price discrimination

The Means of Prediction: How AI Really Works (And Who Benefits)

by Maximilian Kasy  · 15 Jan 2025  · 209pp  · 63,332 words

credit, private health insurance, and air travel, especially in the United States. Individualized price setting is likely to become increasingly widespread, absent legal constraints on price discrimination. Once data collection and predictive capabilities have advanced enough, companies will be able to set prices exactly equal to each buyer’s willingness or ability

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consumers were to have collective control over the rules of price setting, it would often be in their interest not to allow for such monopolistic price discrimination. There are furthermore not only distributional conflicts between monopolists and consumers; there are also distributional conflicts between different groups of consumers who differ in their

The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future

by Orly Lobel  · 17 Oct 2022  · 370pp  · 112,809 words

inequities. By contrast, it is largely impossible to conduct such accurate, robust, ongoing, and granular detection of disparities when it comes to the very real price discrimination that exists offline. In one famous field experiment from the early 1990s, participants posed as buyers at used car dealerships. It’s not difficult to

Virtual Competition

by Ariel Ezrachi and Maurice E. Stucke  · 30 Nov 2016

Steroids: The Predictable Agent 56 8 Artificial Intelligence, God View, and the Digital Eye 71 PART III Behavioral Discrimination 83 9 Price Discrimination (Briefly) Explained 85 10 The Age of Perfect Price Discrimination? 89 11 The Rise of “Almost Perfect” Behavioral Discrimination 101 12 Behavioral Discrimination: Economic and Social Perspectives 117 13 The Comparison

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perfect strategies to optimize profitability. These developments appear to give rise to new forms of competition and commerce. The traditional competitive problems (collusion, monopoly, and price discrimination) should arguably appear infrequently in the digital world, where rivals are simply a click away. With price algorithms analyzing and responding in real time to

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how Big Data and machine learning will enable companies to better discriminate in pricing. But several challenges currently prevent algorithms from perfectly discriminating. While perfect price discrimination is unlikely in the short term, Chapter 11 explores behavioral discrimination, where data-driven algorithms learn how to segment us into smaller groups to target

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the supermarket lowers its price. Here the retailer is responding to a shift in demand for its remaining supply. In principle, these practices differ from price discrimination, where the supermarket charges different prices to different consumers, based on their different reservation prices, for the same bread. In practice, the distinction between dynamic

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tell. What might appear as pricing responsive to changing market conditions may simply be the supermarket segmenting customers by their price sensitivity. Why Do Firms Price Discriminate? Price discrimination is often profitable.10 Returning to our gallery example, when the gallery charges a fi xed price, say $250, for a black-and-white photo

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most he or she is willing to pay? Competition as we know it is changing as companies experiment in devising better ways to price discriminate—far better than the imperfect price discrimination of the analog era (such as the senior citizen discount). Chronicling the advancements in tracking us and collecting our data, this chapter

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an everyday low price? How are online firms able to minimize the attractiveness of the consumer’s outside options? What economists and competition lawyers call “price discrimination,” online industry participants call “price optimization” or “dynamic differential pricing”. Dynamic differential pricing, as Massachusetts Institute of Technology Professor Yossi Sheffi has put it,

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be shocked initially by how expensive or inexpensive things are; eventually you adjust. So with bounded rational consumers with imperfect willpower, the move toward perfect price discrimination requires identifying all the key parameters for each individual, and observing and improving the estimate of each parameter. Does a customer’s reservation price for

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of a greater variety and volume of personal data, online companies can more closely approximate our reservation price. They may find the road to perfect price discrimination and increased profits irresistible. They will compete in refining their pricing algorithms’ many independent variables, and in more precisely classifying individuals into smaller subgroups.

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the same price for corporate stock. They accept that the pricing differences are responsive to market changes in supply and demand (dynamic pricing) rather than price discrimination (differential pricing). So once consumers accept that prices change rapidly (such as airfare, hotels, etc.), they have lower expectations of price uniformity among competitors.

