risk-modeling for demographic profile, 230 exceedance-probability curve, 231–232, 232 figure 3 historical data, 228–229 infectiousness and virulence, 229–230 location of outbreak, 230–231 Leverage, 51, 70–71, 80, 186, 188 Leverage ratio, 76–77 Lewis, Michael, 57 Liber Abaci or Book of Calculation (Fibonacci), 19 LIBOR (London Interbank Offered Rate), 41 Liebman, Jeffrey, 98 Life expectancy government reaction to, 128–129 projections of, 124–127, 126 figure 2 ratio of young to older people, 127–128 Life-insurance policies, 142 Life-settlements industry, 142–143 Life table, 20 Limited liability, 212 Liquidity, 12–14, 39, 185–186 List, John, 109 The Little Book of Behavioral Investing (Montier), 156 Lo, Andrew, 113–115, 117–123 Loans low-documentation, 48–49 secured, 76 small business, 181, 216 student, 164, 166–167, 169–171, 182 syndicated, 41 Victory Loans, 28 See also Lending; Peer-to-Peer lending Logistic regression, 201 London, early fire insurance in, 16–17 London, Great Fire of, 16 London Interbank Offered Rate (LIBOR), 41 Long-Term Capital Management, 123 Longevity, betting on, 143–144 Loss aversion, 136 Lotteries, 212, 213 Low-documentation loans, 48–49 Lumni, 165, 168, 175 Lustgarten, Anders, 111 Lynn, Jeff, 160–161 Mack, John, 180 Mahwah, New Jersey, 52, 53 Marginal borrowers assessment of, 216–217 behavioral finance and, 208–214 industrialization of credit, 206 microfinance and, 203 savings schemes, 209–214 small businesses, 215–219 unsecured lending to, 206 Wonga, 203, 205, 208 Marginal borrowers (continued) ZestFinance, 199, 202, 205–206 Maritime piracy, solutions to, 151–152 Maritime trade, role of in history of finance, 3, 7–8, 14, 17, 23 Market makers, 15–16, 55 MarketInvoice, 195, 207, 217–218 Marketplace lending, 184 Markowitz, Harry, 118 Massachusetts, use of inflation-protected bonds in, 26 Massachusetts, use of social-impact bonds in, 98 Matching engine, 52 Maturity transformation, 12–13, 187–188, 193 McKinsey & Company, ix, 42 Mercator Advisory Group, 203 Merrill, Charles, 28 Merrill, Douglas, 199, 201 Merrill Lynch, 28 Merton, Robert, 31, 113–114, 123–124, 129–132, 142, 145 Mian, Atif, 204 Michigan, University of, financial survey by, 134–135 Microfinance, 203 Micropayment model, 217 Microwave technology, 53 The Million Adventure, 213–214 Minsky, Hyman, 42 Minsky moment, 42 Mississippi scheme, 36 Mitchell, Justin, 166–167 Momentum Ignition, 57 Monaco, modeling risk of earthquake in, 227 Money, history of, 4–5 Money illusion, 73–74 Money laundering, 192 Money-market funds, 43, 44 Monkeys, Yale University study of loss aversion with, 136 Montier, James, 156–157 Moody, John, 24 Moody’s, 24, 235 Moore’s law, 114 Morgan Stanley, 188 Mortgage-backed securities, 49, 233 Mortgage credit by ZIP code, study of, 204 Mortgage debt, role of in 2007–2008 crisis, 69–70 Mortgage products, unsound, 36–37 Mortgage securitization, 47 Multisystemic therapy, 96 Munnell, Alicia, 129 Naked credit-default swaps, 143 Nature Biotechnology, on drug-development megafunds, 118 “Neglected Risks, Financial Innovation and Financial Fragility” (Gennaioli, Shleifer, and Vishny), 42 Network effects, 181 New York, skyscraper craze in, 74–75 New York City, prisoner-rehabilitation program in, 108 New York Stock Exchange (NYSE), 31, 52, 53, 61, 64 New York Times, Merrill Lynch ad in, 28 Noncorrelated assets, 122 Nonprofits, growth of in United States, 105–106 Northern Rock, x NYMEX, 60 NYSE Euronext, 52 NYSE (New York Stock Exchange), 31, 52, 53, 61, 64 OECD (Organization for Economic Co-operation and Development), 128, 147 Oldfield, Sean, 67–68, 80–84 OnDeck, 216–218 One Service, 94–95, 105, 112 Operating expense ratio, 188–189 Options, 15, 124 Order-to-trade ratios, 63 Oregon, interest in income-share agreements, 172, 176 Organization for Economic Co-operation and Development (OECD), 128, 147 Overtrading, 24 Packard, Norman, 60 Pandit, Vikram, 184 Park, Sun Young, 233 Partnership mortgage, 81 Pasion, 11 Pave, 166–168, 173, 175, 182 Payday lending Consumer Financial Protection Bureau, survey on, 200 information on applicants, acquisition of, 202 underwriting of, 201 PayPal, 219 Peak child, 127 Peak risk, 228 Peer-to-peer lending advantages of, 187–189 auction system, 195 big investors in, 183 borrowers, assessment of, 197 in Britain, 181 commercial mortgages, 181 CommonBond, 182, 184, 197 consumer credit, 181 diversification, 196 explained, 180 Funding Circle, 181–182, 189, 197 investors in, 195 Lending Club, 179–180, 182–184, 187, 189, 194–195, 197 network effects, 181 ordinary savers and, 184 Prosper, 181, 187, 195 RateSetter, 181, 187, 196 Relendex, 181 risk management, 195–197 securitization, 183–184, 196 Peer-to-peer lending (continued) small business loans, 181 SoFi, 184 student loans, 182 Zopa, 181, 187, 188, 195 Pensions, cost of, 125–126 Perry, Rick, 142–143 Peterborough, England, social-impact bond pilot in, 90–92, 94–95, 104–105, 112 Petri, Tom, 172 Pharmaceuticals, decline of investment in, 114–115 Piracy Reporting Centre, International Maritime Bureau, 151 Polese, Kim, 210 Poor, Henry Varnum, 24 “Portfolio Selection” (Markowitz), 118 Prediction Company, 60–61 Preferred shares, 25 Prepaid cards, 203 Present value of cash flows, 19 Prime borrowers, 197 Prince, Chuck, 50–51, 62 Principal-agent problem, 8 Prisoner rehabilitation programs, 90–91, 94–95, 98, 108, 112 Private-equity firms, 69, 85, 91, 105, 107 Projection bias, 72–73 Property banking crises and, xiv, 69 banking mistakes involving, 75–80 behavioral biases and, 72–75 dangerous characteristics of, 70–72 fresh thinking, need for, xvii, 80 investors’ systematic errors in, 74–75 perception of as safe investment, 76, 80 Prosper, 181, 187, 195 Provisioning funds, 187 Put options, 9, 82 Quants, 19, 63, 113 QuickBooks, 218 Quote stuffing, 57 Raffray, André-François, 144 Railways, affect of on finance, 23–25 Randomized control trials (RCTs), 101 Raphoen, Christoffel, 15–16 Raphoen, Jan, 15–16 RateSetter, 181, 187, 196 RCTs (randomized control trials), 101 Ready for Zero, 210–211 Rectangularization, 125, 126 figure 2 Regulation NMS, 61 Reinhart, Carmen, 35 Reinsurance, 224 Relendex, 181 Rentes viagères, 20 Repurchase “repo” transactions, 15, 185 Research-backed obligations, 119 Reserve Primary Fund, 44 Retirement, funding for anchoring effect, 137–138 annuities, 139 auto-enrollment in pension schemes, 135 auto-escalation, 135–136 conventional funding, 127–128 decumulation, 138–139 government reaction to increased longevity, 128–129 home equity, 139–140 life expectancy, projections of, 124–127, 126 figure 2 life insurance policies, cash-surrender value of, 142 personal retirement savings, 128–129, 132–133 replacement rate, 125 reverse mortgage, 140–142 savings cues, experiment with, 137 SmartNest, 129–131 Reverse mortgages, 140–142 Risk-adjusted returns, 118 Risk appetite, 116 Risk assessment, 24, 45, 77–78, 208 Risk aversion, 116, 215 Risk-based capital, 77 Risk-based pricing model, 176 Risk management, 55, 117–118, 123, 195–197 Risk Management Solutions, 222 Risk sharing, 8, 82 Risk-transfer instrument, 226 Risk weights, 77–78 Rogoff, Kenneth, 35 “The Role of Government in Education” (Friedman), 165 Roman Empire business corporation in, 7 financial crisis in, 36 forerunners of banks in, 11 maritime insurance in, 8 Rotating Savings and Credit Associations (ROSCAs), 209–210 Roulette wheel, use of in experiment on anchoring, 138 Royal Bank of Scotland, 186 Rubio, Marco, 172 Russia, mortgage market in, 67 S-curve, in diffusion of innovations, 45 Salmon, Felix, 155 Samurai bonds, 27 Satsuma Rebellion (1877), 27 Sauter, George, 58 Save to Win, 214 Savings-and-loan crisis in US (1990s), 30 Savings cues, experiment with, 137 Scared Straight social program, 101 Scholes, Myron, 31, 123–124 Science, Technology, and Industry Scoreboard of OECD, 147 Securities and Exchange Commission (SEC), 54, 56, 57, 58, 64 Securities markets, 14 Securitization, xi, 20, 37–38, 117–122, 183–184, 196, 236 Seedrs, 160–161 Sellaband, 159 Shared equity, 80–84 Shared-equity mortgage, 84 Shepard, Chris, xii–xiii Shiller, Robert, xv–xvi, 242 Shleifer, Andrei, 42, 44 Short termism, 58 SIBs.


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The End of Traffic and the Future of Transport: Second Edition by David Levinson, Kevin Krizek

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, American Society of Civil Engineers: Report Card, autonomous vehicles, barriers to entry, Bay Area Rapid Transit, big-box store, Chris Urmson, collaborative consumption, commoditize, crowdsourcing, DARPA: Urban Challenge, dematerialisation, Elon Musk, en.wikipedia.org, Google Hangouts, Induced demand, intermodal, invention of the printing press, jitney, John Markoff, labor-force participation, lifelogging, Lyft, means of production, megacity, Menlo Park, Network effects, Occam's razor, oil shock, place-making, Ray Kurzweil, rent-seeking, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, technological singularity, Tesla Model S, the built environment, Thomas Kuhn: the structure of scientific revolutions, transaction costs, transportation-network company, Uber and Lyft, Uber for X, urban renewal, women in the workforce, working-age population, Yom Kippur War, zero-sum game, Zipcar

., one rents hotel rooms and cars rather than buying condos and vehicles when on travel; it is now common to rent music, videos, and books). Previously cars, taxis, and hotel rooms were rented from companies which could achieve large economies of scale. Now it is possible to rent couches and cars and rides from individuals with excess capacity. The degree to which economies of scale trump the network effects of distributed suppliers awaits to be seen. We roll out four dimensions of sharing—cars, rides, bikes, information—that have emerging implications for transport.  Sharing Cars While living with his family in Italy, Kevin was carless; his family therefore used the town's Hertz, renting a car once per month. David did the same thing while a graduate student living in a relatively high-density Berkeley, using the neighborhood Avis once a semester.

Streets designs will need to accommodate pick-up and drop-off as a major feature, so curb space will need to be re-arranged so people know where to meet their car (and vice versa), so they don't get into the wrong white Prius. While we lose the need for parking, we might think of channelizing roads more like airports or multi-way boulevards than the monolithic pavement they are today. Street design is discussed more in a later chapter. Discussion Sharing—be it cars, bikes, boats or information—has strong network effects driven by convenience (a characteristic the time-starved seem particularly mindful of). But, macro versus micro transit discussions in the following chapter bring up matters of economies of scale versus economies of scope. There's a role for both. For example, one is more likely to use carsharing if more neighbors use it, since that makes it more likely there will be a car in front of one's house, workplace, or wherever, when it is desired.

Middle-aged US systems born in the 1970s like San Francisco's BART, DC Metro, and Atlanta's MARTA face similar issues associated with aging infrastructure, brittle labor relations, and fixed networks unable to meet changing demand patterns. The challenges facing older systems differ from those that were first launched after 1980 in the era of Light Rail. Expanding and extending is immensely easier (sclerotic New York excepted), and given network effects, more promising than starting from scratch. New and emerging systems (at least in the US) are sold on their ability to yield under-appreciated environmental and societal benefits. Where there are large volumes of people already moving in key corridors, the leap to fixed route service is inevitable. But elsewhere, the assumption is precarious because MaaS transport and micro-transit will suitably serve these markets.

The Open Organization: Igniting Passion and Performance by Jim Whitehurst

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crowdsourcing, Google Hangouts, Network effects, Silicon Valley, Skype, Snapchat

By embracing participation from contributors within and outside the walls of the organization, Red Hat has created a competitive advantage that enables it to compete against— and beat—far larger rivals. Red Hat operates in a really fast-paced environment, and the organizational structure, an open one, is the best way for it to keep pace with the flurry of changes it faces every 9 Chapter_01.indd 9 3/7/15 9:59 AM THE OPEN ORGANIZATION single day. We have harnessed the power of what economists call the “network effect” that results when you connect people and ideas. The more people you connect, the more value they create, which in turn attracts more people, and so on. Red Hat’s management system encompasses principles such as: • People join us because they want to. • Contribution is critical, but it’s not a quid pro quo. • The best ideas win regardless of who they come from. • We encourage and expect open, frank, and passionate debate. • We welcome feedback and make changes in the spirit of “release early—release often.”


pages: 552 words: 143,074

Without Copyrights: Piracy, Publishing, and the Public Domain (Modernist Literature and Culture) by Robert Spoo

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invisible hand, Network effects, New Journalism, peer-to-peer, Ronald Reagan, transaction costs

Roth was a bold pragmatist, the bad boy of magazine publishing who cynically acted within the letter of a discriminatory law and used the public domain to promote his libidinous confections of the avant-garde. He was, in a sense, U.S. copyright law luridly personified, shorn of courtesies and dedicated to a louche, bullying sort of public service. Joyce, in contrast, was the preacher of droit d’auteur, a self-righteous property scold who, even as he launched protests and lawsuits, quietly benefited from the network effects of enhanced fame and expanded markets that lawful piracies created.23 He was Roth’s inevitable adversary, the avenging fury of authors’ moral and natural entitlements. Pound was the theorist of modernism’s encounter with copyright and piracy. Unafraid to articulate the contradictions within literary property, he believed in strong authorial rights as long as they did not interfere with free trade in books and ideas.

Although American publishers continued to preserve an ideal of fairness in their dealings with foreign authors, the old paternalistic spirit had been diminished and, with it, some of the sense of professional camaraderie and joint pursuit of honorable ends. Foreign authors may have benefited in still other ways from the former lack of copyright protection in the United States. According to B. Zorina Khan, it can be argued that piracy allowed foreign authors “to reap higher total returns from the expansion of the market” and to enjoy the benefits of network effects and bundled products, such as best sellers and lecture tours.216 During the 1880s, the cheap reprinter John B. Alden told foreign authors that they should be pleased with unremunerated circulation of their books in the United States because the widespread exposure would help their sales when international copyright finally did come.217 The chief drawback to the Chace Act, however, was its manufacturing clause.

See Rainey, Institutions of Modernism. 21. Anderson to Pound, ca. 1953, EP. 22. Conan Doyle’s 1894 tour of America and Canada is discussed in Redmond, Sherlock Holmes among the Pirates, xvi, 20, 61–62. Lawful piracy enabled Dickens and other authors to provide “complementary goods and services, such as readings and lecture tours” (Khan, Democratization of Invention, 274). 23. Transatlantic authors were able to exploit “network effects as piracy increased the scale of readership and encouraged the growth of a mass market in the United States” (ibid.). 24. Roth to Dr. H. K. Croessmann, 5/5/1927, HKC. 25. Hyde, The Gift, xix. CHAPTER 1. THE AMERICAN PUBLIC DOMAIN AND THE COURTESY OF THE TRADE IN THE NINETEENTH CENTURY 1. “The Author’s Best Friend,” NYEP (9/1/1882); reprinted in PW, no. 558 (9/23/1882): 430. 2. Holt, “Competition,” AM 102 (10/1908): 522–23. 3.


pages: 515 words: 126,820

Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World by Don Tapscott, Alex Tapscott

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Airbnb, altcoin, asset-backed security, autonomous vehicles, barriers to entry, bitcoin, blockchain, Bretton Woods, business process, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, cloud computing, cognitive dissonance, commoditize, corporate governance, corporate social responsibility, creative destruction, Credit Default Swap, crowdsourcing, cryptocurrency, disintermediation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Erik Brynjolfsson, ethereum blockchain, failed state, fiat currency, financial innovation, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, future of work, Galaxy Zoo, George Gilder, glass ceiling, Google bus, Hernando de Soto, income inequality, informal economy, information asymmetry, intangible asset, interest rate swap, Internet of things, Jeff Bezos, jimmy wales, Kickstarter, knowledge worker, Kodak vs Instagram, Lean Startup, litecoin, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, microcredit, mobile money, money market fund, Network effects, new economy, Oculus Rift, off grid, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, performance metric, Peter Thiel, planetary scale, Ponzi scheme, prediction markets, price mechanism, Productivity paradox, QR code, quantitative easing, ransomware, Ray Kurzweil, renewable energy credits, rent-seeking, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, seigniorage, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, smart grid, social graph, social software, Stephen Hawking, Steve Jobs, Steve Wozniak, Stewart Brand, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, The Wisdom of Crowds, transaction costs, Turing complete, Turing test, Uber and Lyft, unbanked and underbanked, underbanked, unorthodox policies, wealth creators, X Prize, Y2K, Zipcar

“There isn’t a trusted entity that has governance over land title, and so allowing people to actually say, ‘I own this property,’ and then use that for collateral to improve them and their family situation is a fascinating use case.”52 On a technical note, Andresen called on Nielsen’s law of Internet bandwidth, where high-end user bandwidth increases by 50 percent each year, whereas the bandwidth of the masses tends to lag by two or three years. Bandwidth lags behind computer processing power, which increases by about 60 percent annually (Moore’s law). So bandwidth is the gating factor, according to Jakob Nielsen.53 Most designs—interfaces, Web sites, digital products, services, organizations, and so forth—will need to accommodate the technology of the masses to leverage network effects. So inclusion means considering the full spectrum of usage—not just the state of the science of high-end users, but the slow tech and sporadic power outages of users in remote regions of the world’s poorest countries. Implications for the Blockchain Economy: Later in the book, we tackle the issue of the prosperity paradox—how the first era of the Internet benefited many, but overall prosperity in the Western world for most people is no longer improving.

Also, because all parties are trusted, a 51 percent attack is unlikely. Nodes can be trusted to be well connected, as in most use cases they are large financial institutions. Furthermore, they are easier for regulators to monitor. However, these advantages also create weaknesses. The easier it is to change the rules, the more likely a member is to flout them. Private blockchains also prevent the network effects that enable a technology to scale rapidly. Intentionally limiting certain freedoms by creating new rules can inhibit neutrality. Finally, with no open value innovation, the technology is more likely to stagnate and become vulnerable.29 This is not to say private blockchains won’t flourish, but financial services stakeholders must still take these concerns seriously. Ripple Labs, which has gained traction within banking circles, is developing other clever ways to relieve Faust.

