Free PDF Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy, by Ariel Ezrachi
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Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy, by Ariel Ezrachi
Free PDF Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy, by Ariel Ezrachi
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Shoppers with Internet access and a bargain-hunting impulse can find a universe of products at their fingertips. In this thought-provoking exposé, Ariel Ezrachi and Maurice Stucke invite us to take a harder look at today’s app-assisted paradise of digital shopping. While consumers reap many benefits from online purchasing, the sophisticated algorithms and data-crunching that make browsing so convenient are also changing the nature of market competition, and not always for the better.Computers colluding is one danger. Although long-standing laws prevent companies from fixing prices, data-driven algorithms can now quickly monitor competitors’ prices and adjust their own prices accordingly. So what is seemingly beneficial―increased price transparency―ironically can end up harming consumers. A second danger is behavioral discrimination. Here, companies track and profile consumers to get them to buy goods at the highest price they are willing to pay. The rise of super-platforms and their “frenemy†relationship with independent app developers raises a third danger. By controlling key platforms (such as the operating system of smartphones), data-driven monopolies dictate the flow of personal data and determine who gets to exploit potential buyers.Virtual Competition raises timely questions. To what extent does the “invisible hand†still hold sway? In markets continually manipulated by bots and algorithms, is competitive pricing an illusion? Can our current laws protect consumers? The changing market reality is already shifting power into the hands of the few. Ezrachi and Stucke explore the resulting risks to competition, our democratic ideals, and our economic and overall well-being.
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Product details
Hardcover: 368 pages
Publisher: Harvard University Press (November 14, 2016)
Language: English
ISBN-10: 0674545478
ISBN-13: 978-0674545472
Product Dimensions:
6.5 x 1.2 x 9.8 inches
Shipping Weight: 1.4 pounds (View shipping rates and policies)
Average Customer Review:
3.5 out of 5 stars
6 customer reviews
Amazon Best Sellers Rank:
#738,743 in Books (See Top 100 in Books)
The book reviews various issues relating to price determination by computerized algorithms in e-commerce and other activities in the internet. I was familiar with most of the issues, and the book didn't teach me anything new about them. But there are few new interesting ideas mainly in regard to antitrust issues.
This is good and alerts you about the future.
Dull and unremarkable. Its a (really boring) textbook.The writers certainly don't understand the purely technical bits and there are errors in the relevant section, although they do understand the implications.
The U.S. Census estimates that 3o-commerce has increased from 2% of U.S. retail sales in 2004 to 6% in 2014, and growing at 16%/year in the U.S. - more than 3X the 5% growth rate in overall retail sales.The Internet has a number of platforms to reduce the time and expense of searching for what we want, and many have established themselves as significant players in the distribution chain - providing greater transparency (compare price and quality, reduce 'information asymmetries,' improve inventory management and marketing/advertising), efficiency, and ease of use. They also lower entry barriers - one no longer needs brick-and-mortar outlets to compete. A 2003 BusinessWeek story asked 'Is Wal-Mart Too Powerful?' Then, January 2016 Walmart announced the closing of 154 stores in the U.S. - attributed to more online commerce and comparison shopping. Walmart now plans to spend $2 billion on its e-commerce in 2015-16, far more than the $700 million spent in 2014. Despite Walmart revenues in 2014 being over 5X those of Amazon's ($486 billion vs. $89 billion), Amazon's stock value as of mid-2015 had eclipsed Walmart's by over $70 billion, and its sales are accelerating - partly by allowing different retailers to use its services.Amazon has a far greater product assortment and inventory than any brick-and-mortar retail outlet. Today it sells far more books than any retail bookstore, and is expected to be the largest clothing retailer in 2017. As any retailer's product assortment grows, so does the impracticability of manually adjusting pricing. Amazon uses computer algorithms that harvest personal and market data to constantly adjust pricing for its millions of products. Amazon sometimes alters prices more than once/day in reaction to other retailers. And online sellers are now increasing the speed at which goods arrive at the customer. Bezos' latest move is adding Chinese vendors - pressuring American vendors to lower prices and making the first move to include the Chinese - before Alibaba invades the U.S. with its Chinese vendors.Larger and larger sums of money are being invested in data collection and analytics. Clearly Big Data (volume, velocity, variety, and value of the data) and Big Analytics (IBM's 'Watson,' self-learning, language translation) can promote a competitive online environment where we benefit. However, we cannot uncritically assume we will always benefit. At times, dynamic pricing is good, eg. 'smart' parking meters. But this also brings the possibility of greater collusion and behavioral exploitation. Sophisticated game theory can now be employed in real time. Ensuring competition will require looking at this new online e-commerce environment.Cartels, even when unsuccessful, are still typically condemned as illegal. But what happens when sophisticated algorithms are designed to follow cartel behavior? They could much more quickly detect cheating or deviations, and then punish those deviations. The day after Easter in 2015, an online poster retailer named David Topkins became the first e-commerce executive to be prosecuted under antitrust law. He'd used Amazon Marketplace. Uber's algorithm can lead to horizontal collusion if the algorithm pushes up prices based on the perceived market value of a ride, rather than its actual market value. Smart machines pursuing self-learning and experimentation may collude without manual intervention.Two-thirds of online shoppers abandon their carts after initial 'purchase placement.' Sellers might then determine such buyers are more price sensitive - though buyers would quickly learn and act accordingly.Bottom-Line: "We cannot assume that the digitized hand will always protect our welfare."
as expected
Incredibly important work that is a must-read for anyone interested in competition policy online.
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