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by large companies, just as for individual consumers.”64 An interesting and challenging question which emerges from our discussion is whether the enhanced capacity to price discriminate in a digitalized environment should call for a more interventionist approach. The next chapter examines the welfare implications of behavioral discrimination, and what tools enforcers

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this chapter we consider the welfare effects of behavioral discrimination. We do so in two steps. First, we explore the welfare effects of price discrimination. We note how price discrimination’s welfare effects are mixed. On the one hand, our increasingly automated, digitalized transactions could create a more transparent marketplace in which resources are

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hand, pricing algorithms may be used to exploit customers and raise “the seemingly endless possibilities for both chaos and mischief.”1 Second, we move beyond price discrimination into the murkier water of behavioral discrimination. Digitalized algorithm-based markets are characterized by the ability of sellers to increasingly “shadow” our activities, harvest data

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a fall in consumers’ trust in online markets.”15 The Added Complexity of Behavioral Discrimination Behavioral discrimination amplifies many of the welfare effects associated with price discrimination. Information gathered about our behav ior, 120 Behavioral Discrimination desires, and ability to pay can help firms exploit consumer biases. Sophisticated online sellers can manipulate

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our environment to increase overall consumption by price discriminating and by shifting the demand curve to the right (getting people other wise uninterested in the product to buy). At times behavioral discrimination may generate

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that many parents will likely pay more or less than we do. No parent, to our knowledge, has stormed the dean’s office protesting the price discrimination. Instead, price discrimination in some contexts, such as higher education, is more accepted than in many other contexts, where people view it as unfair. Why is this

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. The introduction of a profit motive changes the framework of assessment and leads many people to perceive price discrimination as unfair. This attitude intensifies where behavioral discrimination is exposed and people perceive themselves as victims of manipulation. Economic and Social Perspectives 123 (Lack

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S v. Konkurrencerådet,52 the court clarified that “the fact that the practice of a dominant undertaking may, like the pricing policy . . . [be] described as ‘price discrimination’, . . . , cannot of itself suggest that there exists an exclusionary abuse.”53 Evidently, other laws may prohibit discrimination on a broader basis— such as discrimination based

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degradation of air travel, and the rise of airline fees—from luggage to printing boarding passes—our future norms may well include online segmentation and price discrimination. Many forms of discrimination, involving different pricing on mobile platforms and PCs, personalized search results, personalized coupons, and price steering,60 are already appearing

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legal intervention, behavioral discrimination will likely become in many retail industries the new norm. 13 The Comparison Intermediaries H AVING CONSIDERED the possible use of price discrimination in an algorithm- driven environment, we explore in this chapter the role played by price comparison websites (PCWs) and metasearch engines. These comparison intermediaries

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support market transparency, and as such create an environment which can reduce the capacity for price discrimination and help safeguard our welfare. Indeed, these comparison and search platforms have become an integral part of our web environment: Google, Bing, Yahoo!, Amazon,

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an interesting aty pical form of competition. The rise of platform competition and pricing algorithms entails companies increasingly becoming “Frenemies.” 147 148 Frenemies Horizontal Competition Price Discrimination Tacit Collusion Frenemies Horizontal Collaboration Vertical Input Figure 1. Frenemies Figure 1 reflects the move beyond the binary world of coordinated effects/ tacit collusion (which

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Part II addresses) and unilateral effects/price discrimination (which Part III addresses), and beyond horizontal and vertical interplay, to the dynamic real ity of Frenemies. Firms here collaborate (friends), compete (enemies), at

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preferences), the pricing algorithms can also enable sellers to better segment customers and engage in behavioral discrimination—again, at our expense. Some enforcers today accept price discrimination as efficiency-enhancing. Some enforcers scoff at the advances in economic thinking over the past thirty years–downplaying the role of imperfect willpower and biases

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, and Ashkan Soltani, “Websites Vary Prices, Deals Based on Users’ Information,” Wall Street Journal, December 24, 2012, http://www.wsj.com/articles/SB10001424127887 323777204578189391813881534. 9 • Price Discrimination (Briefly) Explained 1. Herbert Hovenkamp, Mark D. Janis, Mark A. Lemley, Christopher R. Leslie, and Michael A. Carrier, IP and Antitrust: An Analysis of Antitrust

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route, the carriers’ competition for consumers with higher price elasticity of demand increases, while fares charged to consumers with inelastic demand stay high”; J. Stavins, “Price Discrimination in the Airline Markets: The Effect of Market Concentration,” Review of Economics and Statistics 83 (2001): 200. In line with this rationale, the competition agencies

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.uk /government/uploads/system /uploads/attachment _data/fi le/435817/The _commercial _use _of_consumer _data.pdf, 3.48. Papandropoulos, “How Should Price Discrimination Be Dealt with by Competition Authorities?” “Price discrimination can also be an instrument to implement predatory pricing. Indeed, it can reduce the costs of the strategy and therefore, make it