In the United States, 15 percent over fifteen years of age, or 37 million Americans, are unbanked.17 Financial inequality is an economic condition that can quickly morph into a social crisis.18 In 2014, the World Economic Forum, a multistakeholder organization whose members include the largest companies and most powerful governments in the world, argued that growing inequality posed the single biggest risk globally, beating out global warming, war, disease, and other calamities.19 Blockchain could be the solution. By lowering barriers to financial inclusion and enabling new models of entrepreneurship, the tonic of the market could be brought to bear on the dreams and ideas of billions of the unbanked. Prosperity Purgatory: An Exercise in Futility For centuries, banks have relied on network effects. Each successive customer, branch, product, dollar in, and dollar out increases the value of the bank’s network. However, building these networks has come at a cost. Specifically, the cost of acquiring a profit-turning customer has only increased. If a prospect’s money won’t earn its keep, the bank won’t be interested in keeping it. Thus, banks have little economic incentive to win customers in the bottom half of the pyramid.


pages: 319 words: 89,477

The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion by John Hagel Iii, John Seely Brown

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Albert Einstein, Andrew Keen, barriers to entry, Black Swan, business process, call centre, Clayton Christensen, cleantech, cloud computing, commoditize, corporate governance, creative destruction, Elon Musk, en.wikipedia.org, future of work, game design, George Gilder, intangible asset, Isaac Newton, job satisfaction, knowledge economy, knowledge worker, loose coupling, Louis Pasteur, Malcom McLean invented shipping containers, Maui Hawaii, medical residency, Network effects, old-boy network, packet switching, pattern recognition, peer-to-peer, pre–internet, profit motive, recommendation engine, Ronald Coase, shareholder value, Silicon Valley, Skype, smart transportation, software as a service, supply-chain management, The Nature of the Firm, the new new thing, too big to fail, trade liberalization, transaction costs

This is what we call the “collaboration curve”—a curve that points upward when more participants join and when the interactions between the participants increase. Collaboration curves are a reversal of the diminishing-returns dynamics of the experience curve, delivering increasing returns to performance instead. What do we mean by increasing returns? The idea of network effects provides a useful starting point. The fax machine (which is fast becoming extinct) provides the classic example of network effects in action. One fax machine is useless. It even has negative value, since it costs money to purchase and operate and generates no value. But as more and more people purchase fax machines, the value of that fax machine increases at an exponential rate. If everyone has a fax machine, it generates enormous value, because the number of fax machines it can communicate with is very high.

The results have been impressive, not only in the scale of the creation space but in the learning and performance improvements it has produced. More than 9,000 companies participate in SAP’s various partner networks globally and 1.2 million people participate in SAP’s online communities. The creation space continues to grow at a healthy pace—more than 25,000 new participants sign up each month in SAP’s online communities and the number of page views doubled between 2006 and 2007, reaching 150 million. Strong network effects appear to be in play as participants find that the value of the creation space as a whole increases with the number of participants. Interactions are also increasing with the number of participants. For example, participants contribute more than 6,000 posts per day in SAP’s online communities. More than 60,000 wikis have been created to handle specific FAQs, and more than 1,200 bloggers comment regularly on community topics.


pages: 314 words: 83,631

Tubes: A Journey to the Center of the Internet by Andrew Blum

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air freight, cable laying ship, call centre, Donald Davies, global village, Hibernia Atlantic: Project Express, if you build it, they will come, inflight wifi, invisible hand, John Markoff, Kevin Kelly, Leonard Kleinrock, Marc Andreessen, Mark Zuckerberg, Menlo Park, Mercator projection, Network effects, New Urbanism, packet switching, Ralph Waldo Emerson, RAND corporation, side project, Silicon Valley, Skype, South of Market, San Francisco, Steve Crocker, Steve Jobs, Steven Levy, urban planning, WikiLeaks, zero-sum game

The Internet is built on connections between networks agreed on with a handshake and consummated with the plugging in of a yellow fiber-optic cable. Technically the connections happening here could happen across any distance. But there’s a profound efficiency in doing it directly, in plugging my box into your box, in an exponentially repeating pattern. Walking through the PAIX is a lesson in the “network effect,” the phenomenon by which something becomes vastly more useful the more people use it—leading more people to use it. In Palo Alto, the more and larger Internet players moved into the building, the more and larger players wanted to be there, seemingly ad infinitum, up against the laws of physics—and the Palo Alto city council. All this equipment needs backup electrical generators, in case of a blackout; and generators need vast quantities of stored diesel fuel—more than any of the neighbors would prefer.

As Kris Foster, the representative from TORIX, in Toronto, offered, “If you’ve got fiber routes from New York to Chicago through Toronto, maybe you should think about stopping.” It wasn’t a bad suggestion. It might make your network more efficient, but at the least it was a way to be “multi-homed,” a salve against fragmentation. But for the most part, the gravitational pull of the biggest exchanges was powerful enough to overcome that geographic diversity. The network effect was unassailable: more networks disproportionately concentrated in fewer places. The result was a striking gap between the average-sized Internet exchanges and the behemoths. “Places like AMS-IX and LINX are a routing engineer’s paradise,” Renesys’s Cowie explained. “They are full of hundreds of organizations that are begging you, ‘Please look at my routes, study me!’” That’s irresistible for a NANOGer.

See also Tata Communications New York City data storage in, 230 Equinix in, 164 and Europe-US telephone connection, 175 fiber highways in, 163–71, 172, 265–66 fiber-optic connections to, 26 Fitzgerald story about, 3 Google headquarters in, 163–64, 172 history of Internet and, 50 hubs in, 171–80, 181 as important network meeting point, 164 and Internet as series of tubes, 5 London traffic with, 180, 202, 208 111 Eighth Avenue (New York City), 163–64, 171, 266 peering and, 128 60 Hudson Street in, 171–74, 176 structure of Internet and, 27 32 Avenue of the Americas in, 171–80 as undersea cables port, 194, 199 New York University (NYU), 50 Newby, Hunter, 174 Ninth Avenue fiber highway (New York City), 164 Nipper, Arnold, 137–38, 140–43, 144–45, 239 North American Network Operators’ Group (NANOG), 58, 66, 157 Austin meeting of, 119–23, 127, 128–35, 157 Northrop Grumman, 62, 123 NorthWestNet, 53 NSFNET, 59, 138 NTT, 125 O’Kane, Victoria, 165 One Wilshire (Los Angeles, California), 200–201 111 Eighth Avenue (New York City), 163–64, 171, 266 online videos, 119 Open Compute project (Facebook), 258 optical modules, 160 Orlowski, Frank, 133–34, 135, 145, 157 Osés, Mara Vanina, 7 Pacific Bell, 64, 84 Pacific DC Intertie, 228 Page, Larry, 69–70 PAIX, undersea cables, PAIX and, 78 Pakistan Telecom, 30 Paling, Jol, 208, 209, 210–15, 216, 267 Palo Alto, California Adelson-Troyer-Blum meeting in, 71–72, 73 See also Palo Alto Internet Exchange (PAIX) Palo Alto Internet Exchange (PAIX) Adelson and, 72, 76–77, 88 Blum visit to, 71–72, 76–85 cable management at, 81–82 carriers and, 89 DEC and, 76, 87, 88 definition of Internet exchange and, 109 diversity at, 79 Equinix and, 76–77, 87 expansion of, 78, 86–87 importance of, 78 location of, 76 “network effect” at, 80–81 openness of Internet and, 117 peering and, 122, 127, 128 problems of, 85–86 Qatar Telecom and, 139 quantity of information passing through, 82–83 and rerouting traffic, 200–201 routers at, 79–80, 82–83, 266 security at, 95 Paris, France, structure of Internet and, 27 Passaic, New Jersey, Smithson tour of, 150–51, 152, 154 Patchett, Ken, 255–56, 257, 258–59, 260–62, 267 Pedro, John, 82 “peering” de-peering and, 123–24, 151 definition of, 118–19 division of groups for, 121–22 globalization of, 125–26 Internet exchanges and, 121–22, 126, 127, 129, 130 NANOG meeting and, 118–23, 128–30, 131–32 and “open peering policy,” 127 Qatar Telecom and, 140 Tier-1 domination of, 124–25 Witteman-Orloski meeting and, 133–35 PeeringDB (website), 126 Peter Faber (cable ship), 219, 221–22 Petrie, Anne, 83 Pipex, 184, 185, 186 “point of entry,” 178, 179 POP (point of presence), 59, 78, 84 Porthcurno (Cornwall, England), 202–16, 253, 267 Portugal, 191–92, 194, 217–26, 267 Postel, Jon, 31, 45 Prineville, Oregon: Facebook data center in, 250–62, 267 privacy issues, 258 Provo, Joe, 122 Provo, Ren, 122, 123 PSI, 56, 59, 60 Qatar, 197 Qatar Telecom, 79, 139–40 Quality Life Broadband (Q-Life), 236, 237, 238, 242, 246 Quincy, Washington, data centers in, 234–35, 250 RAND Corporation, 42 Reid, Brian, 74, 75, 76 Renesys, 123, 124–25, 151 Renton, Alan, 205–6 Research in Motion (RIM), 121 Resolute (cable ship), 218 Reyes, Felix, 77, 81 Roberts, Larry, 42–43, 51 routes/routers in Ashburn, 99–100 as basic building blocks of Internet, 158 Brocade, 157–58, 159–63, 188 dead-end, 31, 32 expansion of Internet and, 55 function of, 160 Internet as self-healing and, 200 IP addresses and, 29–30 at large Internet exchanges, 111 at MAE-East, 65–66, 75–76, 80 in New York City, 164–71 at PAIX, 79–80, 82–83, 266 peering and, 124–25, 127 and rerouting traffic, 200–201 “routing table” and, 30 Traceroute program and, 31–34 trust and, 30–31 “routing table,” 30, 125 Rudin Management, 174–75, 176 Rwanda, 110 Sabey, 235 Sacca, Chris, 237–38, 239 San Jose, California: peering and, 128 SAT-3 (undersea communications cables), 191–92, 197 satellites: Internet exchanges and, 110 Saudi Arabia, 197 Schoffstall, Marty, 60 SEACOM (undersea communications cables), 192, 197 Seales, Brian, 166–71 security/secrecy for cable landing stations, 202, 203 for data centers/storage, 93, 141, 237–40, 242–43, 254, 257 at DE-CIX, 140–41 at Dutch data centers, 152 at Equinix, 93, 141 at Google data center, 242–50, 254, 257 at Internet exchanges, 113–16 at LINX, 185–86 Sensitive Compartmented Information Facilities (“skiffs”), 62 Seoul, Korea: structure of Internet and, 27 service providers: peering and, 119 SESQUINET, 53 The Shadow Factory (Bamford), 63 Shorto, Russell, 146 Siemens Brothers, 206 Sigma-7 computer, 43 Silcock, Colin, 186, 187–89 Silicon Valley belief in limitless potential of technology in, 70 connection of networks in, 67 expansion of Internet and, 50 structure of Internet and, 27 wealth in, 70 See also Palo Alto, California; specific person or corporation Singapore, 128, 139, 194, 196, 199, 201 Singapore Telecommunications, 79 SIX (Seattle, Washington), 111 60 Hudson Street (New York City), 171–74, 176, 202, 215, 266 Smallwood, Christine, 107 Smithson, Robert, 150–51, 154 South Africa, 191–93, 197, 204, 219 South Asia, 196, 200 South Park (TV show), 107–8 Spain, 113 SPAN, 52 speed.


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Social Life of Information by John Seely Brown, Paul Duguid

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AltaVista, business process, Claude Shannon: information theory, computer age, cross-subsidies, disintermediation, double entry bookkeeping, Frank Gehry, frictionless, frictionless market, future of work, George Gilder, George Santayana, global village, Howard Rheingold, informal economy, information retrieval, invisible hand, Isaac Newton, John Markoff, Just-in-time delivery, Kenneth Arrow, Kevin Kelly, knowledge economy, knowledge worker, loose coupling, Marshall McLuhan, medical malpractice, moral hazard, Network effects, new economy, Productivity paradox, Robert Metcalfe, rolodex, Ronald Coase, shareholder value, Shoshana Zuboff, Silicon Valley, Steve Jobs, Superbowl ad, Ted Nelson, telepresence, the medium is the message, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thomas Malthus, transaction costs, Turing test, Vannevar Bush, Y2K

A second problem is that, as part of the process of price competition and standardization, subjective issues such as quality and service disappear. Both service and quality, the economists Brad de Long and Michael Froomkin have argued, tend to get squeezed Page 47 out of markets when low price becomes the decisive factor. 18 From the decisive factor, low price soon becomes the only factor. Network effects will tend to marginalize merchants who try to resist. With bots, which are not well suited to weigh subjective issues such as quality and service, these will probably disappear much more quickly. In fact, though, quality and service don't simply disappear in these conditions. They can become highly problematic "externalities," not subject to the sales and purchase contract, but imposing heavy burdens after the fact.

The concentration of media ownership was the subject of a Page 257 special edition of The Nation (March 13, 1997). The picture drawn there recalled Frank Norris's famous image of the railroads as an "octopus," but, as with any list we might produce, the Nation's octopus is already well out of date. 28. Paul Krugman, quoted in Kelly, 1998. 29. The appearance of the fax provides a conventional example of network effects at work. At first, for most people, it was hardly worth owning a fax machine because so few others did. But with each new buyer, owning a fax became more useful and so more valuable. Each addition to the network meant that everyone had more people to fax to and receive faxes from. By the late 1980s, the network had grown to such a size that owning one became almost a necessity. The fax spread on the back of nonproprietary standards that allowed many different firms to compete in the fax market, as they still do.

The fax spread on the back of nonproprietary standards that allowed many different firms to compete in the fax market, as they still do. But if someone had owned those standards, the results would have been quite different. Here the obvious example is not the fax, but the video recorder and the battle between VHS and Betamax. This battle was in effect a race between the two to establish network effects. In such races, a small lead can produce a "tipping" effect, where whoever gets ahead can quickly end up taking it all. In such conditions, firms will grow, not shrink. 30. Raik-Allen, 1998. 31. Sassen, 1996, p. 38. 32. With the rise of the Internet, many people argue that information can travel straight from its producer to its consumer, without need for any intermediaries. Kelly (1997), for example, envisages music going from musicians to listeners and then leaps to gourmet coffee from producers to drinkers.


pages: 212 words: 49,544

WikiLeaks and the Age of Transparency by Micah L. Sifry

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1960s counterculture, Amazon Web Services, banking crisis, barriers to entry, Bernie Sanders, Buckminster Fuller, Chelsea Manning, citizen journalism, Climategate, crowdsourcing, Google Earth, Howard Rheingold, Internet Archive, Jacob Appelbaum, John Markoff, Julian Assange, Network effects, RAND corporation, school vouchers, Skype, social web, source of truth, Stewart Brand, web application, WikiLeaks

Google’s search engine ranks pages based on how many other pages link to them, and it learns from what links people click which pages offer the best results to a particular search phrase. Wikipedia harnesses the power-of-many by allowing anyone to add or edit any page. Picture-sharing sites like Flickr let anyone make up their own tags for content, rather than forcing people to only use categories chosen from above. In each case, network effects make these services more valuable as they gain more users. y Data is “the next Intel inside”: successful Web 2.0 companies win in their fields not only by cornering some class of data (location, product identifiers, namespaces) but by also making their data the underpinning of a whole range of additional services. For example, Amazon didn’t just build its books database on top of a proprietary tracking tool known as the ISBN number; it added new data (cover images, table of contents) and, crucially, invited its users to add their own (reviews, ratings).

But given how much our privacy is already being eroded, not just by government but also by private corporations, it’s an understandable 162 MICAH L. SIFRY concern. It is striking to see how often people react to the news about WikiLeaks by asking how they could possibly do their jobs if every confidential conversation or negotiation were required to be public. But the transparency movement isn’t aimed at exposing the doings of ordinary people to intense scrutiny, and the kind of network effects that occur around instances of information censorship generally don’t happen around spreading someone’s shopping list. As Julian Assange argued as recently as the middle of January 2011, “Transparency should be proportional to the power that one has. The more power one has, the greater the dangers generated by that power, and the more need for transparency. Conversely, the weaker one is, the more danger there is in being transparent.”42 In other words, if information is power, then what the transparency movement is trying to do is correct an asymmetric power relationship.


pages: 183 words: 49,460

Start Small, Stay Small: A Developer's Guide to Launching a Startup by Rob Walling

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8-hour work day, en.wikipedia.org, inventory management, Lean Startup, Marc Andreessen, Network effects, Paul Graham, rolodex, side project, Silicon Valley, software as a service, SpamAssassin, Superbowl ad, web application

After sending 100-200 visitors to your site, look at the numbers of “trials” or “purchases.” Assume you will convert between 2% and 5% of people who clicked “try now” or “download free trial.” Assume 40% of the people who clicked “buy now” would have completed the purchase. When Not to Use This Approach In general, this approach will not work if you are planning to build a social networking or social media site, or any other product that’s reliant on a network effect. With these types of sites you can’t test the idea until you try it out with a full-blown marketing effort. But if you’re selling a niche downloadable, mobile or web-based (SaaS) application this approach will work. The Components Screenshots – For application screen shots, you can build them yourself or pay a designer for mockups – you only need 2-3 screens and they never have to be built into HTML.

Here is a quick rundown of the potential market sizes for the largest platforms based on the most recent numbers I could track down: Facebook – over 500 million active users MySpace – over 125 million users SalesForce.com – over 1.5 million paying subscribers Pricing Structure In the consumer space, applications are free and typically earn revenue through advertising, affiliate links, or driving traffic to a specific website where users can be monetized In the enterprise space (such as SalesForce.com) applications may have an up-front or recurring cost Benefits for the Entrepreneur These platforms tend to have a high adoption rate for new plug-ins If you design your application correctly, you can achieve exponential growth using viral marketing since the social platforms tend to have a high network effect Often your audience has a single place where they can acquire applications (such as the Facebook Application Directory or Salesforce AppExchange) so there is more likelihood your application will be discovered accidentally than with an application on the open internet The space is relatively new so there is less competition than with web or desktop apps Benefits for the Customer Convenience of new features and functionality without relying on the platform providers to build them Many plug-ins are free The Downside Gold-rush mentality and dubious monetization methods means few applications ever make money Plugging functionality holes in the application of a major vendor will eventually backfire should the vendor incorporate your functionality into the main application When to Use When you want to extend an existing web or desktop application by making it easy for platform users to add your application’s capabilities When you have a product idea that’s targeted towards a demographic that resides on a particular platform Type #6 – Community Websites Though not a conventional “cash for software” arrangement, community websites such as social networks, forums, social bookmarking tools, file sharing or photo sharing sites can not only be fun projects to build, but fun to market since the press is currently enamored with this market segment.


pages: 271 words: 52,814

Blockchain: Blueprint for a New Economy by Melanie Swan

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23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, basic income, bioinformatics, bitcoin, blockchain, capital controls, cellular automata, central bank independence, clean water, cloud computing, collaborative editing, Conway's Game of Life, crowdsourcing, cryptocurrency, disintermediation, Edward Snowden, en.wikipedia.org, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, intangible asset, Internet Archive, Internet of things, Khan Academy, Kickstarter, lifelogging, litecoin, Lyft, M-Pesa, microbiome, Network effects, new economy, peer-to-peer, peer-to-peer lending, peer-to-peer model, personalized medicine, post scarcity, prediction markets, QR code, ride hailing / ride sharing, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Skype, smart cities, smart contracts, smart grid, software as a service, technological singularity, Turing complete, unbanked and underbanked, underbanked, web application, WikiLeaks

., Fitbit), smart home, smart car, and smart city. The economy that the blockchain enables is not merely the movement of money, however; it is the transfer of information and the effective allocation of resources that money has enabled in the human- and corporate-scale economy. With revolutionary potential equal to that of the Internet, blockchain technology could be deployed and adopted much more quickly than the Internet was, given the network effects of current widespread global Internet and cellular connectivity. Just as the social-mobile functionality of Paradigm 4 has become an expected feature of technology properties, with mobile apps for everything and sociality as a website property (liking, commenting, friending, forum participation), so too could the blockchain of Paradigm 5 bring the pervasive expectation of value exchange functionality.

The issues are in clear sight of developers, with different answers to the challenges posited, and avid discussion and coding of potential solutions. Insiders have different degrees of confidence as to whether and how these issues can be overcome to evolve into the next phases of blockchain industry development. Some think that the de facto standard will be the Bitcoin blockchain, as it is the incumbent, with the most widely deployed infrastructure and such network effects that it cannot help but be the standardized base. Others are building different new and separate blockchains (like Ethereum) or technology that does not use a blockchain (like Ripple). One central challenge with the underlying Bitcoin technology is scaling up from the current maximum limit of 7 transactions per second (the VISA credit card processing network routinely handles 2,000 transactions per second and can accommodate peak volumes of 10,000 transactions per second), especially if there were to be mainstream adoption of Bitcoin.178 Some of the other issues include increasing the block size, addressing blockchain bloat, countering vulnerability to 51 percent mining attacks, and implementing hard forks (changes that are not backward compatible) to the code, as summarized here:179 Throughput The Bitcoin network has a potential issue with throughput in that it is processing only one transaction per second (tps), with a theoretical current maximum of 7 tps.


pages: 385 words: 48,143

The Monk and the Riddle: The Education of a Silicon Valley Entrepreneur by Randy Komisar

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Apple's 1984 Super Bowl advert, barriers to entry, belly landing, discounted cash flows, estate planning, Jeff Bezos, Network effects, new economy, Sand Hill Road, Silicon Valley, Silicon Valley startup, Steve Jobs

Just a few messages, including a response from Frank, had dropped in since I had last checked a couple of hours earlier. TO: randy@virtual.net FROM: frank@vcfirm.com SUBJECT: Re: A Second Life Randy, Interesting. The content and community aspects are appealing--playing to the Internet's strengths. Incorporating the local services also sounds good. I can definitely see some network effect here. Makes a win-win and a more defensible referral channel. Obviously has to be fleshed out, but more intriguing. Unfortunately, it's not the Funerals.com Lenny presented. Is it yours or Lenny's? Lenny seems stuck on the casket business. Who will lead this? Frank Who will lead this? Good question. I knew Lenny's answer based on the org Page 135 chart in his plan, but Lenny had not yet demonstrated that he had the right stuff.

The more people who gravitated to the site, the more valuable it would become to others as they shared information and attracted more local providers of goods and Page 167 services. Competitors could try to duplicate this model, but once Circle-of-Life.com established itself at the center of the network, competitors would find it difficult to dislodge. This scenario is referred to as the much-coveted "network effect," an increasing return on the benefits of growing scale on the Internet with little or no marginal cost. What Lenny and Allison proposed to do required an enormous amount of work, and success was far from guaranteed. But here the risk was in the right placein the execution of the big idea. Their idea embraced fundamental life needs and would employ the proven strengths of the Net, making it hard to believe someone, somewhere, couldn't make it work.


pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

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3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, Buckminster Fuller, call centre, clean water, collaborative consumption, commoditize, conceptual framework, continuous integration, crowdsourcing, disintermediation, distributed ledger, Edward Snowden, Elon Musk, epigenetics, Erik Brynjolfsson, future of work, global value chain, Google Glasses, income inequality, Internet Archive, Internet of things, invention of the steam engine, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, life extension, Lyft, mass immigration, megacity, meta analysis, meta-analysis, more computing power than Apollo, mutually assured destruction, Narrative Science, Network effects, Nicholas Carr, personalized medicine, precariat, precision agriculture, Productivity paradox, race to the bottom, randomized controlled trial, reshoring, RFID, rising living standards, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, smart cities, smart contracts, software as a service, Stephen Hawking, Steve Jobs, Steven Levy, Stuxnet, supercomputer in your pocket, The Future of Employment, The Spirit Level, total factor productivity, transaction costs, Uber and Lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

The fourth industrial revolution forces companies to think about how offline and online worlds work together in practice. 3.2.4 New Operating Models All these different impacts require companies to rethink their operating models. Accordingly, strategic planning is being challenged by the need for companies to operate faster and with greater agility. As mentioned earlier, an important operating model enabled by the network effects of digitization is the platform. While the third industrial revolution saw the emergence of purely digital platforms, a hallmark of the fourth industrial revolution is the appearance of global platforms intimately connected to the physical world. The platform strategy is both profitable and disruptive. Research by the MIT Sloan School of Management shows that 14 out of the top 30 brands by market capitalization in 2013 were platform-oriented companies.37 Platform strategies, combined with the need to be more customer-centric and to enhance products with data, are shifting many industries from a focus on selling products to delivering services.

Many senior executives expect industry convergence to be the primary force impacting their business in the next three to five years.39 Once a customer has established a track record of trust and confidence on the platform, it becomes easy for the digital provider to offer other products and services. Fast-moving competitors provoke a disaggregation of the more traditional industry silos and value chains, and also disintermediate the existing relationship between businesses and their customers. New disruptors can rapidly scale at a much lower cost than the incumbents, generating in the process a rapid growth in their financial returns through network effects. Amazon’s evolution from a bookseller to a $100 billion a year retail conglomerate shows how customer loyalty, combined with insights on preferences and solid execution can lead to selling across multiple industries. It also demonstrates the benefits of scale. In almost all industries, digital technologies have created new, disruptive ways of combining products and services – and in the process, have dissolved the traditional boundaries between industries.


pages: 411 words: 80,925

What's Mine Is Yours: How Collaborative Consumption Is Changing the Way We Live by Rachel Botsman, Roo Rogers

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Airbnb, barriers to entry, Bernie Madoff, bike sharing scheme, Buckminster Fuller, carbon footprint, Cass Sunstein, collaborative consumption, collaborative economy, commoditize, Community Supported Agriculture, credit crunch, crowdsourcing, dematerialisation, disintermediation, en.wikipedia.org, experimental economics, George Akerlof, global village, Hugh Fearnley-Whittingstall, information retrieval, iterative process, Kevin Kelly, Kickstarter, late fees, Mark Zuckerberg, market design, Menlo Park, Network effects, new economy, new new economy, out of africa, Parkinson's law, peer-to-peer, peer-to-peer lending, peer-to-peer rental, Ponzi scheme, pre–internet, recommendation engine, RFID, Richard Stallman, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Ronald Coase, Search for Extraterrestrial Intelligence, SETI@home, Simon Kuznets, Skype, slashdot, smart grid, South of Market, San Francisco, Stewart Brand, The Nature of the Firm, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thorstein Veblen, Torches of Freedom, transaction costs, traveling salesman, ultimatum game, Victor Gruen, web of trust, women in the workforce, Zipcar

The experience is appealing as much for the “collaborative” as for the “consumption.” A single phone is useless, but the more people who own telephones, the more valuable the telephone is to each owner as the total number of people on the network increases. Similarly, the more users who participate in programs such as Landshare, Airbnb, or bike sharing, the better the system works for everyone—there is a “network effect.” Every single person who joins or uses Collaborative Consumption creates value for another person, even if this was not the intention. Trust Between Strangers The second intersection of Ostrom’s research with Collaborative Consumption is her idea that “commoners” can self-govern shared resources if they are empowered with the right tools to coordinate projects or specific needs, and the right to monitor each other.

Hundreds of thousands of early users spread the brand through discussing a new service called VoIP, whereby you could call people anywhere in the world for free on blogs, Facebook, and forums. Skype made it easy for the brand to go viral by providing users with items they could easily share, such as Skype buttons for personal Web sites. Within a couple of years, the verb “to Skype” was being used almost as often as “to Google.” The network effect was in play. Given that any Skype user can call any other Skype user, it was in the early adopters’ self-interest to get their friends and relatives to sign up to Skype, not Vonage or Go2Call or any other VoIP service. But awareness of Skype grew at a rapid rate primarily because people felt that they made a discovery of something new and valuable and immediately wanted to talk it up. The same is true of Collaborative Consumption.


pages: 224 words: 64,156

You Are Not a Gadget by Jaron Lanier

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1960s counterculture, accounting loophole / creative accounting, additive manufacturing, Albert Einstein, call centre, cloud computing, commoditize, crowdsourcing, death of newspapers, digital Maoism, Douglas Hofstadter, Extropian, follow your passion, hive mind, Internet Archive, Jaron Lanier, jimmy wales, John Conway, John von Neumann, Kevin Kelly, Long Term Capital Management, Network effects, new economy, packet switching, PageRank, pattern recognition, Ponzi scheme, Ray Kurzweil, Richard Stallman, Silicon Valley, Silicon Valley startup, slashdot, social graph, stem cell, Steve Jobs, Stewart Brand, Ted Nelson, telemarketer, telepresence, The Wisdom of Crowds, trickle-down economics, Turing test, Vernor Vinge, Whole Earth Catalog

Entrepreneurs naturally sought to create products that would inspire demand (or at least hypothetical advertising opportunities that might someday compete with Google) where there was no lack to be addressed and no need to be filled, other than greed. Google had discovered a new permanently entrenched niche enabled by the nature of digital technology. It turns out that the digital system of representing people and ads so they can be matched is like MIDI. It is an example of how digital technology can cause an explosive increase in the importance of the “network effect.” Every element in the system—every computer, every person, every bit—comes to depend on relentlessly detailed adherence to a common standard, a common point of exchange. Unlike MIDI, Google’s secret software standard is hidden in its computer cloud* instead of being replicated in your pocket. Anyone who wants to place ads must use it, or be out in the cold, relegated to a tiny, irrelevant subculture, just as digital musicians must use MIDI in order to work together in the digital realm.

You never know where the cloud resides physically. Google, Microsoft, IBM, and various government agencies are some of the proprietors of computing clouds. * Facebook does have advertising, and is surely contemplating a variety of other commercial plays, but so far has earned only a trickle of income, and no profits. The same is true for most of the other web 2.0 businesses. Because of the enhanced network effect of all things digital, it’s tough for any new player to become profitable in advertising, since Google has already seized a key digital niche (its ad exchange). In the same way, it would be extraordinarily hard to start a competitor to eBay or Craigslist. Digital network architectures naturally incubate monopolies. That is precisely why the idea of the noosphere, or a collective brain formed by the sum of all the people connected on the internet, has to be resisted with more force than it is promoted


pages: 251 words: 76,128

Borrow: The American Way of Debt by Louis Hyman

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asset-backed security, barriers to entry, big-box store, cashless society, collateralized debt obligation, credit crunch, deindustrialization, deskilling, diversified portfolio, financial innovation, Ford paid five dollars a day, Home mortgage interest deduction, housing crisis, income inequality, market bubble, McMansion, mortgage debt, mortgage tax deduction, Network effects, new economy, Paul Samuelson, Plutocrats, plutocrats, price stability, Ronald Reagan, statistical model, technology bubble, transaction costs, women in the workforce

In Chicago, the aggressive move of some banks into the credit card field had particularly calamitous results, highlighting the challenges facing lenders in the 1960s. In Chicago, as in many regions, a group of banks banded together in 1966 to form the Midwest Bank Card System.18 Though each bank enrolled its own clients, a card issued by Bank A could be used at a retailer affiliated with Bank B. In that way, a network effect could be created similar to that enjoyed by much larger banks such as BofA. Customers and retailers alike would find Bank A’s and Bank B’s cards more convenient than either one of them independently. And when a bank got a customer in 1966, it would probably keep that customer even after BankAmericard came to town. Balances could not be rolled over from card to card as easily as they are today, and as long as you had a balance you were hooked.

Even then, the second largest bank in the country behind Bank of America—Chase Manhattan—still did not offer a credit card.42 In 1968, less than 10 percent of banks offered credit cards.43 The consolidation of a national system took a few years, but the advantages of joining a network became apparent, even if it meant sending along some of the profits to Bank of America. A few local programs remained in New York City and in certain states such as Georgia and Michigan, but by the early 1970s, most banks were aligned with either BankAmericard or Master Charge,44 which dramatically increased the usefulness of credit cards. Credit cards took off because of those new networks.45 The network effect is evident in the proliferation of card programs from 1967 to 1968 as BankAmericard and Master Charge spread. In September 1967, 197 banks offered credit cards, and by June 1968—just nine months later—that number had more than doubled, to 416.46 Yet despite the greater availability of bank cards, most retail borrowing (93 percent) remained through the store and not the bank.47 Master Charge turned out to be good for BankAmericard, which was threatening to look like a monopoly.


pages: 532 words: 139,706

Googled: The End of the World as We Know It by Ken Auletta

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23andMe, AltaVista, Anne Wojcicki, Apple's 1984 Super Bowl advert, bioinformatics, Burning Man, carbon footprint, citizen journalism, Clayton Christensen, cloud computing, Colonization of Mars, commoditize, corporate social responsibility, creative destruction, death of newspapers, disintermediation, don't be evil, facts on the ground, Firefox, Frank Gehry, Google Earth, hypertext link, Innovator's Dilemma, Internet Archive, invention of the telephone, Jeff Bezos, jimmy wales, John Markoff, Kevin Kelly, knowledge worker, Long Term Capital Management, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Network effects, new economy, Nicholas Carr, PageRank, Paul Buchheit, Peter Thiel, Ralph Waldo Emerson, Richard Feynman, Richard Feynman, Sand Hill Road, Saturday Night Live, semantic web, sharing economy, Silicon Valley, Skype, slashdot, social graph, spectrum auction, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, strikebreaker, telemarketer, the scientific method, The Wisdom of Crowds, Upton Sinclair, X Prize, yield management, zero-sum game

Microsoft’s power was its ability to leverage its potent operating system to control the various applications that use the operating system. So Microsoft offered a free browser to knock out the Netscape browser and attacked Java software that might “facilitate competition with the underlying operating system.” Google’s power flows from a different source, he said. “They have produced this amazing machine for building data, and that data has its own ‘network effect’”—the more people who use it, the more data generated, the more advertisers flock to it. “Everything sits on top of that layer, starting with search. Every time you search, you give Google some value because you pick a certain result. And every time you pick a result, Google learns something from that. So each time you do a search, you’re adding value to Google’s data base. The data base becomes so rich that the advertising model that sits on top of it can out-compete other advertising models because it has better data....

Because it is free, Google will be difficult to assail. No one can predict with certainty where Google and the digital wave is heading, when it will crest, or who it will flatten. If the public or its representatives come to believe Google plays favorites, aims to monopolize knowledge or its customers, invades their privacy, or arrogantly succumbs, in the words of Clayton Christensen, “to the falsehood that you can grow and grow because of network effects,” then it will be more vulnerable. If Google maintains its deposit of public trust—continuing to put users first—and if it stays humble and moves with the swiftness of a fox, it will be difficult to catch. Other companies have profoundly disrupted the business landscape. Think of the Ford automobile or the Intel chip. We can, however, be certain of this: Nowhere in the three billion daily searches it conducts, the two dozen or so tetabits (about twenty-four quadrillion bits) of data it stores, the more than twenty million books it plans to digitize, will we find another company that has swept so swiftly across the media horizon.

See Data collection by Google; Privacy CPC (cost per click) development of DoubleClick effectiveness of ads, measuring future pressures in Gmail Gmail problem Google Ad Planner Google as Big Brother view Google Audio Ads Google News as Google option Google policy Google Print Ads Google TV Ads and Google values Google viewpoint on importance to Americans initial resistance to method, advantages of on mobile devices network effect versus old media ads. See Advertising, traditional; Old media and Patriot Act privacy versus user trust revenues sales force syndication of ads and YouTube Google Analytics, function of Google Audio Ads Google Books Google Book Search Google Checkout Google Content Network Google Desktop Google Desktop Search Google Docs Google Earth Google employees dog policy engineering staff.


pages: 457 words: 128,838

The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order by Paul Vigna, Michael J. Casey

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3D printing, Airbnb, altcoin, bank run, banking crisis, bitcoin, blockchain, Bretton Woods, California gold rush, capital controls, carbon footprint, clean water, collaborative economy, collapse of Lehman Brothers, Columbine, Credit Default Swap, cryptocurrency, David Graeber, disintermediation, Edward Snowden, Elon Musk, ethereum blockchain, fiat currency, financial innovation, Firefox, Flash crash, Fractional reserve banking, hacker house, Hernando de Soto, high net worth, informal economy, intangible asset, Internet of things, inventory management, Julian Assange, Kickstarter, Kuwabatake Sanjuro: assassination market, litecoin, Long Term Capital Management, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, McMansion, means of production, Menlo Park, mobile money, money: store of value / unit of account / medium of exchange, Network effects, new economy, new new economy, Nixon shock, offshore financial centre, payday loans, Pearl River Delta, peer-to-peer, peer-to-peer lending, pets.com, Ponzi scheme, prediction markets, price stability, profit motive, QR code, RAND corporation, regulatory arbitrage, rent-seeking, reserve currency, Robert Shiller, Robert Shiller, Satoshi Nakamoto, seigniorage, shareholder value, sharing economy, short selling, Silicon Valley, Silicon Valley startup, Skype, smart contracts, special drawing rights, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, supply-chain management, Ted Nelson, The Great Moderation, the market place, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, tulip mania, Turing complete, Tyler Cowen: Great Stagnation, Uber and Lyft, underbanked, WikiLeaks, Y Combinator, Y2K, zero-sum game, Zimmermann PGP

But it also means that some transactions have longer wait times before they are fully confirmed and installed in the blockchain. * * * Anyone can become a miner and is free to use whatever computing equipment he or she can come up with to participate. Nakamoto knew that as more miners entered the hunt, the incentive would be strong to ramp up computing power to beat the competition. So to keep everything in sync, he programmed the bitcoin algorithm to calculate the so-called hashrate of the overall network—effectively, the total computational capacity per second—and automatically adjust the mathematical puzzle’s difficulty so that blocks would become harder to seal off. That way, the bitcoin reward program could more or less stick to an ingrained ten-minute-per-block schedule. The ten-minute gap is somewhat arbitrary, but by choosing an interval and programming the software to stick to that fixed schedule, he could arrange the currency-issuance schedule to be consistent over a 130-year period.

As a group of businesses in one region begins adopting the currency, it will become more appealing to others with whom they do business. Once such a network of intertwined businesses builds up, no one wants to be excluded from it. Or so the theory goes. “Just as American retail collapsed into Walmart, who knows how much can collapse into us? And I don’t mean Overstock. I mean bitcoin,” Byrne said. “You start getting network effects. You are incentivizing everyone—it’s like we have the first fax machine but nobody else has a fax machine, so it doesn’t do you any good. But you start adding other nodes and making incentives to add nodes and eventually get a critical mass. Now people aren’t just faxing us, they are faxing each other.” * * * “I have no compassion for these women in Afghanistan,” Francesco Rulli says from behind the bar at which he entertains visitors to his company’s whitewashed loft in a downtown Manhattan building.

Imagine how much wider the use of cryptocurrency would be if a major retailer such as Walmart switched to a blockchain-based payment network in order to cut tens of billions of dollars in transaction costs off the $350 billion it sends annually to tens of thousands of suppliers worldwide. What if, further, such a player really got religion, as Overstock CEO Patrick Byrne did with his plan to incentivize suppliers to accept bitcoin? That way it would foment changes that go far beyond its direct payment relationships. With networking effects like that in mind, it’s not hard to imagine a Walmart-like player feeding the spread of adoption until a critical mass of self-reinforcement is reached. (For the record, we have no idea of Walmart’s current thinking on cryptocurrency.) The major catalyst for adoption might be a government seeking to reduce procurement costs or bring greater transparency to governance. We already know that Canada explored the idea of a digital Canadian dollar with its MintChip, and Ecuador is planning to introduce a centrally issued digital currency.


pages: 380 words: 118,675

The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone

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3D printing, airport security, AltaVista, Amazon Mechanical Turk, Amazon Web Services, bank run, Bernie Madoff, big-box store, Black Swan, book scanning, Brewster Kahle, call centre, centre right, Chuck Templeton: OpenTable, Clayton Christensen, cloud computing, collapse of Lehman Brothers, crowdsourcing, cuban missile crisis, Danny Hillis, Douglas Hofstadter, Elon Musk, facts on the ground, game design, housing crisis, invention of movable type, inventory management, James Dyson, Jeff Bezos, John Markoff, Kevin Kelly, Kodak vs Instagram, late fees, loose coupling, low skilled workers, Maui Hawaii, Menlo Park, Network effects, new economy, optical character recognition, pets.com, Ponzi scheme, quantitative hedge fund, recommendation engine, Renaissance Technologies, RFID, Rodney Brooks, search inside the book, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Skype, statistical arbitrage, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Thomas L Friedman, Tony Hsieh, Whole Earth Catalog, why are manhole covers round?, zero-sum game

Customers could reach Amazon Auctions only by clicking on a separate tab on the Amazon home page, and it looked like a dingy leftovers bin to people who were accustomed to using Amazon to shop in the traditional way, with predictable prices for each item. The high-tech community was getting a lesson in the dynamics of network effects—products or services become increasingly valuable as more people use them. In online marketplaces, the network effect was pervasive; sellers stuck around for access to a critical mass of buyers, and vice versa. In the auctions category, eBay already had an insurmountable advantage. Amazon’s executives remember this significant failure as painful but strangely uplifting. “Those days in the nineties were the most intense, fun time I ever had at the company,” Blackburn says. “We had an insanely talented group of people trying to figure out how to launch a superior auctions site. In the end the network effect mattered. You could say we were naïve, but we built a great product.” Bezos didn’t take the defeat personally.


pages: 396 words: 117,149

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos

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3D printing, Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is the new oil, double helix, Douglas Hofstadter, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, global village, Google Glasses, Gödel, Escher, Bach, information retrieval, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, lone genius, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, Richard Feynman, Second Machine Age, self-driving car, Silicon Valley, speech recognition, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, zero-sum game

The success or failure of a company now depends on how much the learners like its products, and the success of a whole economy—whether everyone gets the best products for their needs at the best price—depends on how good the learners are. The best way for a company to ensure that learners like its products is to run them itself. Whoever has the best algorithms and the most data wins. A new type of network effect takes hold: whoever has the most customers accumulates the most data, learns the best models, wins the most new customers, and so on in a virtuous circle (or a vicious one, if you’re the competition). Switching from Google to Bing may be easier than switching from Windows to Mac, but in practice you don’t because Google, with its head start and larger market share, knows better what you want, even if Bing’s technology is just as good.