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same IP address, leading to the website to offer a higher price on each successive search.” Mac Macmillan, “European MEP Calls for Investigation of Online Price Discrimination,” Hogan Lovells Chronicle of Data Protection, September 13, 2013, http://www.hldataprotection.com/2013/09/articles/consumer-privacy /european-mep-calls-for-investigation-of-online

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travel agency is starting to show them different, and sometimes costlier, travel options than Windows visitors see.”). Article referred to in Frederik Zuiderveen Borgesius, “Online Price Discrimination and Data Protection Law,” Amsterdam Law School Research Paper No. 2015-32 (August 28, 2015), http://ssrn.com/abstract =2652665. 13 • The Comparison Intermediaries

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/articles/get-ready-for-your-digital-model-1447351480?alg = y. 32. For discussion of the applicability of the EU data protection law to price discrimination, see Frederik Zuiderveen Borgesius, “Online Price Discrimination and Data Protection Law,” Amsterdam Law School Research Paper No. 2015-32 (August 28, 2015), http://ssrn.com/abstract =2652665. 33. Simon

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intermediaries and, 139–142, 143 Airbnb, 6–7 Airlines: behavioral discrimination and, 112, 294n4; collusion and, 40–41, 269n16; comparison intermediaries and price distortion, 137; price discrimination and, 87 Airline Tariff Publishing case, 40–41 AKZO, 118–119 Algorithms, proposal to audit, 230–231. See also Self-learning algorithms Allstate, 90 Alphabet

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, 297n12; reduced by online markets, 6–7 Baymard Institute, 110 Behavioral advertising, 20, 262n75 Behavioral discrimination (general), viii, 32, 83–84. See also Comparison intermediaries; Price discrimination Behavioral discrimination, “almost perfect,” 30, 101–116, 289n1; biases used to increase consumer demand, 105–113; personal data and informational asymmetries, 112–115, 294n62; self

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superplatforms and, 173–174; intervention and antitrust issues, 188–190; superplatforms, advertising revenue, and privacy issues, 178–190 Inequality. See Wealth inequality Inflated list prices, price discrimination and, 97–99 Information flow: hub and spoke collusion scenario, 52, 275nn28,30; improved by comparison intermediaries, 132; online markets benefits and, 4, 50 Intel

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Morgan Stanley, 269n9 Morozov, Evgeny, 239 Most Favored Nation (MFN) clauses, comparison intermediaries and, 140–142, 143 Neoclassical economics, 205; behavioral discrimination and, 120–121; price discrimination and, 117–119, 295nn4–9, 297n12 Nest Labs, 154 Netfl ix, 238, 337n22 Network effects: of comparison intermediaries, 133–135, 303n6; market power and, 237

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platforms and, 244–246 Post Danmark A/S v. Konkurrencerådet, 128 Power Conversion, Inc. v. Saft Am., Inc., 271n20 Predictability, and insufficient data for perfect price discrimination, 97–98 Predictable agent collusion scenario, 36–37, 56–70, 221; enforcement challenges and anticompetitive intent issues, 65–69, 279n31, 280nn39,41; predictive analytics and

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47, 269n7 Rubicon Project, 259n47 “Rule of Reason” standard, 54–55, 246, 279n31, 343n73 Index Salem, Enrique, 149 Sample size, and insufficient data for perfect price discrimination, 99 San Francisco parking regulation, 217, 328nn32–37; SFpark program, 214, 328nn32–37 Scarcity marketing, 110 Schmidt, Eric, 147 Schumpeter, Joseph, 295–296n6 Search costs

Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking

by Foster Provost and Tom Fawcett  · 30 Jun 2013  · 660pp  · 141,595 words

companies did not have adequate information systems to deal with differential pricing at massive scale, and (2) bank management believed customers would not stand for price discrimination. Around 1990, two strategic visionaries (Richard Fairbanks and Nigel Morris) realized that information technology was powerful enough that they could do more sophisticated predictive modeling

People, Power, and Profits: Progressive Capitalism for an Age of Discontent

by Joseph E. Stiglitz  · 22 Apr 2019  · 462pp  · 129,022 words

for the same thing—price is determined by the (marginal) cost of production, not by the value the customer places on the good. Yet such price discrimination has become commonplace in our digital economy, as we discuss further in chapter 6. Innovation in creating market power There can be little doubt that