“Spreadsheet data manipulation using examples,”* by Sumit Gulwani, William Harris, and Rishabh Singh (Communications of the ACM, 2012), is an example of how computers can program themselves by observing users. Competing on Analytics, by Tom Davenport and Jeanne Harris (HBS Press, 2007), is an introduction to the use of predictive analytics in business. In the Plex, by Steven Levy (Simon & Schuster, 2011), describes at a high level how Google’s technology works. Carl Shapiro and Hal Varian explain the network effect in Information Rules (HBS Press, 1999). Chris Anderson does the same for the long-tail phenomenon in The Long Tail (Hyperion, 2006). The transformation of science by data-intensive computing is surveyed in The Fourth Paradigm, edited by Tony Hey, Stewart Tansley, and Kristin Tolle (Microsoft Research, 2009). “Machine science,” by James Evans and Andrey Rzhetsky (Science, 2010), discusses some of the different ways computers can make scientific discoveries.

See Markov logic networks (MLNs) Moby Dick (Melville), 72 Molecular biology, data and, 14 Moneyball (Lewis), 39 Mooney, Ray, 76 Moore’s law, 287 Moravec, Hans, 288 Muggleton, Steve, 80 Multilayer perceptron, 108–111 autoencoder, 116–118 Bayesian, 170 driving a car and, 113 Master Algorithm and, 244 NETtalk system, 112 reinforcement learning and, 222 support vector machines and, 195 Music composition, case-based reasoning and, 199 Music Genome Project, 171 Mutation, 124, 134–135, 241, 252 Naïve Bayes classifier, 151–153, 171, 304 Bayesian networks and, 158–159 clustering and, 209 Master Algorithm and, 245 medical diagnosis and, 23 relational learning and, 228–229 spam filters and, 23–24 text classification and, 195–196 Narrative Science, 276 National Security Agency (NSA), 19–20, 232 Natural selection, 28–29, 30, 52 as algorithm, 123–128 Nature Bayesians and, 141 evolutionaries and, 137–142 symbolists and, 141 Nature (journal), 26 Nature vs. nurture debate, machine learning and, 29, 137–139 Neal, Radford, 170 Nearest-neighbor algorithms, 24, 178–186, 202, 306–307 dimensionality and, 186–190 Negative examples, 67 Netflix, 12–13, 183–184, 237, 266 Netflix Prize, 238, 292 Netscape, 9 NETtalk system, 112 Network effect, 12, 299 Neumann, John von, 72, 123 Neural learning, fitness and, 138–139 Neural networks, 99, 100, 112–114, 122, 204 convolutional, 117–118, 302–303 Master Algorithm and, 240, 244, 245 reinforcement learning and, 222 spin glasses and, 102–103 Neural network structure, Baldwin effect and, 139 Neurons action potentials and, 95–96, 104–105 Hebb’s rule and, 93–94 McCulloch-Pitts model of, 96–97 processing in brain and, 94–95 See also Perceptron Neuroscience, Master Algorithm and, 26–28 Newell, Allen, 224–226, 302 Newhouse, Neil, 17 Newman, Mark, 160 Newton, Isaac, 293 attribute selection, 189 laws of, 4, 14, 15, 46, 235 rules of induction, 65–66, 81, 82 Newtonian determinism, Laplace and, 145 Newton phase of science, 39–400 New York Times (newspaper), 115, 117 Ng, Andrew, 117, 297 Nietzche, Friedrich, 178 NIPS.


pages: 494 words: 142,285

The Future of Ideas: The Fate of the Commons in a Connected World by Lawrence Lessig

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AltaVista, Andy Kessler, barriers to entry, business process, Cass Sunstein, commoditize, computer age, creative destruction, dark matter, disintermediation, Donald Davies, Erik Brynjolfsson, George Gilder, Hacker Ethic, Hedy Lamarr / George Antheil, Howard Rheingold, Hush-A-Phone, HyperCard, hypertext link, Innovator's Dilemma, invention of hypertext, inventory management, invisible hand, Jean Tirole, Jeff Bezos, Joseph Schumpeter, Kenneth Arrow, Larry Wall, Leonard Kleinrock, linked data, Marc Andreessen, Menlo Park, Network effects, new economy, packet switching, peer-to-peer, peer-to-peer model, price mechanism, profit maximization, RAND corporation, rent control, rent-seeking, RFC: Request For Comment, Richard Stallman, Richard Thaler, Robert Bork, Ronald Coase, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, smart grid, software patent, spectrum auction, Steve Crocker, Steven Levy, Stewart Brand, Ted Nelson, Telecommunications Act of 1996, The Chicago School, transaction costs, zero-sum game

I am not claiming IPSec would necessarily be consistent with end-to-end, but simply that it provides a consistent protocol that could be implemented consistent with end-to-end. 53 Garrett Hardin, “The Tragedy of the Commons,” Science 162 (1968): 1243, 1244 (emphasis added). 54 National Research Council, 24-25. 55 As Faulhaber put it, “[T]he third view is that, as Adam Smith pointed out, producers are always conspiring about how to fleece the unsuspecting consuming public; it is only the competitive market that keeps their avarice in check. But producers will always search for ways to escape competition, through marketing, customer lock-in, predatory pricing, network effects, etc. AND . . . technological innovation is just a part of this strategic quest for greater profits, perhaps at the consumers' expense.” “Faulhaber Comments at E-2-E Workshop,” http://www.law.stanford.edu/e2e/papers.html. François Bar has made a similar point: “If the Internet could reduce friction, the same technology can also be deployed to create more of it.” François Bar, “The Construction of Marketplace Architecture,” 5. 56 Charles Platt, “The Future Will Be Fast but Not Free,” Wired, May 2001, available at http://www.wired.com/wired/archive/9.05/broadband_pr.html (emphasis added).

., 26. 67 Ibid. 68 A similar skepticism has been raised about strong property rights where network externalities are strong. See Pamela Samuelson et al., “Manifesto Concerning the Legal Protection of Computer Programs,” Columbia Law Review 94 (1994): 2308, 2375, citing Joseph Farrell, “Standardization and Intellectual Property,” Jurimetrics Journal 30 (1989): 35, 36-38, 45-46 (discussing network effects). 69 See, e.g., Josh Lerner, “150 Years of Patent Protection” (NBER Working Paper No. 7477, January 2000) (examines 177 policy changes in the strength of protection across sixty countries, over a 150-year period, and concludes that strengthening patent protection had few positive effects on patent applications in the country making the policy change); Mariko Sakakibara and Lee Branstetter, “Do Stronger Patents Induce More Innovation?

Thus, while such a benefit is possible, that it is possible in the current regime has not, in my view, been shown. 103 Telephone interview with Bob Young, November 14, 2000. See also Kahin, 3-4 (“At the level of individual patents, patents may benefit small firms more than large firms because small-firm options for appropriating returns from innovation are fewer. For example, small firms may be less able to exploit first-mover advantages. At the portfolio level, large firms with large portfolios benefit disproportionately from network effects and economies of scale and scope. This includes their ability to manage transaction costs, which is the subject of the third perspective that I will explore at greater length.”); Kahin, 4 (“Small firms [with some exceptions] are generally disadvantaged because they lack in-house patent counsel and their business focus can be easily distracted by litigation or even claims of infringement.”). 104 “In the short run, individual patents work to [the benefit of small firms], while in the long run and in the aggregate, patents favor large firms.


pages: 390 words: 114,538

Digital Wars: Apple, Google, Microsoft and the Battle for the Internet by Charles Arthur

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activist fund / activist shareholder / activist investor, AltaVista, Build a better mousetrap, Burning Man, cloud computing, commoditize, credit crunch, crowdsourcing, disintermediation, don't be evil, en.wikipedia.org, Firefox, gravity well, Jeff Bezos, John Gruber, Mark Zuckerberg, Menlo Park, Network effects, PageRank, pre–internet, Robert X Cringely, Silicon Valley, Silicon Valley startup, skunkworks, Skype, slashdot, Snapchat, software patent, speech recognition, stealth mode startup, Steve Ballmer, Steve Jobs, the new new thing, the scientific method, Tim Cook: Apple, turn-by-turn navigation, upwardly mobile

Born in April 1955, he was very experienced, the former chief executive of Novell – a company whose glory days were behind it and which was struggling to compete with Microsoft. Page and Brin also liked him because he had been to the Burning Man festival, a meeting place for geeks. The venture capitalists liked him because he looked like, as Schmidt put it, ‘adult supervision’. Boom With a business model in place, Google could expand aggressively. It started to benefit too from the network effect among advertisers. If you advertised on Google and you got business from it, then you’d probably point people back towards it. By automating the process of bidding for an advertisement based on any search term you liked, Google also made it possible for the tiniest business to get seen by the world in a way that previous search engines hadn’t. And because the overwhelming majority of businesses are small, and because Google’s advertising business could scale endlessly – since it was not relying on its own staff to input the advertisements or the contents of the web – it could grow really fast.

Being in the Xbox division, I knew all about that because those guys [from Windows and Office] would say ‘What are you [people in the division housing Xbox] doing for us? You’re just eating up all our profit and you’re spending all our money, and what for?’32 What for indeed? By mid-2005, the online advertising market was worth $5 billion and growing at 40 per cent. And the benefits were beginning to accrue to Google through a network effect: the more popular a marketplace destination is, the more it will grow compared to others because traders want to be at a place that maximizes their opportunity to trade. And Microsoft couldn’t beat the auction model. Google’s moat was repelling invaders. But Microsoft could still use its dominance on the desktop and browsers to push its new web search to prominence, couldn’t it? To those outside the business, the obvious threat was that future versions of its dominant Internet Explorer browser would make Microsoft’s search engine the default.

The counterpoint is [Nokia’s] Symbian with 250 million users – but they’re pulling the rug. It wasn’t sticky enough. Symbian was unable to form a protective moat – that combination of hardware accessories and software ecosystem – to hold its users close and prevent defection to other platforms. In addition, of course, Nokia didn’t react quickly enough, as Dediu had forecast. ‘You have to quantify the network effects [of being on a platform],’ he continues. ‘Apple’s iOS is sticky.’ And that’s where the simplistic ‘winning’ or ‘losing’ idea breaks down. ‘Each platform has a different position. I think Microsoft will buy its way in – $2 billion will buy a way in,’ Dediu says. (That’s the minimum amount Microsoft spent on its partnership with Nokia; the true cost is likely to be very much higher.) The position exists for Android to rush ahead and plant a flag in all new markets, and then Apple can skim the best customers.


pages: 327 words: 103,336

Everything Is Obvious: *Once You Know the Answer by Duncan J. Watts

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active measures, affirmative action, Albert Einstein, Amazon Mechanical Turk, Black Swan, butterfly effect, Carmen Reinhart, Cass Sunstein, clockwork universe, cognitive dissonance, collapse of Lehman Brothers, complexity theory, correlation does not imply causation, crowdsourcing, death of newspapers, discovery of DNA, East Village, easy for humans, difficult for computers, edge city, en.wikipedia.org, Erik Brynjolfsson, framing effect, Geoffrey West, Santa Fe Institute, George Santayana, happiness index / gross national happiness, high batting average, hindsight bias, illegal immigration, industrial cluster, interest rate swap, invention of the printing press, invention of the telescope, invisible hand, Isaac Newton, Jane Jacobs, Jeff Bezos, Joseph Schumpeter, Kenneth Rogoff, lake wobegon effect, Long Term Capital Management, loss aversion, medical malpractice, meta analysis, meta-analysis, Milgram experiment, natural language processing, Netflix Prize, Network effects, oil shock, packet switching, pattern recognition, performance metric, phenotype, Pierre-Simon Laplace, planetary scale, prediction markets, pre–internet, RAND corporation, random walk, RFID, school choice, Silicon Valley, statistical model, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, The Death and Life of Great American Cities, the scientific method, The Wisdom of Crowds, too big to fail, Toyota Production System, ultimatum game, urban planning, Vincenzo Peruggia: Mona Lisa, Watson beat the top human players on Jeopardy!, X Prize

And if it had come to pass, the superior picture quality of Betamax might well have made up for the extra cost, while the shorter taping time may have been irrelevant.16 Nor was it the case that Matsushita had any better inkling than Sony how fast the video-rental market would take off—indeed, an earlier experiment in movie rentals by the Palo Alto–based firm CTI had failed dramatically. Regardless, by the time it had become clear that home movie viewing, not taping TV shows, would be the killer app of the VCR, it was too late. Sony did their best to correct course, and in fact very quickly produced a longer-playing BII version, eliminating the initial advantage held by Matsushita. But it was all to no avail. Once VHS got a sufficient market lead, the resulting network effects were impossible to overcome. Sony’s failure, in other words, was not really the strategic blunder it is often made out to be, resulting instead from a shift in consumer demand that happened far more rapidly than anyone in the industry had anticipated. Shortly after their debacle with Betamax, Sony made another big strategic bet on recording technology—this time with their MiniDisc players.

Persistence and Periodicity in a Dynamic Proximity Network in DIMACS Workshop on Compututional Methods for Dynamic Interaction Networks. Clifford, Stephanie. 2009. “Put Ad on Web. Count Clicks. Revise.” New York Times, May 30. ———. 2010. “We’ll Make You a Star (if the Web Agrees).” New York Times, June 4. Cohen-Cole, Ethan, and Jason M. Fletcher. 2008a. “Are All Health Outcomes ‘Contagious’? Detecting Implausible Social Network Effects in Acne, Height, and Headaches.” Available at SSRN: ssrn.count/abstract=133901. ———. 2008b. “Is Obesity Contagious? Social Networks vs. Environmental Factors in the Obesity Epidemic.” Journal of Health Economics 27 (5):1382–7. Cohn, Jonathan. 2007. Sick: The Untold Story of America’s Health Care Crisis—and the People Who Pay the Price. New York: HarperCollins. Coleman, James S. 1986. Individual Interests and Collective Action.


pages: 299 words: 91,839

What Would Google Do? by Jeff Jarvis

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23andMe, Amazon Mechanical Turk, Amazon Web Services, Anne Wojcicki, barriers to entry, Berlin Wall, business process, call centre, cashless society, citizen journalism, clean water, commoditize, connected car, credit crunch, crowdsourcing, death of newspapers, disintermediation, diversified portfolio, don't be evil, fear of failure, Firefox, future of journalism, Google Earth, Googley, Howard Rheingold, informal economy, inventory management, Jeff Bezos, jimmy wales, Kevin Kelly, Mark Zuckerberg, moral hazard, Network effects, new economy, Nicholas Carr, old-boy network, PageRank, peer-to-peer lending, post scarcity, prediction markets, pre–internet, Ronald Coase, search inside the book, Silicon Valley, Skype, social graph, social software, social web, spectrum auction, speech recognition, Steve Jobs, the medium is the message, The Nature of the Firm, the payments system, The Wisdom of Crowds, transaction costs, web of trust, Y Combinator, Zipcar

Glam sells ads on those sites and shares revenue with them. Glam also replicates the best of the network’s content at Glam.com, selling ads there—at a higher rate—and sharing that revenue, too. Glam gives its member sites technology and content to make them better. It gives them traffic and they give each other traffic, pointing to sister sites in the network. The more traffic each site gets, the more traffic it has to send around—that is the network effect, another virtuous circle. Glam also gives its sites prestige, for unlike Google, it is selective. Glam’s editors find sites they like and highlight the best of the content, making Glam a curated content and ad network. That allows Glam to tell skittish advertisers that their messages will appear in a quality, safe environment, and advertisers will pay more for that. There’s another big advantage to Glam’s network approach: cost.

If a Googley restaurant would tell me how many diners ordered the crab cakes, a Googley doctor should tell me how often she has treated afib. I would also be impressed if the doctor treating me had written about the condition online. I’d be doubly impressed if I saw other doctors linking to her. The changes in medicine we’ve touched on all relate to information: opening it up, sharing it, organizing it, analyzing it, bringing the network effect to the industry and our health. That is Google’s specialty. Google Mutual Insurance: The business of cooperation As I was researching this book, I wrote on my blog that I had come up against a few industries I thought were immune from reform through Googlification. Insurance topped my list (we’ll get to the others shortly). Insurance is built on getting us to take a sucker bet—a bet even we want to lose.


pages: 315 words: 85,791

Technical Blogging: Turn Your Expertise Into a Remarkable Online Presence by Antonio Cangiano

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Albert Einstein, anti-pattern, bitcoin, bounce rate, cloud computing, en.wikipedia.org, John Gruber, Lean Startup, Network effects, revision control, Ruby on Rails, search engine result page, slashdot, software as a service, web application

Either way, it got my page more than fifty initial Likes. This means that new updates I posted on the page appeared in the News Feeds of these fans, who could then interact with the updates by liking them, commenting on them, or even sharing them with their friends. And hopefully their friends will do the same in turn, and so on. If your updates are engaging and your fans loyal enough, you can leverage a network effect and reach thousands of people’s News Feeds very quickly. For Twitter, I did something similar. I announced the new account from my personal Twitter account, leveraging my existing contacts in this case as well. If you don’t have the luxury of an existing account and network, fear not. We’ll delve right into how to acquire fans/followers in the next few sections. 14.4 Cross Promote Your Site and Social Properties You have a successful site and you’ve created various accounts on social networks.

When visitors follow you on Twitter, your follower count increases, which in turn shows social proof as well. Finally, when visitors like your fan page through your site, they’ll increase your Facebook counter, automatically subscribe to your updates on Facebook, and broadcast that they just liked you to their friends. A small percentage of their friends may decide to like you as well, and in turn, some of their followers will too, and so on. Again, a network effect can take place if enough people genuinely like your brand/site/blog. For Facebook, opt to use the official Like button so as to show a random assortment of your followers. Faces add a powerful human element to what you’re doing and may increase trust for your project or business as well as invite others to like the page also. If you have Twitter embedded in your site, opt for either its compact Follow button or one of Twitter’s widgets that showcase your latest tweets.


pages: 378 words: 110,518

Postcapitalism: A Guide to Our Future by Paul Mason

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Alfred Russel Wallace, bank run, banking crisis, banks create money, Basel III, basic income, Bernie Madoff, Bill Gates: Altair 8800, bitcoin, Branko Milanovic, Bretton Woods, BRICs, British Empire, business process, butterfly effect, call centre, capital controls, Cesare Marchetti: Marchetti’s constant, Claude Shannon: information theory, collaborative economy, collective bargaining, Corn Laws, corporate social responsibility, creative destruction, credit crunch, currency manipulation / currency intervention, currency peg, David Graeber, deglobalization, deindustrialization, deskilling, discovery of the americas, Downton Abbey, drone strike, en.wikipedia.org, energy security, eurozone crisis, factory automation, financial repression, Firefox, Fractional reserve banking, Frederick Winslow Taylor, full employment, future of work, game design, income inequality, inflation targeting, informal economy, information asymmetry, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, Kevin Kelly, knowledge economy, knowledge worker, late capitalism, low skilled workers, market clearing, means of production, Metcalfe's law, money: store of value / unit of account / medium of exchange, mortgage debt, Network effects, new economy, Norbert Wiener, Occupy movement, oil shale / tar sands, oil shock, Paul Samuelson, payday loans, Pearl River Delta, post-industrial society, precariat, price mechanism, profit motive, quantitative easing, race to the bottom, RAND corporation, rent-seeking, reserve currency, RFID, Richard Stallman, Robert Gordon, Robert Metcalfe, secular stagnation, sharing economy, Stewart Brand, structural adjustment programs, supply-chain management, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, Transnistria, union organizing, universal basic income, urban decay, urban planning, Vilfredo Pareto, wages for housework, women in the workforce

That’s why we noticed the disruptions first in the news industry, in music and the sudden loss of the state’s monopoly over political propaganda and ideology. Next, it began to undermine traditional concepts of property and privacy. Wikileaks and the controversy over the mass surveillance data collected by the NSA are just the latest phase of a war over who can own and store information. But the biggest impact of all is only now being understood. The ‘network effect’ was first theorized by Bell Telephone boss Theodore Vail 100 years ago. Vail realized that networks create something extra, for free. In addition to utility for the user of a telephone and revenue for the owner, he noticed a third thing: the more people join the network, the more useful it becomes to everybody. The problem comes when you try to measure and capture that third thing. Robert Metcalfe, the inventor of the Ethernet switch, claimed in 1980 that a network’s value is ‘the number of users squared’.

In 2013, the OECD’s economists agreed that it could not be captured by traditional market metrics. ‘While the Internet’s impact on market transactions and value added has been undoubtedly far-reaching,’ they wrote, ‘its effect on non-market interactions … is even more profound.’39 Economists have tended to ignore non-market interactions: they are, by definition, non-economic – as insignificant as a smile passed between two customers in the Starbucks queue. As to the network effect, they assumed its benefits would be quantified into lower prices and distributed between producers and consumers. But in the space of less than thirty years, network technologies have opened whole areas of economic life to the possibility of collaboration and production beyond the market. On 15 September 2008, the Nokias and Motorolas pointed at Lehman Brothers HQ, and the free wifi signal in the Starbucks opposite, were in their own way just as significant as the bank that had collapsed.


pages: 313 words: 95,077

Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky

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Andrew Keen, Berlin Wall, bioinformatics, Brewster Kahle, c2.com, crowdsourcing, en.wikipedia.org, hiring and firing, hive mind, Howard Rheingold, Internet Archive, invention of agriculture, invention of movable type, invention of the printing press, invention of the telegraph, jimmy wales, Kuiper Belt, liberation theology, lump of labour, Mahatma Gandhi, means of production, Merlin Mann, Metcalfe’s law, Nash equilibrium, Network effects, Nicholas Carr, Picturephone, place-making, Pluto: dwarf planet, prediction markets, price mechanism, prisoner's dilemma, profit motive, Richard Stallman, Robert Metcalfe, Ronald Coase, Silicon Valley, slashdot, social software, Stewart Brand, supply-chain management, The Nature of the Firm, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, transaction costs, ultimatum game, Vilfredo Pareto, Yogi Berra

Prior to that year sociologists understood that social networks somehow manage to be sparsely connected (most people have only a moderate number of connections), but that despite this sparseness the networks are both efficient (any two people are connected together by only a few links—the Six Degrees of Separation pattern) and robust (the loss of a random connection, or even several, doesn’t destroy the network). What they didn’t understand was how those networks were held together. In 1998 Duncan Watts and Steve Strogatz published their research on a pattern they dubbed the “Small World network.” Small World networks have two characteristics that, when balanced properly, let messages move through the network effectively. The first is that small groups are densely connected. In a small group the best pattern of communication is that everyone connects with everyone. In a group of friends Alice knows Bob, Carol, Doria, and Eunice, and each of them knows the others. In a cluster of five people there would be ten connections (by Birthday Paradox math), so each person could communicate directly with any of the others.

In 1994, Greg LeVert, telecommunications engineer, estimated that only half the world had made a phone call. By 2008, there were 3.3 billion mobile phone subscribers, out of a global adult population of less than 5 billion. This increase in scale, both of the underlying social media and of the population that uses it, is still creating surprises because large systems behave differently from small ones. One fitting name for the way more is different is “the network effect,” the name given to networks that become more valuable as people adopt them. Robert Metcalfe, the inventor of the Ethernet networking protocol, gave his name to a law that describes this increase in value. Metcalfe’s Law is usually stated this way: “The value of the network grows with the square of its users.” When you double the size of the network, you quadruple the number of potential connections.


pages: 391 words: 105,382

Utopia Is Creepy: And Other Provocations by Nicholas Carr

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Air France Flight 447, Airbnb, Airbus A320, AltaVista, Amazon Mechanical Turk, augmented reality, autonomous vehicles, Bernie Sanders, book scanning, Brewster Kahle, Buckminster Fuller, Burning Man, Captain Sullenberger Hudson, centralized clearinghouse, cloud computing, cognitive bias, collaborative consumption, computer age, corporate governance, crowdsourcing, Danny Hillis, deskilling, digital map, Donald Trump, Electric Kool-Aid Acid Test, Elon Musk, factory automation, failed state, feminist movement, Frederick Winslow Taylor, friendly fire, game design, global village, Google bus, Google Glasses, Google X / Alphabet X, Googley, hive mind, impulse control, indoor plumbing, interchangeable parts, Internet Archive, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, Jeff Bezos, jimmy wales, job automation, Kevin Kelly, lifelogging, low skilled workers, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, mental accounting, natural language processing, Network effects, new economy, Nicholas Carr, Norman Mailer, off grid, oil shale / tar sands, Peter Thiel, Plutocrats, plutocrats, profit motive, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, Republic of Letters, robot derives from the Czech word robota Czech, meaning slave, Ronald Reagan, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley ideology, Singularitarianism, Snapchat, social graph, social web, speech recognition, Startup school, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, technoutopianism, the medium is the message, theory of mind, Turing test, Whole Earth Catalog, Y Combinator

At the same time, and for related reasons, size began to matter. A lot. Big media outlets moved online, creating vast, enticing pools of branded content. Search engines and content aggregators expanded explosively, providing them with the money and expertise to create technical advantages—in speed and reliability, among other things—that often proved decisive in attracting and holding consumers. The winner-take-all “network effects” of mass communication systems took hold. (Everybody wants to be where everyone else is.) And, of course, people began to demonstrate their innate laziness, retreating from the wilds and following well-trod trails. A Google search may turn up thousands of results, but few of us bother to scroll beyond the top three. When convenience battles curiosity, convenience usually wins. Wikipedia provides a good example of the self-reinforcing power of the web’s centripetal force.

That won’t come as a surprise to anyone who has had to wait for a YouTube clip to begin after clicking the Start button. More interesting is the study’s finding of a causal link between higher connection speeds and higher abandonment rates. Every time a network gets quicker, we get antsier. “Every millisecond matters,” says a Google engineer. As we experience faster flows of information online, we become, in other words, less patient people. But impatience is not just a network effect. The phenomenon is amplified by the constant buzz of Facebook, Twitter, Snapchat, texting, and social networking in general. Society’s “activity rhythm” has never been so harried. Impatience is a contagion spread from gadget to gadget. All of this has obvious importance to anyone involved in producing online media or running data centers. But it also has implications for how all of us think, socialize, and in general live.


pages: 518 words: 107,836

How Not to Network a Nation: The Uneasy History of the Soviet Internet (Information Policy) by Benjamin Peters

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Albert Einstein, Andrei Shleifer, Benoit Mandelbrot, bitcoin, Brownian motion, Claude Shannon: information theory, cloud computing, cognitive dissonance, computer age, conceptual framework, continuation of politics by other means, crony capitalism, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Graeber, Dissolution of the Soviet Union, Donald Davies, double helix, Drosophila, Francis Fukuyama: the end of history, From Mathematics to the Technologies of Life and Death, hive mind, index card, informal economy, information asymmetry, invisible hand, Jacquard loom, Jacquard loom, John von Neumann, Kevin Kelly, knowledge economy, knowledge worker, linear programming, mandelbrot fractal, Marshall McLuhan, means of production, Menlo Park, Mikhail Gorbachev, mutually assured destruction, Network effects, Norbert Wiener, packet switching, Pareto efficiency, pattern recognition, Paul Erdős, Peter Thiel, Philip Mirowski, RAND corporation, rent-seeking, road to serfdom, Ronald Coase, scientific mainstream, Steve Jobs, Stewart Brand, stochastic process, technoutopianism, The Structural Transformation of the Public Sphere, transaction costs, Turing machine

Much of this characterized “McCulloch’s version of the brain,” which, Baran continued, “had the characteristics I felt would be important in designing a really reliable communication system.”41 Reliable national computer networking were inspired by models of complex (heterarchical) neural networks. The result of Baran’s conversations was packet switching, a technology that broke messages into “packets,” which allowed digital “bursts” of data to be rerouted around damaged parts of a network—just as the brain can reroute neural impulses around damaged neural matter. Similarly, Baran’s observation was that, due to network effects, the brilliance of a distributed network, whether neural or national, is that it does not need each of the average eighty-six billion neurons in the human brain to connect to every other (and the number of possible connections between eighty-six billion neurons is so incomprehensibly large that the need for robust reconnection becomes obvious).42 Rather, attaching to a couple of other nodes allows a distributed packet-switched network to reroute in real time around damaged territory, whether neural or national.

Both international and internal critics, including the British organizational cyberneticist Stafford Beer, were critical of Soviet management techniques.7 More than a network, the OGAS Project as formulated by Glushkov outlines a daring technocratic economic imagining that was meant to operate in a future Soviet information society by digitizing, supervising, and optimizing the coordination challenges besetting the national command economy. The associated costs and scale of such a supercharged system were accordingly colossal. Glushkov captured the sentiment of network effects, which is still alive in surveillance capitalism’s promotion of big data today, in this phrase: “world practice shows that the larger the object for which an information-management system is created, the greater its economic effect.”8 More than komchamstvo, or Lenin’s term for “Communist boasting,” the basic OGAS blueprint affirms its staggering magnitude. In its initial proposals, the OGAS Project estimated that it would take over thirty years to be fully online, that it would need a labor transfer of some 300,000 personnel, that costs would be upward of 20 billion rubles for the first fifteen years, and that tens of thousands of computing center and interactive access points would be distributed across the Soviet population.


pages: 366 words: 94,209

Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity by Douglas Rushkoff

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3D printing, activist fund / activist shareholder / activist investor, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business process, buy low sell high, California gold rush, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, centralized clearinghouse, citizen journalism, clean water, cloud computing, collaborative economy, collective bargaining, colonial exploitation, Community Supported Agriculture, corporate personhood, corporate raider, creative destruction, crowdsourcing, cryptocurrency, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Naomi Klein, Network effects, new economy, Norbert Wiener, Oculus Rift, passive investing, payday loans, peer-to-peer lending, Peter Thiel, post-industrial society, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, TaskRabbit, The Future of Employment, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, unpaid internship, Y Combinator, young professional, zero-sum game, Zipcar

Union Square Ventures founder Fred Wilson worries aloud on his company blog that digital entrepreneurs are more focused on creating monopolies and extracting value than they are on realizing the Internet’s potential to promote value creation by many players. Wilson is excited about the possibility of new platforms that allow new sorts of exchange, “but,” he says, “there is another aspect to the Internet that is not so comforting. And that is that the Internet is a network and the dominant platforms enjoy network effects that, over time, lead to dominant monopolies.”27 The fact that digital companies can build platform monopolies brings creative destruction to a whole new level. Amazon provides the clearest example of traditional corporate values amplified through a digital platform monopoly. As the New York Times explained, “At first, those in the publishing business considered it a cute toy (you could see a book’s exact sales ranking!)

With geographically based currencies, the thinking goes, the “buy local” ethos becomes visible—still voluntary but validated by merchants and political leaders. Unless you’re spending BerkShares, how can you make it clear to merchants that you are thoughtfully supporting local business? Local currencies are their own best publicity, rendering “buy local” visible and thereby fostering the community spirit and soft peer pressure that lead to widespread buy-in and network effect. Then again, some customers might demonstrate their loyalty to local merchants by forgoing the local currency discount altogether and spending “real” money without the discount. Many other communities are experimenting with variations on the BerkShare model. Proponents claim that by being removed from the greater economy, these currencies work against the scarcity bias of central currency and are more resistant to boom, bust, and bubble cycles.54 Detroit Dollars, Santa Barbara Missions, and, in the UK, the Bristol, Brixton, and Cumbrian Pounds each offer their particular variations.


pages: 326 words: 103,170

The Seventh Sense: Power, Fortune, and Survival in the Age of Networks by Joshua Cooper Ramo

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Airbnb, Albert Einstein, algorithmic trading, barriers to entry, Berlin Wall, bitcoin, British Empire, cloud computing, crowdsourcing, Danny Hillis, defense in depth, Deng Xiaoping, drone strike, Edward Snowden, Fall of the Berlin Wall, Firefox, Google Chrome, income inequality, Isaac Newton, Jeff Bezos, job automation, market bubble, Menlo Park, Metcalfe’s law, natural language processing, Network effects, Norbert Wiener, Oculus Rift, packet switching, Paul Graham, price stability, quantitative easing, RAND corporation, recommendation engine, Republic of Letters, Richard Feynman, Richard Feynman, road to serfdom, Robert Metcalfe, Sand Hill Road, secular stagnation, self-driving car, Silicon Valley, Skype, Snapchat, social web, sovereign wealth fund, Steve Jobs, Steve Wozniak, Stewart Brand, Stuxnet, superintelligent machines, technological singularity, The Coming Technological Singularity, The Wealth of Nations by Adam Smith, too big to fail, Vernor Vinge, zero day

The convenience, the efficiency, the benefits of Microsoft’s billions of dollars of research spending to you and me, might dwarf even the company’s massive profits. “Increasing returns,” Arthur wrote, “cause businesses to work differently, and they stand many of our notions of how business operates on their head.” The essential phenomenon that Arthur spotted at work two decades ago is something we now know as “network effects”—an idea that changed how we think about businesses, and particularly about the sticky and alluring power of gated, connected systems. In the years after Arthur’s paper was published, billions of us ran madly along a course he had anticipated: We crashed our way as fast as possible into those single, winning businesses, rewarding them with near-monopoly positions in exchange for the benefits of being “inside.”

Our modern gates are different from older ones because it is lethally costly to leave them for an impossibly slower world. It is why mastery of network gates is even more insanely lucrative than Cecil Rhodes’s gold mines. Think of the old Industrial Age power games for a moment, by way of comparison: Britain and Germany tried to match each other with their industrial output during a fatal competitive sprint 150 years ago. But imagine if network effects had obtained? If Britain’s initial head start in the Industrial Revolution had given them a 90 percent share of global trade? Germany would never have even tried to compete. They would have been the Friendster of the twentieth century: isolated, slow growing, powerless, and, finally, bankrupted or consumed. No need for World War I or World War II. But that was a different age. 6. Once a billion people were connected, there was inevitably going to be something like Facebook, a gateland in which people can link to one another.


pages: 283 words: 85,824

The People's Platform: Taking Back Power and Culture in the Digital Age by Astra Taylor

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A Declaration of the Independence of Cyberspace, American Legislative Exchange Council, Andrew Keen, barriers to entry, Berlin Wall, big-box store, Brewster Kahle, citizen journalism, cloud computing, collateralized debt obligation, Community Supported Agriculture, conceptual framework, corporate social responsibility, creative destruction, cross-subsidies, crowdsourcing, David Brooks, digital Maoism, disintermediation, don't be evil, Donald Trump, Edward Snowden, Fall of the Berlin Wall, Filter Bubble, future of journalism, George Gilder, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, Internet Archive, Internet of things, invisible hand, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Julian Assange, Kevin Kelly, Kickstarter, knowledge worker, Mark Zuckerberg, means of production, Metcalfe’s law, Naomi Klein, Narrative Science, Network effects, new economy, New Journalism, New Urbanism, Nicholas Carr, oil rush, peer-to-peer, Peter Thiel, Plutocrats, plutocrats, pre–internet, profit motive, recommendation engine, Richard Florida, Richard Stallman, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, slashdot, Slavoj Žižek, Snapchat, social graph, Steve Jobs, Stewart Brand, technoutopianism, trade route, Whole Earth Catalog, WikiLeaks, winner-take-all economy, Works Progress Administration, young professional

In his book Linked, physicist Albert-László Barabási investigated network phenomena by mapping online space and came to this dramatic conclusion: “The most intriguing result … is the complete absence of democracy, fairness, and egalitarian values on the Web.” These dynamics partly explain why, for all of its overwhelming, exciting variation, the Internet has a strange tendency toward monopoly. Aided by preferential attachment and network effects (the phenomenon of a good or service becoming more valuable the more people who use it), a handful of winners emerge, overshadowing other available options. While you can find something related to any subject online—medieval polyphonic music, lepidoptery, retroviruses, you name it—there is still one leading search engine (Google), one major bookstore (Amazon), one predominant market (eBay), one popular place to see movies (Netflix—a site that accounts for more than 40 percent of U.S. bandwidth usage most evenings), and so on.

Meanwhile, data from Compete, a Web analytics company, indicate that digital concentration may only be increasing: in 2001, ten Web sites accounted for 31 percent of U.S. page views; by 2010, that number had skyrocketed to 75 percent. “Big sucks the traffic out of small,” Yuri Milner, an investor who owns a chunk of Facebook, told Wired magazine. “In theory you can have a few very successful individuals controlling hundreds of millions of people. You can become big fast, and that favors the domination of strong people.” Preferential attachment, network effects, and the power laws they produce matter, in part, because they intensify and epitomize the old inequities we hoped the Internet would overthrow, from the star system to the hit-driven manufacturing of movies, music, and books. Winner-take-all markets promote certain types of culture at the expense of others, can make it harder for niche cultures and late bloomers to flourish, and contribute to broader income inequality.26 More specifically, where cultural production is concerned, the persistence of power laws refutes the myth of independent creators competing on even ground.


pages: 407 words: 103,501

The Digital Divide: Arguments for and Against Facebook, Google, Texting, and the Age of Social Netwo Rking by Mark Bauerlein

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Amazon Mechanical Turk, Andrew Keen, centre right, citizen journalism, collaborative editing, computer age, computer vision, corporate governance, crowdsourcing, David Brooks, disintermediation, Frederick Winslow Taylor, Howard Rheingold, invention of movable type, invention of the steam engine, invention of the telephone, Jaron Lanier, Jeff Bezos, jimmy wales, Kevin Kelly, knowledge worker, late fees, Mark Zuckerberg, Marshall McLuhan, means of production, meta analysis, meta-analysis, moral panic, Network effects, new economy, Nicholas Carr, PageRank, peer-to-peer, pets.com, Results Only Work Environment, Saturday Night Live, search engine result page, semantic web, Silicon Valley, slashdot, social graph, social web, software as a service, speech recognition, Steve Jobs, Stewart Brand, technology bubble, Ted Nelson, The Wisdom of Crowds, Thorstein Veblen, web application

• Even much of the infrastructure of the Web—including the Linux, Apache, MySQL, and Perl, PHP, or Python code involved in most Web servers—relies on the peer-production methods of open source, in themselves an instance of collective, Net-enabled intelligence. There are more than 100,000 open source software projects listed on SourceForge.net. Anyone can add a project, anyone can download and use the code, and new projects migrate from the edges to the center as a result of users putting them to work, an organic software adoption process relying almost entirely on viral marketing. The lesson: Network effects from user contributions are the key to market dominance in the Web 2.0 era. Blogging and the Wisdom of Crowds One of the most highly touted features of the Web 2.0 era is the rise of blogging. Personal home pages have been around since the early days of the Web, and the personal diary and daily opinion column around much longer than that, so just what is the fuss all about? At its most basic, a blog is just a personal home page in diary format.