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product, a better service. But now we know that higher profits can also arise from a better way of exploiting consumers, a better way of price discrimination, extracting “consumer surplus” (the excess of what individuals would be willing to pay for a product from what he would have to pay in a

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individual values different products and is therefore willing to pay, they give these firms the power to price discriminate, to charge more to those customers who value the product more or who have fewer options.17 Price discrimination not only is unfair, but it also undermines the efficiency of the economy: standard economic theory

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innovators, partly because more of what is spent on research is devoted to sustaining and increasing market power and devising better ways of exploiting it. Price discrimination—where firms charge different prices to different customers, an increasing characteristic of the digital economy as firms use the data they have collected on each

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worse—establishing what is the relevant market is often hard. When there is direct evidence of market power (of the kind discussed above—high markups, price discrimination, excessive returns with no entry, forcing buyers to accept terms, like arbitration clauses, that should be unacceptable), that should be proof enough. For further discussion

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,” Journal of Information Technology 30, no. 1 (2015): 75–89; and Shoshana Zuboff, The Age of Surveillance Capitalism (New York: Public Affairs, 2019). 17.“Perfect” price discrimination is the practice of trying to charge each consumer the maximum he is willing to pay for a good or service. In each market for

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made illegal under the Robinson-Patman Act of 1936, but the act has rarely been enforced. For a discussion of price discrimination in the context of Big Data, see Silvia Merler, “Big Data and First-Degree Price Discrimination,” Bruegel, Feb. 20, 2017, available at http://bruegel.org/2017/02/big-data-and-first-degree

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-price-discrimination/. 18.The standard argument for efficiency of markets is based on the notion that individuals’ marginal valuation of a good are

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cost, and this is true because they all face the same prices. While there can still be market efficiency if there is perfect price discrimination, the real world of imperfect price discrimination is marked by pervasive inefficiencies and distortions. See, e.g., Stiglitz, “Monopoly, Non-Linear Pricing and Imperfect Information: The Insurance Market,” Review

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pattern of trade, 90–91 Paul, Rand, xix Paxton, Robert O., 15–16 per capita income, China, 37, 96 perfect competition, monopoly vs., 56 perfect price discrimination, 318n17 Petersen, Matthew Spencer, 17 Pew Mobility Project, 45 pharmaceutical companies, See Big Pharma Phishing for Phools: The Economics of Manipulation and Deception (Akerlof and

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market, See market power PPP (purchasing power parity), 272n12 predatory behavior, 145 predatory pricing, 69 pre-distribution, xxv, 198 preemptive mergers, 60–61, 70, 73 price discrimination, 57, 64, 125 pricing power, 48, 50 principal agent problem, 291n58 prisons, See incarceration privacy, 127–30, 135 private equity, 258n6 private prisons, 323n8 private

Future Politics: Living Together in a World Transformed by Tech

by Jamie Susskind  · 3 Sep 2018  · 533pp

abuses in the form OUP CORRECTED PROOF – FINAL, 26/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS 358 FUTURE POLITICS of price discrimination, predatory pricing, and the like, rather than to shape and constrain political power. But as we saw in chapter eighteen, the Data Deal means that

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/2017/05/how-online-shopping-makes-suckers-of-usall/521448/?utm_source=nextdraft&utm_medium=email> (accessed 1 December 2017). Benjamin Reed Shiller, ‘First-Degree Price Discrimination Using Big Data’, Brandeis University, 19 January 2014 <http://benjaminshiller. OUP CORRECTED PROOF – FINAL, 30/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK

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.COM/WSNWS 420 Notes com/images/First_Degree_PD_Using_Big_Data_Jan_18,_2014.pdf > (accessed 1 December 2017). 35. Shiller, ‘First-Degree Price Discrimination’. 36. See Lawrence Lessig, Code Version 2.0 (New York: Basic Books, 2006). Chapter 15 1. See Axel Honneth, The Struggle for Recognition: The Moral

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.businessinsider.com/amazons-go-supermarket-of-the-future3-human-staff-2017-2?r=UK&IR=T> (accessed 8 Dec. 2017). Shiller, Benjamin Reed. ‘First-Degree Price Discrimination Using Big Data’. Brandeis University, 19 Jan. 2014 <http://benjaminshiller.com/ images/First_Degree_PD_Using_Big_Data_Jan_18,_2014.pdf> (accessed 1 Dec