We also studied a burgeoning group of start–ups and asked why they were growing so quickly. The answers helped us understand the rules of business on this new platform. Chief among our insights was that “the network as platform” means far more than just offering old applications via the network (“software as a service”); it means building applications that literally get better the more people use them, harnessing network effects not only to acquire users, but also to learn from them and build on their contributions. From Google and Amazon to Wikipedia, eBay, and craigslist, we saw that the value was facilitated by the software, but was cocreated by and for the community of connected users. Since then, powerful new platforms like YouTube, Facebook, and Twitter have demonstrated that same insight in new ways. Web 2.0 is all about harnessing collective intelligence.


pages: 410 words: 101,260

Originals: How Non-Conformists Move the World by Adam Grant

Albert Einstein, Apple's 1984 Super Bowl advert, availability heuristic, barriers to entry, business process, business process outsourcing, Cass Sunstein, clean water, cognitive dissonance, creative destruction, cuban missile crisis, Daniel Kahneman / Amos Tversky, Dean Kamen, double helix, Elon Musk, fear of failure, Firefox, George Santayana, Ignaz Semmelweis: hand washing, Jeff Bezos, job satisfaction, job-hopping, Joseph Schumpeter, Kickstarter, Lean Startup, Louis Pasteur, Mahatma Gandhi, Mark Zuckerberg, meta analysis, meta-analysis, minimum viable product, Network effects, pattern recognition, Paul Graham, Peter Thiel, Ralph Waldo Emerson, random walk, risk tolerance, Rosa Parks, Saturday Night Live, Silicon Valley, Skype, Steve Jobs, Steve Wozniak, Steven Pinker, The Wisdom of Crowds, women in the workforce

As physicist Max Planck once observed, “A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die.” I don’t mean to imply that it’s never wise to be first. If we all wait for others to act, nothing original will ever be created. Someone has to be the pioneer, and sometimes that will pay off. First-mover advantages tend to prevail when patented technology is involved, or when there are strong network effects (the product or service becomes more valuable when there are a greater number of users, as with telephones or social media). But in the majority of circumstances, your odds of success aren’t higher if you go first. And when the market is uncertain, unknown, or underdeveloped, being a pioneer has pronounced disadvantages. The key lesson here is that if you have an original idea, it’s a mistake to rush with the sole purpose of beating your competitors to the finish line.

Vincent, 114 Miller, Arthur, 238 Milosevic, Slobodan, 218–20, 223, 226, 227, 236, 241, 242 Mindset (Dweck), 169n Minkoff, Rob, 134, 135, 137, 141 minorities, 86 Mitteness, Cheryl, 54 Mojzisch, Andreas, 199n Molitor, Paul, 151 Mona Lisa (da Vinci), 96, 112 Moreno, Omar, 149 Morita, Akio, 183–84 Morse, Meroë, 182 motivation, 218, 248 converting anxiety into, 213, 215, 217 movements, 126 former adversaries and, 132 resistance, 219–20, 223, 225–27 status and, 121n–22n See also Coalitions movie rentals, 105 Moyers, Bill, 177 Mozart, Wolfgang Amadeus, 36 Mubarak, Hosni, 228 Musk, Elon, 172 My Left Foot, 238 Nadkarni, Sucheta, 100–101 NASA, 27, 197, 203 Navy, U.S., 125, 247 NBC, 34, 40, 45, 50 negative thinking, 212, 214, 214n neglect, 79–80, 89, 249 Nemeth, Charlan, 185, 191–94 Netflix, 105 network effects, 108 Neustadt, Richard, 178 new skills, learning, 246 Newton, Isaac, 151 New Yorker, 23 New York Times, 71 niches, 156–59, 174, 253 Nicolay, John, 98 Nike, 2 Nintendo, 104–5 Nobel Peace Prize, 143n Nobel Prize, 46–47, 110, 113, 123, 154, 232, 233 Norem, Julie, 212–13, 217 North Pole, 27, 210–11, 214, 217 O’Brien, Conan, 45 “O Canada,” 120 Occupy Wall Street, 125–26 odyssey, 104 offense, playing defense versus, 234n Office, The, 45 O’Keeffe, Georgia, 114 Oliner, Pearl, 163–65, 168 Oliner, Samuel, 163–65, 168 Omidyar, Pierre, 19–20 openness, 47n–48n opinions: believability and, 200–201, 207, 208 dissenting.


The Metropolitan Revolution: How Cities and Metros Are Fixing Our Broken Politics and Fragile Economy by Bruce Katz, Jennifer Bradley

3D printing, additive manufacturing, Affordable Care Act / Obamacare, British Empire, business climate, carbon footprint, clean water, cleantech, collapse of Lehman Brothers, deindustrialization, demographic transition, desegregation, double entry bookkeeping, edge city, Edward Glaeser, global supply chain, immigration reform, income inequality, industrial cluster, intermodal, Jane Jacobs, jitney, Kickstarter, knowledge economy, lone genius, Mark Zuckerberg, Masdar, megacity, Menlo Park, Moneyball by Michael Lewis explains big data, Network effects, new economy, New Urbanism, Occupy movement, place-making, postindustrial economy, purchasing power parity, race to the bottom, Richard Florida, Shenzhen was a fishing village, Silicon Valley, smart cities, smart grid, sovereign wealth fund, the built environment, The Death and Life of Great American Cities, the market place, The Spirit Level, Tony Hsieh, too big to fail, trade route, transit-oriented development, urban planning, white flight

But in general, casting a wider net makes it more likely that one person’s idea will interact usefully with another person’s idea and that something 02-2151-2 ch2.indd 37 5/20/13 6:48 PM 38 NYC: INNOVATION AND THE NEXT ECONOMY beneficial will emerge. Steven Johnson points to fourteenth-century Italian market cities as examples of networked economies: these were the places from which emerged double-entry bookkeeping—the notion of recording each transaction as a debit or a credit, which was one of financial accounting’s biggest innovations. This network effect applies to the game-changers approach as well: “They didn’t magically create some higher-level group consciousness. They simply widened the pool of minds that could come up with and share good ideas. This is not the wisdom of the crowd, but the wisdom of someone in the crowd.”66 Moreover, a half-year period of brainstorming sessions gave the NYCEDC time to discern common threads and connect different expressions or facets of the same idea.67 Cities and metropolitan areas concentrate the expertise of a vast range of people working in myriad sectors.

Sennett, Richard. The Craftsman. Yale University Press, 2008. ———. Together: The Rituals, Pleasures, and Politics of Cooperation. Yale University Press, 2012. 11-2151-2 biblio.indd 248 5/20/13 7:00 PM SELECTED BIBLIOGRAPHY 249 Sørensen, Eva, and Jacob Torfing. “The Democratic Anchorage of Governance Networks.” Scandinavian Political Studies 28, no. 3 (2005): 195–218. ———. “Making Governance Networks Effective and Democratic through Metagovernance.” Public Administration 87, no. 2 (2009): 234–58. Sorkin, Andrew Ross. Too Big to Fail: The Inside Story of How Wall Street and Washington Fought to Save the Financial System from Crisis—and Themselves. New York: Viking, 2009. Sthanumoorthy, R. “Rate War, Race to the Bottom, and Uniform State VAT Rates: An Empirical Foundation for a Difficult Policy Issue.”


pages: 151 words: 38,153

With Liberty and Dividends for All: How to Save Our Middle Class When Jobs Don't Pay Enough by Peter Barnes

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Alfred Russel Wallace, banks create money, basic income, Buckminster Fuller, collective bargaining, computerized trading, creative destruction, David Ricardo: comparative advantage, declining real wages, deindustrialization, diversified portfolio, en.wikipedia.org, Fractional reserve banking, full employment, hydraulic fracturing, income inequality, Jaron Lanier, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, land reform, Mark Zuckerberg, Network effects, oil shale / tar sands, Paul Samuelson, profit maximization, quantitative easing, rent-seeking, Ronald Coase, Ronald Reagan, Silicon Valley, sovereign wealth fund, the map is not the territory, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, Tyler Cowen: Great Stagnation, Upton Sinclair, Vilfredo Pareto, wealth creators, winner-take-all economy

The reasons why people pay hundreds of dollars, over and over, for unexceptional products that cost just a few dollars to reproduce include the following: • Everyone uses Microsoft programs, so if you want to be compatible, you have to use them, too. • Your computer manufacturer preinstalled them and included them in the price of your computer. • You can’t borrow them from friends because they’re copyrighted. Thus, a sizable portion of Microsoft’s stock value—arguably the lion’s share—comes from system properties such as the network effect, market power, and copyright protection, a gift for which our government charges nothing. On top of this, Microsoft benefits from decades of public investment in schools, semiconductors, and the Internet; centuries of scientific progress; and unstinting generosity from nature (think of the fuels and atmosphere required to power the Internet). When you add it all up, you can’t help but conclude that a large portion of Gates’s fortune wasn’t earned by him but rather was taken by him from wealth that rightfully belongs to everyone.


pages: 125 words: 28,222

Growth Hacking Techniques, Disruptive Technology - How 40 Companies Made It BIG – Online Growth Hacker Marketing Strategy by Robert Peters

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Airbnb, bounce rate, business climate, citizen journalism, crowdsourcing, digital map, Google Glasses, Jeff Bezos, Lean Startup, Menlo Park, Network effects, new economy, pull request, revision control, ride hailing / ride sharing, search engine result page, sharing economy, Skype, TaskRabbit, turn-by-turn navigation

. — Dan Martell, Founder of Clarity A growth hacker is someone who has thrown out the playbook of traditional marketing and replaced it with only what is testable, trackable, and scalable. Their tools are emails, pay-per-click ads, blogs, and platform APIs instead of commercials, publicity, and money. Growth hacking tends to be more “experience” focused. This includes driving engagement and sharing within a product or spreading a product experience across networks. Effective growth hackers are relentless about running creative experiments and optimizing the components of the experiment until finding something that works. - Sean Ellis, CEO of Qualaroo Perhaps my favorite however is by David Ogilvy, known as “the father of advertising.” It speaks to both the serious detail orientation of growth hacking and the relentless curiosity and urge to optimize that goes with it: “I prefer the discipline of knowledge to the anarchy of ignorance.


pages: 133 words: 36,528

Peak Car: The Future of Travel by David Metz

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autonomous vehicles, bike sharing scheme, Clayton Christensen, congestion charging, crowdsourcing, David Attenborough, decarbonisation, edge city, Edward Glaeser, Just-in-time delivery, Network effects, Richard Florida, Robert Gordon, Silicon Valley, Skype, urban sprawl, yield management, young professional

But low frequency is unattractive to users who will prefer the car if they have one, which further reduces the viability of the route. There is, nevertheless, scope to configure bus services to cater for off‑peak, cross‑city and recreational travel, as well as peak flows. A network of routes, linking with rail and trams, and with easy transfers, can attract passengers—as seen in many European cities as well as London. There is a ‘network effect’ at work—recognised by economists as a ‘positive externality’—in which the more users there are, the greater the value for each user, as first seen in the early days of telephones. For buses what is needed is a single planned network with near effortless transfers between routes, with timetable coordination and through ticketing. There is a debate about how best to organise a bus network. The approach in Britain outside London is to allow bus companies to run the routes they wish, hoping that competition between them will lead to services that meet people’s needs.


pages: 798 words: 240,182

The Transhumanist Reader by Max More, Natasha Vita-More

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23andMe, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, augmented reality, Bill Joy: nanobots, bioinformatics, brain emulation, Buckminster Fuller, cellular automata, clean water, cloud computing, cognitive bias, cognitive dissonance, combinatorial explosion, conceptual framework, Conway's Game of Life, cosmological principle, data acquisition, discovery of DNA, Douglas Engelbart, Drosophila, en.wikipedia.org, endogenous growth, experimental subject, Extropian, fault tolerance, Flynn Effect, Francis Fukuyama: the end of history, Frank Gehry, friendly AI, game design, germ theory of disease, hypertext link, impulse control, index fund, John von Neumann, joint-stock company, Kevin Kelly, Law of Accelerating Returns, life extension, lifelogging, Louis Pasteur, Menlo Park, meta analysis, meta-analysis, moral hazard, Network effects, Norbert Wiener, P = NP, pattern recognition, phenotype, positional goods, prediction markets, presumed consent, Ray Kurzweil, reversible computing, RFID, Richard Feynman, Ronald Reagan, silicon-based life, Singularitarianism, stem cell, stochastic process, superintelligent machines, supply-chain management, supply-chain management software, technological singularity, Ted Nelson, telepresence, telepresence robot, telerobotics, the built environment, The Coming Technological Singularity, the scientific method, The Wisdom of Crowds, transaction costs, Turing machine, Turing test, Upton Sinclair, Vernor Vinge, Von Neumann architecture, Whole Earth Review, women in the workforce, zero-sum game

Opponents of human enhancement focus on the alleged social harms that might result, while overlooking the huge social costs that forgoing the benefits of enhancement technologies would entail. Allen Buchanan posits “that some enhancements will increase human productivity very broadly conceived and thereby create the potential for large-scale increases in human ­well-being, and that the enhancements that are most likely to attract sufficient resources to become widespread will be those that promise increased productivity and will often exhibit what economists call network effects; the benefit to the individual of being enhanced will depend upon, or at least be greatly augmented by others having the enhancement as well” (Buchanan 2008: 2). Buchanan points out that much of the ethical debate (cited above) about enhancements focuses on them as positional goods that primarily help an individual to outcompete his rivals. This characterization of enhancements leads quickly and ineluctably to pervasive zero sum thinking in which for every winner there is assumed to be a loser.

Such social monitoring will be nearly as omnipresent as that of a hunter-gatherer band. Everyone will want to have a good reputation. One might try to fake being virtuous, but the best and easiest way to have a good reputation will be the same as it is today, by actually being virtuous. Buchanan argues that modern people have already adopted a wide array of enhancements that display these beneficial network effects, including literacy, numeracy, and social institutions that “extend our abilities beyond what is natural for human beings” (Buchanan 2008: 7). Some future biomedical enhancements that would significantly increase both individual and social productivity include those that raise the cognitive capabilities of human beings (memory, attention, and processing speed), increase healthy lifespans, and boost our immune systems.

Assumption#2: Once greater than human intelligence comes into existence, everything will change within hours or days or, at most, a few weeks. All the old rules will cease to apply. The awakening of a superhumanly intelligent computer is only one of several possible initiators of a Singularity recognized by Vinge. Other possibilities include the emergence of superhuman intelligence in computer networks, effective human-computer interfaces, and biotechnologically improved human intelligence. Whichever of these paths to superintelligence Vinge, like I.J. Good, expects an immediate intelligence explosion leading to a total transformation of the world. I have doubts about both of these assumptions. Curiously, the first assumption of an immediate jump from human-level AI to superhuman intelligence seems not to be a major hurdle for most people to whom Vinge has presented this idea.


pages: 777 words: 186,993

Imagining India by Nandan Nilekani

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affirmative action, Airbus A320, BRICs, British Empire, business process, business process outsourcing, call centre, clean water, colonial rule, corporate governance, cuban missile crisis, deindustrialization, demographic dividend, demographic transition, Deng Xiaoping, digital map, distributed generation, farmers can use mobile phones to check market prices, full employment, ghettoisation, glass ceiling, global supply chain, Hernando de Soto, income inequality, informal economy, Intergovernmental Panel on Climate Change (IPCC), joint-stock company, knowledge economy, labour market flexibility, land reform, light touch regulation, LNG terminal, load shedding, Mahatma Gandhi, market fragmentation, mass immigration, Mikhail Gorbachev, Network effects, new economy, New Urbanism, open economy, Parag Khanna, pension reform, Potemkin village, price mechanism, race to the bottom, rent control, rolodex, Ronald Reagan, school vouchers, Silicon Valley, smart grid, special economic zone, The Wealth of Nations by Adam Smith, Thomas L Friedman, Thomas Malthus, transaction costs, trickle-down economics, unemployed young men, upwardly mobile, urban planning, urban renewal, women in the workforce, working poor, working-age population

Table of Contents Copyright Page Title Page Dedication Foreword Part One - INDIA REIMAGINED IDEAS THAT HAVE ARRIVED INDIA, BY ITS PEOPLE FROM REJECTION TO OPEN ARMS - The Entrepreneur in India THE PHOENIX TONGUE - The Rise, Fall and Rise of English FROM MANEATERS TO ENABLERS HOME AND THE WORLD - Our Changing Seasons THE DEEPENING OF OUR DEMOCRACY A RESTLESS COUNTRY Part Two - ALL ABOARD IDEAS IN PROGRESS S IS FOR SCHOOLS - The Challenges in India’s Classrooms OUR CHANGING FACES - India in the City THE LONG ROADS HOME ERASING LINES - Our Emerging Single Market MOVING DEADLINES Part Three - FIGHTING WORDS IDEAS IN BATTLE THE SOUND AND THE FURY - Our Biggest Fights JOSTLING FOR JOBS INSTITUTIONS OF SAND - Our Universities A FINE BALANCE Part Four - CLOSER THAN THEY APPEAR IDEAS TO ANTICIPATE ICT IN INDIA - From Bangalore One to Country One CHANGING EPIDEMICS - From Hunger to Heart Disease OUR SOCIAL INSECURITIES - The Missing Demographic THE FOREST FOR THE TREES - India’s Environment Challenge POWER PLAYS - In Search of Our Energy Solutions THE NETWORK EFFECT CONCLUSION Acknowledgements NOTES A TIME LINE OF KEY EVENTS INDEX VIKING CANADA Published by the Penguin Group Penguin Group (Canada), 90 Eglinton Avenue East, Suite 700, Toronto, Ontario, Canada M4P 2Y3 (a division of Pearson Canada Inc.) • Penguin Group (USA) Inc., 375 Hudson Street, New York, New York 10014, U.S.A. • Penguin Books Ltd, 80 Strand, London WC2R 0RL, England Penguin Ireland, 25 St Stephen’s Green, Dublin 2, Ireland (a division of Penguin Books Ltd) • Penguin Group (Australia), 250 Camberwell Road, Camberwell, Victoria 3124, Australia (a division of Pearson Australia Group Pty Ltd) • Penguin Books India Pvt Ltd, 11 Community Centre, Panchsheel Park, New Delhi - 110 017, India • Penguin Group (NZ), 67 Apollo Drive, Rosedale, North Shore 0632, New Zealand (a division of Pearson New Zealand Ltd) • Penguin Books (South Africa) (Pty) Ltd, 24 Sturdee Avenue, Rosebank, Johannesburg 2196, South Africa Penguin Books Ltd, Registered Offices: 80 Strand, London WC2R 0RL, England Simultaneously published by the Penguin Press, a member of Penguin Group (USA) Inc.

It is increasingly obvious that what we need instead are well-connected states that diminish the distance between the two—the vitality of both the city and the village hinges on our infrastructure. Productivity in rural India will only improve with stronger supply chains and multiple ways to connect people, both within rural India and with urban areas. So far, India, and particularly the countryside, has not yet experienced the immense productivity gains that will emerge from the “network effect” of being well connected to markets through telecom, roads and rail. To date, our policy makers have underestimated the impact of building these connections. But as India’s fishermen who use mobile phones and farmers who use Internet kiosks have shown, giving people multiple means of connectivity can trigger a level of economic growth that we have so far underplayed. From how talk around roads, rail and power is changing, it is obvious that the new focus on infrastructure is here to stay.

We can move to empowerment and decentralization, from monopolistic, inefficient systems to a market governed by both efficiency standards and carbon pricing, and from subsidies to funds for new technologies and R&D in energy. It is a chance to choose a solution that is not “dirty, insecure and unsafe,” but one that is far more democratic and equitable, and which leverages India’s greatest strength—the momentum of our human capital and our capacity for bottom-up growth. THE NETWORK EFFECT OUR ANSWERS TO our emerging challenges—in technology, health, pensions, environment and energy—depend very much on decentralized approaches, and these will have to come, in part, from the same people who built the jugaad. Jugaad, which means “everything put together,” quick-fix and improvised, is the name of the vehicle that people in many parts of rural north India use to travel. This “car” is a brilliant improvisation, nailed together from whatever parts rural mechanics can get their hands on.


pages: 477 words: 135,607

The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger by Marc Levinson

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air freight, anti-communist, barriers to entry, Bay Area Rapid Transit, British Empire, call centre, collective bargaining, conceptual framework, David Ricardo: comparative advantage, deindustrialization, deskilling, Edward Glaeser, Erik Brynjolfsson, full employment, global supply chain, intermodal, Isaac Newton, job automation, knowledge economy, Malcom McLean invented shipping containers, manufacturing employment, Network effects, New Economic Geography, new economy, oil shock, Panamax, Port of Oakland, post-Panamax, Productivity paradox, refrigerator car, South China Sea, trade route, Works Progress Administration, Yom Kippur War, zero-sum game

Brian Arthur, Increasing Returns and Path Dependence in the Economy (Ann Arbor, 1994), chap. 2. There is an extensive literature exploring the economic costs of technological incompatibilities; see especially Joseph Farrell and Garth Saloner, “Installed Base and Compatibility: Innovation, Product Preannouncements, and Predation,” American Economic Review 76, no. 5 (1986): 940–955; Michael L. Katz and Carl Shapiro, “Systems Competition and Network Effects,” Journal of Economic Perspectives 8, no. 2 (1994): 93–115; and S. J. Liebowitz and Stephen E. Margolis, “Network Externality: An Uncommon Tragedy,” Journal of Economic Perspectives 8, no. 2 (1994): 133–150. 5. Minutes of November 18, 1958, meeting of Committee on Standardization of Van Container Dimensions (hereafter Marad Dimensions Committee). 6. Minutes of November 19, 1958, meeting of Committee on Construction and Fittings (hereafter Marad Construction Committee); author’s telephone interview with Vincent Grey, May 1, 2005. 7.

_. “Towards a Geography of Trade Costs.” Mimeo, University of Chicago, 1999. Isard, Caroline, and Walter Isard. “Economic Implications of Aircraft.” Quarterly Journal of Economics 59 (1945): 145–169. Jorgenson, Dale W., and Kevin J. Stiroh. “Information Technology and Growth.” American Economic Review 89, no. 2 (1999): 109–115. Katz, Michael L., and Carl Shapiro. “Systems Competition and Network Effects.” Journal of Economic Perspectives 8, no. 2 (1994): 93–115. Kelley, Robin D. G. “‘We Are Not What We Seem’: Rethinking Black Working-Class Opposition in the Jim Crow South.” Journal of American History 80, no. 1 (1993). Kerr, Clark, and Lloyd Fisher. “Conflict on the Waterfront.” Atlantic 184, no. 3 (1949). King, Robert C., George M. Adams, and G. Lloyd Wilson, “The Freight Container as a Contribution to Efficiency in Transportation.”


pages: 386 words: 122,595

Naked Economics: Undressing the Dismal Science (Fully Revised and Updated) by Charles Wheelan

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affirmative action, Albert Einstein, Andrei Shleifer, barriers to entry, Berlin Wall, Bernie Madoff, Bretton Woods, capital controls, Cass Sunstein, central bank independence, clean water, collapse of Lehman Brothers, congestion charging, creative destruction, Credit Default Swap, crony capitalism, currency manipulation / currency intervention, Daniel Kahneman / Amos Tversky, David Brooks, demographic transition, diversified portfolio, Doha Development Round, Exxon Valdez, financial innovation, fixed income, floating exchange rates, George Akerlof, Gini coefficient, Gordon Gekko, greed is good, happiness index / gross national happiness, Hernando de Soto, income inequality, index fund, interest rate swap, invisible hand, job automation, John Markoff, Joseph Schumpeter, Kenneth Rogoff, libertarian paternalism, low skilled workers, lump of labour, Malacca Straits, market bubble, microcredit, money market fund, money: store of value / unit of account / medium of exchange, Network effects, new economy, open economy, presumed consent, price discrimination, price stability, principal–agent problem, profit maximization, profit motive, purchasing power parity, race to the bottom, RAND corporation, random walk, rent control, Richard Thaler, rising living standards, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, school vouchers, Silicon Valley, Silicon Valley startup, South China Sea, Steve Jobs, The Market for Lemons, the rule of 72, The Wealth of Nations by Adam Smith, Thomas L Friedman, Thomas Malthus, transaction costs, transcontinental railway, trickle-down economics, urban sprawl, Washington Consensus, Yogi Berra, young professional, zero-sum game

You and some college friends could start a new airline relatively easily; the problem is that you wouldn’t be able to land your planes anywhere. There are a limited number of gate spaces available at most airports, and they tend to be controlled by the big guys. At Chicago’s O’Hare Airport, one of the world’s biggest and busiest airports, American and United control some 80 percent of all the gates.6 Or consider a different kind of entry barrier that has become highly relevant in the Internet age: network effects. The basic idea of a network effect is that the value of some goods rises with the number of other people using them. I don’t think Microsoft Word is particularly impressive software, but I own it anyway because I spend my days e-mailing documents to people who do like Word (or at least they use it). It would be very difficult to introduce a rival word-processing package—no matter how good the features or how low the price—as long as most of the world is using Word.


pages: 545 words: 137,789

How Markets Fail: The Logic of Economic Calamities by John Cassidy

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Albert Einstein, Andrei Shleifer, anti-communist, asset allocation, asset-backed security, availability heuristic, bank run, banking crisis, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Black-Scholes formula, Bretton Woods, British Empire, capital asset pricing model, centralized clearinghouse, collateralized debt obligation, Columbine, conceptual framework, Corn Laws, corporate raider, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, Daniel Kahneman / Amos Tversky, debt deflation, diversification, Elliott wave, Eugene Fama: efficient market hypothesis, financial deregulation, financial innovation, Financial Instability Hypothesis, financial intermediation, full employment, George Akerlof, global supply chain, Gunnar Myrdal, Haight Ashbury, hiring and firing, Hyman Minsky, income per capita, incomplete markets, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, laissez-faire capitalism, Landlord’s Game, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, market bubble, market clearing, mental accounting, Mikhail Gorbachev, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, Myron Scholes, Naomi Klein, negative equity, Network effects, Nick Leeson, Northern Rock, paradox of thrift, Pareto efficiency, Paul Samuelson, Ponzi scheme, price discrimination, price stability, principal–agent problem, profit maximization, quantitative trading / quantitative finance, race to the bottom, Ralph Nader, RAND corporation, random walk, Renaissance Technologies, rent control, Richard Thaler, risk tolerance, risk-adjusted returns, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, shareholder value, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical model, technology bubble, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, unorthodox policies, value at risk, Vanguard fund, Vilfredo Pareto, wealth creators, zero-sum game

In many parts of the economy, such as oil, autos, and finance, giganticism remains a basic fact of economic life. Then there is the high-technology sector, where monopoly power is endemic. One of the first people to point this out was W. Brian Arthur, a soft-spoken applied mathematician who grew up in Northern Ireland and fell into economics almost by accident. Back in the mid-1980s, Arthur, who was then at Stanford, presented a paper at Harvard in which he argued that chance events and network effects can enable inferior technologies to beat out superior products and take over entire markets. A Harvard economist, Richard Zeckhauser, stood up afterward and said, “If you are right, capitalism can’t work.” A few months later, Arthur presented the same paper in Moscow, where an eminent Russian economist said, “Your argument cannot be true!” The essence of Arthur’s paper was that with some types of goods, the utility they provide to people depends not just on their intrinsic merits but on how many other people are using them.

But the modern theory of the invisible hand that Friedman and others promoted explains too much with too little. At its core, it says simply: self-interest plus competition equals nirvana. There is no mention in this equation of the institutions of modern capitalism, such as multinational corporations, derivatives markets, universal banks, and mutual funds. Information asymmetries, uncertainty, copycat behavior, network effects, and disaster myopia—the invisible hand metaphor abstracts from all of these awkward features of reality, too. Don’t worry, its defenders say, the market will take care of things. Just make sure that competition reigns, prevent the emergence of monopolies, and a good outcome is guaranteed. Actually, some free market economists aren’t saying this anymore. Alan Greenspan has blamed the subprime collapse on the misleading risk models that private-sector enterprises relied on.


pages: 481 words: 125,946

What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence by John Brockman

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3D printing, agricultural Revolution, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, clean water, cognitive dissonance, Colonization of Mars, complexity theory, computer age, computer vision, constrained optimization, corporate personhood, cosmological principle, cryptocurrency, cuban missile crisis, Danny Hillis, dark matter, discrete time, Douglas Engelbart, Elon Musk, Emanuel Derman, endowment effect, epigenetics, Ernest Rutherford, experimental economics, Flash crash, friendly AI, functional fixedness, Google Glasses, hive mind, income inequality, information trail, Internet of things, invention of writing, iterative process, Jaron Lanier, job automation, John Markoff, John von Neumann, Kevin Kelly, knowledge worker, loose coupling, microbiome, Moneyball by Michael Lewis explains big data, natural language processing, Network effects, Norbert Wiener, pattern recognition, Peter Singer: altruism, phenotype, planetary scale, Ray Kurzweil, recommendation engine, Republic of Letters, RFID, Richard Thaler, Rory Sutherland, Satyajit Das, Search for Extraterrestrial Intelligence, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, superintelligent machines, supervolcano, the scientific method, The Wisdom of Crowds, theory of mind, Thorstein Veblen, too big to fail, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K

He devoted his life to the pursuit of that dream, but it eluded him because the technology was always too crude, too stupid, too inflexible to enable its realization. It still is, despite Moore’s Law and the rest of it. But it’s getting better, slowly. Search engines, for example, have in some cases become a workable memory prosthesis for some of us. But they’re still pretty dumb. So I can’t wait for the moment when I can say to my computer, “Hey, do you think Robert Nozick’s idea about how the state evolves is really an extreme case of network effects in action?,” and get an answer that’s approximately as good as what I get from the average grad student. That moment, alas, is still a long way off. Right now, I’m finding it hard to persuade my dictation software that when I say “Bruno Latour,” I don’t mean “Banana till.” But at least the “personal assistant” app on my smartphone knows that when I ask for the weather forecast I get the one for Cambridge, U.K., rather than Cambridge, MA.

The true transforming genius of human intelligence is not individual thinking at all but collective, collaborative, and distributed intelligence—the fact that (as the libertarian Leonard Read pointed out) it takes thousands of different people to make a pencil, not one of whom knows how to make a pencil. What transformed the human race into a world-dominating technium was not some change in human heads but a change among them: the invention of exchange and specialization. It was a network effect. We really have no idea what dolphins or octopi or crows could achieve if their brains were networked in the same way. Conversely, if human beings had remained largely autonomous individuals, they would have continued as rare hunter-gatherers at the mercy of their environments, as the huge-brained Neanderthals indeed did right to the end. What transformed human intelligence was the connecting-up of human brains into networks by the magic of division of labor, a feat first achieved on a small scale in Africa around 300,000 years ago and then with gathering speed in the last few thousand years.


pages: 442 words: 39,064

Why Stock Markets Crash: Critical Events in Complex Financial Systems by Didier Sornette

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Asian financial crisis, asset allocation, Berlin Wall, Bretton Woods, Brownian motion, capital asset pricing model, capital controls, continuous double auction, currency peg, Deng Xiaoping, discrete time, diversified portfolio, Elliott wave, Erdős number, experimental economics, financial innovation, floating exchange rates, frictionless, frictionless market, full employment, global village, implied volatility, index fund, information asymmetry, intangible asset, invisible hand, John von Neumann, joint-stock company, law of one price, Louis Bachelier, mandelbrot fractal, margin call, market bubble, market clearing, market design, market fundamentalism, mental accounting, moral hazard, Network effects, new economy, oil shock, open economy, pattern recognition, Paul Erdős, Paul Samuelson, quantitative trading / quantitative finance, random walk, risk/return, Ronald Reagan, Schrödinger's Cat, selection bias, short selling, Silicon Valley, South Sea Bubble, statistical model, stochastic process, Tacoma Narrows Bridge, technological singularity, The Coming Technological Singularity, The Wealth of Nations by Adam Smith, Tobin tax, total factor productivity, transaction costs, tulip mania, VA Linux, Y2K, yield curve

This is usually attributed to a “business-as-usual” corporate statement of a slightly revised, smallerthan-expected earnings! These considerations make it clear that it is the expectation of future earnings and future capital gains rather than present economic reality that motivates the average investor, thus creating a speculative bubble. It has also been proposed [289] that better business models, the network effect, first-to-scale advantages, and real options effect could account for the apparent overvaluation, providing a sound justification for the high prices of dot.com and other New Economy companies. In a nutshell, the arguments are as follows. 1. The better business models refer to the fact that dot.com companies such as Amazon require little capital investment compared to their autopsy of major c r a s h e s 271 brick-and-mortar competitors.

In addition, the reduced delay in receiving electronic payments from customers compared to sending payments to suppliers means that, as the business grows, it actually generates cash from working capital. 2. Usually, positive feedback stems from economies of scale: the largest companies sustain the lowest unit costs. Economies of scale are driven by the “supply side,” and consequently, may run into natural limitations and wane at a point well below market dominance. In the Internet economy, in contrast, positive feedback is fueled by the network effect, whose fundamental principle is that a network becomes more valuable to each user as incremental users are added. More specifically, the value of the network grows exponentially as the number of members grows arithmetically. A network of users is very valuable and becomes more so as it grows over time, locking in the customer base and enhancing the sustainability of excess returns. As companies start to enjoy the virtuous cycle, their revenue growth often meaningfully outstrips their cost increases. 3.


pages: 742 words: 137,937

The Future of the Professions: How Technology Will Transform the Work of Human Experts by Richard Susskind, Daniel Susskind

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23andMe, 3D printing, additive manufacturing, AI winter, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, Andrew Keen, Atul Gawande, Automated Insights, autonomous vehicles, Big bang: deregulation of the City of London, big data - Walmart - Pop Tarts, Bill Joy: nanobots, business process, business process outsourcing, Cass Sunstein, Checklist Manifesto, Clapham omnibus, Clayton Christensen, clean water, cloud computing, commoditize, computer age, Computer Numeric Control, computer vision, conceptual framework, corporate governance, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, death of newspapers, disintermediation, Douglas Hofstadter, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Frank Levy and Richard Murnane: The New Division of Labor, full employment, future of work, Google Glasses, Google X / Alphabet X, Hacker Ethic, industrial robot, informal economy, information retrieval, interchangeable parts, Internet of things, Isaac Newton, James Hargreaves, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, knowledge economy, lifelogging, lump of labour, Marshall McLuhan, Metcalfe’s law, Narrative Science, natural language processing, Network effects, optical character recognition, Paul Samuelson, personalized medicine, pre–internet, Ray Kurzweil, Richard Feynman, Richard Feynman, Second Machine Age, self-driving car, semantic web, Shoshana Zuboff, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, telepresence, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, transaction costs, Turing test, Watson beat the top human players on Jeopardy!, young professional

This represents a (slightly more than) one thousandfold increase in capacity in ten years. This is a doubling every year, a steeper exponential growth than in processing power. In the same vein is Metcalfe’s Law, which states (broadly speaking) that the value of a network to its users is proportional to the square of the number of the users connected to it. This is sometimes referred to as the ‘network effect’, and it means that a network’s utility increases non-linearly with the number of new users who join.24 Yet another illustration is Koomey’s Law—that the electrical efficiency of computation will double roughly every eighteen months, as it has done for the last six decades.25 We accept that Kurzweil’s theories do not command universal assent.26 However, other experts and commentators draw similar conclusions on the question of the exponential growth in processing power.27 We also acknowledge that exponential growth in information technologies need not always lead to an explosive increase in the speed and scale of adoption of new systems.

Adrian Paenza, ‘How folding paper can get you to the moon’, Ted-Ed video, <http://ed.ted.com/lessons/how-folding-paper-can-get-you-to-the-moon> (accessed 27 March 2015). 19 Ray Kurzweil, How to Create a Mind (2012), 249. Also see Kurzweil, The Singularity is Near, chs. 2 and 3. 20 Kurzweil, The Singularity is Near, 7–8. 21 Kurzweil, The Singularity is Near, 22–6. 22 Kurzweil, The Singularity is Near, 127. 23 Kurzweil, How to Create a Mind, 248–61. 24 The economic impact of this network effect is discussed by Michael Spence in his Nobel Prize lecture of 2001. See Michael Spence, ‘Signaling in Retrospect and the Informational Structure of Markets’, Nobel Prize Lecture, 8 Dec. 2001. 25 Jonathan Koomey et al., ‘Implications of Historical Trends in the Electrical Efficiency of Computing’, Annals of the History of Computing, 33: 3 (2011), 46–54. 26 See ongoing discussions on Kurzweil’s website <www.kurzweilai.net>.


pages: 528 words: 146,459

Computer: A History of the Information Machine by Martin Campbell-Kelly, William Aspray, Nathan L. Ensmenger, Jeffrey R. Yost

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Ada Lovelace, air freight, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Apple's 1984 Super Bowl advert, barriers to entry, Bill Gates: Altair 8800, borderless world, Buckminster Fuller, Build a better mousetrap, Byte Shop, card file, cashless society, cloud computing, combinatorial explosion, computer age, deskilling, don't be evil, Donald Davies, Douglas Engelbart, Douglas Engelbart, Dynabook, fault tolerance, Fellow of the Royal Society, financial independence, Frederick Winslow Taylor, game design, garden city movement, Grace Hopper, informal economy, interchangeable parts, invention of the wheel, Jacquard loom, Jacquard loom, Jeff Bezos, jimmy wales, John Markoff, John von Neumann, light touch regulation, linked data, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Menlo Park, natural language processing, Network effects, New Journalism, Norbert Wiener, Occupy movement, optical character recognition, packet switching, PageRank, pattern recognition, Pierre-Simon Laplace, pirate software, popular electronics, prediction markets, pre–internet, QWERTY keyboard, RAND corporation, Robert X Cringely, Silicon Valley, Silicon Valley startup, Steve Jobs, Steven Levy, Stewart Brand, Ted Nelson, the market place, Turing machine, Vannevar Bush, Von Neumann architecture, Whole Earth Catalog, William Shockley: the traitorous eight, women in the workforce, young professional

Between 1983 and 1991 the French government distributed more than 5 million Minitel units and developed an online telephone/address directory that people could use for free. The Minitel terminals, with their monochrome nine-inch screen and small keypads, cost approximately 500 francs (less than $100) to manufacture. The massive free distribution of these basic terminals (in place of white-page directories) led to what economists call “network effects”: more Minitel users generated the need for more service providers, more service providers attracted more users, and so on. The provision of new services, in turn, accelerated the demand for upscale Minitel units with larger screens and color monitors, which were sold or leased by France Télécom. A further contribution to Minitel’s financial success was the permissiveness of France Télécom and the French government regarding the types of services offered.

Thus Reader’s Digest Association saw consumer networks as a new form of publishing (which in time it became, though not until long after the Association had quit the business), and Sears saw the network as an extension of its famous mail-order catalog. Both organizations also had excellent distribution channels through which they could get access software into the hands of their subscribers. But success was elusive, and it proved very difficult to compete with CompuServe. The Source was sold to CompuServe in 1989, while Prodigy incurred huge losses before its owners abandoned it in 1996. CompuServe’s relative success benefited from network effects. At a time when users of one network could not communicate with those of another, it made sense to belong to the biggest network. By 1990, CompuServe had 600,000 subscribers and it offered literally thousands of services: from home banking to hotel reservations, from Roger Ebert’s movie reviews to Golf Magazine. In 1987 CompuServe had extended into Japan (with a service called NiftyServe) and in the early 1990s it began a service in Europe.


pages: 251 words: 44,888

The Words You Should Know to Sound Smart: 1200 Essential Words Every Sophisticated Person Should Be Able to Use by Bobbi Bly

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Albert Einstein, Alistair Cooke, Anton Chekhov, British Empire, Columbine, Donald Trump, George Santayana, haute couture, Honoré de Balzac, John Nash: game theory, Network effects, placebo effect, Ralph Waldo Emerson, school vouchers, Stephen Hawking, Steve Jobs

GEOPOLITICAL instability in the Middle East is fueling rising crude oil prices. geostationary (GEE-oh-STAY-shin-air-ee), adjective A satellite in orbit 22,300 miles above the Earth’s surface so that the satellite is always directly over the same spot of ground. Arthur C. Clark was the first to propose that three GEOSTATIONARY satellites orbiting Earth could provide a global communications network effectively covering every location on the planet. germane (jehr-MANE), adjective Relevant, pertinent, and fitting. “Quotes from Mao, Castro, and Che Guevara … are as GERMANE to our highly technological, computerized society as a stagecoach on a jet runway at Kennedy airport.” – Saul Alinksy, American activist germinal (JUHRM-nuhl), adjective Related to the earliest stage of development. Roland’s foray into art-buying is in its GERMINAL phase.


pages: 186 words: 49,251

The Automatic Customer: Creating a Subscription Business in Any Industry by John Warrillow

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Airbnb, airport security, Amazon Web Services, asset allocation, barriers to entry, call centre, cloud computing, commoditize, David Heinemeier Hansson, discounted cash flows, high net worth, Jeff Bezos, Network effects, passive income, rolodex, sharing economy, side project, Silicon Valley, Silicon Valley startup, software as a service, statistical model, Steve Jobs, Stewart Brand, subscription business, telemarketer, time value of money, zero-sum game, Zipcar

Once it achieved success in its original founding markets, it was able to expand, which further increased the value proposition for Zipcar members. Today, a Boston-based subscriber can not only find a car in her neighborhood, she can just as easily hop out of a train in Baltimore or a plane in Bristol, UK, and find a Zipcar. Thanks to leveraging the network model, Griffiths had built the company up to more than $100 million in revenue and 760,000 subscribers when Avis Budget Group acquired it in 2013 for $491 million.6 The Network Effect in Reverse The word-of-mouth advertising that helps you build a subscription business using the network model can also work in reverse. Let’s take a look at the dramatic rise and recent stumble of World of Warcraft, a fantasy adventure video game in the genre commonly referred to as MMORPGs (massively multiplayer online role-playing games). With a MMORPG, thousands of players in a game world interact with each other at the same time.


pages: 241 words: 43,073

Puppet 3 Beginner's Guide by John Arundel

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cloud computing, Debian, job automation, job satisfaction, Lao Tzu, Larry Wall, Network effects, SpamAssassin

Once he learns to use it, and to write programs in the standard language, he can take that skill with him to other jobs. He can choose from a large library of existing programs in the standard configuration language, covering most of the popular software in use. These programs are updated and improved to keep up with changes in the software and operating systems they manage. This kind of beneficial network effect is why we don't have a million different operating systems, or programming languages, or processor chips. There's strong pressure for people to converge on a standard. On the other hand, we don't have just one of each of those things either. There's never just one solution that pleases everybody. If you're not happy with an existing CM system, and you have the skills, you can write one that works the way you prefer.


pages: 188 words: 9,226

Collaborative Futures by Mike Linksvayer, Michael Mandiberg, Mushon Zer-Aviv

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4chan, Benjamin Mako Hill, British Empire, citizen journalism, cloud computing, collaborative economy, corporate governance, crowdsourcing, Debian, en.wikipedia.org, Firefox, informal economy, jimmy wales, Kickstarter, late capitalism, loose coupling, Marshall McLuhan, means of production, Naomi Klein, Network effects, optical character recognition, packet switching, postnationalism / post nation state, prediction markets, Richard Stallman, semantic web, Silicon Valley, slashdot, Slavoj Žižek, stealth mode startup, technoutopianism, the medium is the message, The Wisdom of Crowds, web application

This algorithmic logic justifies open access to knowledge and distribution of power that favors merit over entitlement. This is not a democracy, but a meritocracy. A meritocracy that favors technical expertise, free time, persistence and social skills. All traits that are definitely not evenly distributed. 102 Initiatives like FLOSS Manuals have acknowledged the importance of documentation for the collaborative process. To take real advantage of the network effect, we should learn to document failure, not only success. In the past, experiments in alternative social organizations were hampered by limitations on the resources available within individual projects, and isolated by the costs of communication and coordination with kindred efforts. This was the case of the Cooperative movement, communes, the occupied factories in Argentina and other similar alternative social experiments.


pages: 171 words: 54,334

Barefoot Into Cyberspace: Adventures in Search of Techno-Utopia by Becky Hogge, Damien Morris, Christopher Scally

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A Declaration of the Independence of Cyberspace, back-to-the-land, Berlin Wall, Buckminster Fuller, Chelsea Manning, citizen journalism, cloud computing, corporate social responsibility, disintermediation, Douglas Engelbart, Douglas Engelbart, Electric Kool-Aid Acid Test, Fall of the Berlin Wall, game design, Hacker Ethic, informal economy, information asymmetry, Jacob Appelbaum, jimmy wales, John Markoff, Julian Assange, Kevin Kelly, mass immigration, Menlo Park, moral panic, Mother of all demos, Naomi Klein, Network effects, New Journalism, Norbert Wiener, peer-to-peer, Richard Stallman, Silicon Valley, Skype, Socratic dialogue, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, technoutopianism, Telecommunications Act of 1996, Vannevar Bush, Whole Earth Catalog, Whole Earth Review, WikiLeaks

The many-to-many communications environment would allow individuals to bypass outmoded cultural gatekeepers and to smash corrupt institutions. The assumption was twofold – that those institutions would be unable to fight back, and that the ordinary people at the bottom of society, the edges of the network, were somehow worthier than the centralised elites at the top. Internet thinkers like to talk about “network effects”, about how networks that connect everyone to everyone double in value each time they add one more connection, how the value of a network, and thus its power, can increase exponentially and at a rapid pace. WikiLeaks takes advantage of this feature, and attempts to exploit it in pursuit of truth. But it works both ways. The crowd isn’t always wise. Courage isn’t always contagious. The WikiLeaks story also shows how easy it remains to distract the masses


pages: 201 words: 63,192

Graph Databases by Ian Robinson, Jim Webber, Emil Eifrem

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Amazon Web Services, anti-pattern, bioinformatics, commoditize, corporate governance, create, read, update, delete, data acquisition, en.wikipedia.org, fault tolerance, linked data, loose coupling, Network effects, recommendation engine, semantic web, sentiment analysis, social graph, software as a service, SPARQL, web application

ensures that assets that lack a status property are not included in the results. RETURN DISTINCT asset ensures that unique assets are returned in the results, no matter how many times they are matched. Given that such a query is readily supported by our graph, we gain confidence that the design is fit for purpose. Cross-Domain Models Business insight often depends on us understanding the hidden network effects at play in a complex value chain. To generate this understanding, we need to join domains together without distorting or sacrificing the details particular to each domain. Property graphs provide a solution here. Using a property graph, we can model a value chain as a graph of graphs in which specific relationships connect and distinguish constituent subdomains. In Figure 3-6 we see a graph representation of the value chain surrounding the pro‐ duction and consumption of Shakespearean literature.


pages: 133 words: 42,254

Big Data Analytics: Turning Big Data Into Big Money by Frank J. Ohlhorst

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algorithmic trading, bioinformatics, business intelligence, business process, call centre, cloud computing, create, read, update, delete, data acquisition, DevOps, fault tolerance, linked data, natural language processing, Network effects, pattern recognition, performance metric, personalized medicine, RFID, sentiment analysis, six sigma, smart meter, statistical model, supply-chain management, Watson beat the top human players on Jeopardy!, web application

Additional information and large data sets can be found on social media sites such as Facebook, Foursquare, and Twitter. A number of new businesses are now building Big Data environments, based on scale-out clusters using power-efficient multicore processors that leverage consumers’ (conscious or unconscious) nearly continuous streams of data about themselves (e.g., likes, locations, and opinions). Thanks to the network effect of successful sites, the total data generated can expand at an exponential rate. Some companies have collected and analyzed over 4 billion data points (e.g., web site cut-and-paste operations) since information collection started, and within a year the process has expanded to 20 billion data points gathered. DIVING DEEPER INTO BIG DATA SOURCES A change in resolution is further driving the expansion of Big Data.


pages: 219 words: 63,495

50 Future Ideas You Really Need to Know by Richard Watson

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23andMe, 3D printing, access to a mobile phone, Albert Einstein, artificial general intelligence, augmented reality, autonomous vehicles, BRICs, Buckminster Fuller, call centre, clean water, cloud computing, collaborative consumption, computer age, computer vision, crowdsourcing, dark matter, dematerialisation, digital Maoism, digital map, Elon Musk, energy security, failed state, future of work, Geoffrey West, Santa Fe Institute, germ theory of disease, happiness index / gross national happiness, hive mind, hydrogen economy, Internet of things, Jaron Lanier, life extension, Mark Shuttleworth, Marshall McLuhan, megacity, natural language processing, Network effects, new economy, oil shale / tar sands, pattern recognition, peak oil, personalized medicine, phenotype, precision agriculture, profit maximization, RAND corporation, Ray Kurzweil, RFID, Richard Florida, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Skype, smart cities, smart meter, smart transportation, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, supervolcano, telepresence, The Wisdom of Crowds, Thomas Malthus, Turing test, urban decay, Vernor Vinge, Watson beat the top human players on Jeopardy!, web application, women in the workforce, working-age population, young professional

It allows patients to control their own destiny and represents a significant shift in power away from the medical profession and pharmaceuticals industry toward the individual patient. One issue, for example, is why some medical records still held by medical institutions are often on paper. This is slowly changing, but until we achieve a shift in attitudes relating to who has access to what and in what format, this will act against not only the generation and transmission of knowledge by small groups of patients, but will also prevent the occurrence of larger network effects (i.e. “the wisdom of crowds”). “This artificial distinction between a consumer and a producer is dissolving, I call it the participant economy. Web 2.0 is about people.” David Sifry, Technorati But does user-generated medicine or “open-source health” really have a future? On the one hand, you’d think that privacy issues alone would prevent any meaningful exchange of knowledge, but this doesn’t seem to be an issue.


pages: 166 words: 49,639

Start It Up: Why Running Your Own Business Is Easier Than You Think by Luke Johnson

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Albert Einstein, barriers to entry, Bernie Madoff, collapse of Lehman Brothers, corporate governance, corporate social responsibility, creative destruction, credit crunch, Grace Hopper, happiness index / gross national happiness, high net worth, James Dyson, Jarndyce and Jarndyce, Jarndyce and Jarndyce, mass immigration, mittelstand, Network effects, North Sea oil, Northern Rock, patent troll, Plutocrats, plutocrats, Ponzi scheme, profit motive, Ralph Waldo Emerson, Silicon Valley, software patent, stealth mode startup, Steve Jobs, Steve Wozniak, The Wealth of Nations by Adam Smith, traveling salesman, tulip mania, Vilfredo Pareto, wealth creators

It couldn’t happen soon enough: if I were twenty-five with no ties I’d relocate to Silicon Valley or New York in a flash, the better to draw upon the bountiful and sophisticated investor culture in those places. So how do you reach this audience to raise equity? Despite the scale of business angel activity, it is an inefficient market. Both entrepreneurs and business angels complain that they find it difficult to meet each other and network effectively, but finding angel networks isn’t difficult – a quick web search will reveal that every country has multiple trade organizations for angel investors. It’s worth noting at this stage that the race for funding is like every other appealing prize: it attracts a small percentage of scammers, incompetents and shady types. The hard part is working out which of the networks of angels offer legitimate benefits.


pages: 239 words: 56,531

The Secret War Between Downloading and Uploading: Tales of the Computer as Culture Machine by Peter Lunenfeld

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Albert Einstein, Andrew Keen, Apple II, Berlin Wall, British Empire, Brownian motion, Buckminster Fuller, Burning Man, butterfly effect, computer age, creative destruction, crowdsourcing, cuban missile crisis, Dissolution of the Soviet Union, don't be evil, Douglas Engelbart, Douglas Engelbart, Dynabook, East Village, Edward Lorenz: Chaos theory, Fall of the Berlin Wall, Francis Fukuyama: the end of history, Frank Gehry, Grace Hopper, gravity well, Guggenheim Bilbao, Honoré de Balzac, Howard Rheingold, invention of movable type, Isaac Newton, Jacquard loom, Jacquard loom, Jane Jacobs, Jeff Bezos, John Markoff, John von Neumann, Mark Zuckerberg, Marshall McLuhan, Mercator projection, Metcalfe’s law, Mother of all demos, mutually assured destruction, Network effects, new economy, Norbert Wiener, PageRank, pattern recognition, peer-to-peer, planetary scale, Plutocrats, plutocrats, Post-materialism, post-materialism, Potemkin village, RFID, Richard Feynman, Richard Feynman, Richard Stallman, Robert Metcalfe, Robert X Cringely, Schrödinger's Cat, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Skype, social software, spaced repetition, Steve Ballmer, Steve Jobs, Steve Wozniak, Ted Nelson, the built environment, The Death and Life of Great American Cities, the medium is the message, Thomas L Friedman, Turing machine, Turing test, urban planning, urban renewal, Vannevar Bush, walkable city, Watson beat the top human players on Jeopardy!, William Shockley: the traitorous eight

Fuller maintained that the goal was to “make the world work, for 100% of humanity, in the shortest possible time, through spontaneous cooperation, without ecological offense or the disadvantage of anyone.” The World Game was a product of postscarcity thinking and 1960s’ utopianism, played without benefit of networks and computer simulations, but its essential message—that humans working together have the 73 CHAPTER 3 potential to craft a better world—resonates, and more than ever looks like a prototype for the networked effects of simulation and participation.26 Running Room or Play Space? Simulation and participation drive everything from figuring information to the fabbing of WYMIWYM objects; they make possible the mixing and mashing of open-source sound and imagescapes; and they shape the ways that we work as well as the ways that we play. It is my hope that the detailed listing of all these manifestations of the computer as culture machine in aggregate proves the existence of the unimodern unimedia posited at the start of this chapter.


pages: 295 words: 66,824

A Mathematician Plays the Stock Market by John Allen Paulos

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Benoit Mandelbrot, Black-Scholes formula, Brownian motion, business climate, butterfly effect, capital asset pricing model, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, diversified portfolio, Donald Trump, double entry bookkeeping, Elliott wave, endowment effect, Erdős number, Eugene Fama: efficient market hypothesis, four colour theorem, George Gilder, global village, greed is good, index fund, intangible asset, invisible hand, Isaac Newton, John Nash: game theory, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, mental accounting, Myron Scholes, Nash equilibrium, Network effects, passive investing, Paul Erdős, Paul Samuelson, Ponzi scheme, price anchoring, Ralph Nelson Elliott, random walk, Richard Thaler, Robert Shiller, Robert Shiller, short selling, six sigma, Stephen Hawking, survivorship bias, transaction costs, ultimatum game, Vanguard fund, Yogi Berra

Petersburg paradox Pareto laws. see power law Parrondo, Juan patterns, random events and PEG ratio personal accounting Peters, Tom Pi Pitt, Harvey Poincare, Henri politics campaign contributions politically incorrect funds power law and Ponzi schemes portfolios. see stock portfolios pound-euro/euro-pound exchange rate power law complex systems economic power “flocking effect” on Internet linguistics media influence political power price movements Pradilla, Charles Prechter, Bob predictability, of stock market complexity of cross-correlations over time and Efficient Market Hypothesis multifractal forgeries price anomalies leading to private information randomness vs. technical analysis trading strategies unemployment whim World Class Options Market Maker (WCOMM) present value compound interest and discounting process for stock purchases based on price movements complexity changes over time extreme movements herd-like and volatile nature of insider trading and network effect on normal curve and power law and subterranean information processing and price, P/E ratio price targets anchoring effect and hype and unrealistic prices, of stocks manipulating for own benefit (management/CEO) oscillation created by investor reactions to each other reflecting publicly available information prisoner’s dilemma private information becoming common knowledge dynamic with common knowledge market predictions and probability coin flipping game and dice and gambling games games of chance outguessing the average guess St.


pages: 247 words: 81,135

The Great Fragmentation: And Why the Future of All Business Is Small by Steve Sammartino

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3D printing, additive manufacturing, Airbnb, augmented reality, barriers to entry, Bill Gates: Altair 8800, bitcoin, BRICs, Buckminster Fuller, citizen journalism, collaborative consumption, cryptocurrency, David Heinemeier Hansson, Elon Musk, fiat currency, Frederick Winslow Taylor, game design, Google X / Alphabet X, haute couture, helicopter parent, illegal immigration, index fund, Jeff Bezos, jimmy wales, Kickstarter, knowledge economy, Law of Accelerating Returns, lifelogging, market design, Metcalfe's law, Metcalfe’s law, Minecraft, minimum viable product, Network effects, new economy, peer-to-peer, post scarcity, prediction markets, pre–internet, profit motive, race to the bottom, random walk, Ray Kurzweil, recommendation engine, remote working, RFID, Rubik’s Cube, self-driving car, sharing economy, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, social graph, social web, software is eating the world, Steve Jobs, survivorship bias, too big to fail, US Airways Flight 1549, web application, zero-sum game

In the new media of today the most trusted voice is an independent one, something a corporation can never be. Network diffusion In simple terms, Metcalfe’s law2 states that the power of a network is proportional to the number of connected people using the system. So, the power of a network increases as a function of the number of people using it. This law was first used to describe the network effects of fax machines or the number of telephone lines, both of which are useless with only one device. But the value of the network increases with each device because the total number of connections is increased. For example, two telephones can only make one connection, five can make 10 connections and 12 can make 66 connections. It offers a vast and noticeable difference from the one-message-to-all broadcast model of legacy media.


pages: 260 words: 76,223

Ctrl Alt Delete: Reboot Your Business. Reboot Your Life. Your Future Depends on It. by Mitch Joel

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3D printing, Amazon Web Services, augmented reality, call centre, clockwatching, cloud computing, Firefox, future of work, ghettoisation, Google Chrome, Google Glasses, Google Hangouts, Khan Academy, Kickstarter, Kodak vs Instagram, Lean Startup, Marc Andreessen, Mark Zuckerberg, Network effects, new economy, Occupy movement, place-making, prediction markets, pre–internet, QR code, recommendation engine, Richard Florida, risk tolerance, self-driving car, Silicon Valley, Silicon Valley startup, Skype, social graph, social web, Steve Jobs, Steve Wozniak, Thomas L Friedman, Tim Cook: Apple, Tony Hsieh, white picket fence, WikiLeaks, zero-sum game

The majority of people do not want to friend or like your brand. They use their social graphs for friends, family, and those they made fun of in high school. The intrusion of brands is simply that: an intrusion. Your business will never get everyone to like it. So instead, turn to the fanatical. Find and nurture your true fans. Your heavy users. As that relationship delivers, they will become evangelists for you and you will begin to experience the network effect. IT’S NOT (PERFECTLY) CLEAR. Look at everything from your business development and sales to your marketing and public relations. Is what you’re doing based on nurturing a more direct and personal relationship with your consumers, or are you simply blasting corporate messaging out through the channels? This fostering of direct relationships is what will move you forward through purgatory.


pages: 304 words: 82,395

Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schonberger, Kenneth Cukier

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23andMe, Affordable Care Act / Obamacare, airport security, AltaVista, barriers to entry, Berlin Wall, big data - Walmart - Pop Tarts, Black Swan, book scanning, business intelligence, business process, call centre, cloud computing, computer age, correlation does not imply causation, dark matter, double entry bookkeeping, Eratosthenes, Erik Brynjolfsson, game design, IBM and the Holocaust, index card, informal economy, intangible asset, Internet of things, invention of the printing press, Jeff Bezos, lifelogging, Louis Pasteur, Mark Zuckerberg, Menlo Park, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, obamacare, optical character recognition, PageRank, performance metric, Peter Thiel, Post-materialism, post-materialism, random walk, recommendation engine, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, smart grid, smart meter, social graph, speech recognition, Steve Jobs, Steven Levy, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Watson beat the top human players on Jeopardy!

These are things that were utterly impossible to know before, and which could change teaching and learning forever. Data exhaust can be a huge competitive advantage for companies. It may also become a powerful barrier to entry against rivals. Consider: if a newly launched company devised an e-commerce site, social network, or search engine that was much better than today’s leaders like Amazon, Google, or Facebook, it would have trouble competing not simply because of economies of scale and network effects or brand, but because so much of those leading firms’ performance is due to the data exhaust they collect from customer interactions and incorporate back into the service. Could a new online education site have the know-how to compete with one that already has a gargantuan amount of data with which it can learn what works best? The value of open data Today we’re likely to think of sites like Google and Amazon as the pioneers of big data, but of course governments were the original gatherers of information on a mass scale, and they still rival any private enterprise for the sheer volume of data they control.