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by Bryan Caplan  · 16 Jan 2018  · 636pp  · 140,406 words

ample discounts. While schools frame this discounting as high-minded do-gooding, it amounts to what economists call “price discrimination”—tailoring prices to squeeze extra profits out of richer and less flexible customers.25 Price discrimination is the standard story about why travelers pay vastly more for same-day plane tickets. List tuition does

Economic Dignity

by Gene Sperling  · 14 Sep 2020  · 667pp  · 149,811 words

lack of adequate coverage, lifetime and annual limits on how much insurers will pay for critical care, limits on families’ out-of-pocket costs, or price discrimination against those with preexisting conditions.15 Take just one example of what this means. In October 2018, I spoke at the kickoff of the Nuns

Evicted: Poverty and Profit in the American City

by Matthew Desmond  · 1 Mar 2016  · 444pp  · 138,781 words

, 2009–2011; US Department of Housing and Urban Development, Final FY 2008 Fair Market Rent Documentation System. 5. Robert Collinson and Peter Ganong, “Incidence and Price Discrimination: Evidence from Housing Vouchers,” working paper, Harvard University and the US Department of Housing and Urban Development, 2014; Eva Rosen, The Rise of the Horizontal

Uberland: How Algorithms Are Rewriting the Rules of Work

by Alex Rosenblat  · 22 Oct 2018  · 343pp  · 91,080 words

on a show of mathematical prowess: it analyzed dozens of pricing and shipping combinations, then used that information to ultimately disadvantage consumers with the results. Price discrimination, or price gouging, is hardly new, but the rise of e-commerce businesses, like Amazon, that use Big Data to personalize product recommendations raises sharper

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-commerce sites may also be used to the user’s disadvantage by manipulating the products shown (price steering) or by customizing the prices of products (price discrimination). Unfortunately, today, we lack the tools and techniques necessary to be able to detect such behavior.”8 On the Staples website, for example, consumers can

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price. The market is setting the price.”36 However, Uber appears to be charging different prices for similarly situated customers—a practice known as dynamic price discrimination, which some customers and commentators find alarming. Research by computer scientists Le Chen, Alan Mislove, and Christo Wilson measured the prices that Uber’s application

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of price tiers. Regardless of the reason, it’s clear that the new rhetoric of algorithmic neutrality has done nothing to change older practices of price discrimination. The “neutrality” of algorithms has different implications in the context of employment and algorithmic management. Surge pricing is used as a tactic to provide drivers

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, a message that effectively devalues and feminizes paid work. Issues like missing wages are attributed to technical language, such as “glitches.” The market logic of price discrimination is reframed as an innovation of artificial intelligence. Over and over again, we see how the language of technology is used rhetorically to advance the

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/article/amazon-says-it-puts-customers-first-but-its-pricing-algorithm-doesnt. 8. Aniko Hannak, Gary Soeller, David Lazer, Alan Mislove, and Christo Wilson, “Measuring Price Discrimination and Steering on E-Commerce Web Sites,” Proceedings of the 2014 Internet Measurement Conference (New York: ACM, 2014): 305–318, https://dl.acm.org/citation

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family life of drivers, 40–41, 44–45, 75 Faraz (driver), 66 fare rates, 42, 43, 87–91, 102, 108, 170. See also incentive pricing; price discrimination Farhad (driver), 71 Federal Trade Commission (FTC): author’s presentation for, 16; endorsement of Uber by, 177; litigation against Uber by, 61, 63, 77, 158

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; Trump’s travel ban on, 190–91, 192; Uber’s messaging on, 182–83, 191 incentive pricing, 46, 54, 58–59, 78, 98. See also price discrimination; referral promotions; surge manipulation income statistics, 45; differing claims of, 63–64, 226n26; FTC’s fine for misleading, 61, 63, 77; of Lyft drivers, 56

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Trump of, 191; #DeleteUber protest and, 192; driver experiences of, 43, 48, 56; driver management by, 58, 78, 158; driver statistics of, 50, 51–52; price discrimination by, 124; regulatory challenges by, 175–76, 180; scandals of, 175, 189, 201 MacLean, Nancy, 184 macroeconomic vs. microeconomic logic, 87–88, 236n19 Madrigal, Alexis

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, 180 platform capitalism, 24–25, 226n20, 228n48, 229n58. See also sharing economy Plattsburgh Taxi, 169 Plouffe, David, 181 predatory lending agreements, 44, 65–68, 194 price discrimination, 110–11, 122–24, 160–61. See also incentive pricing; surge manipulation Prim, 27 privacy rights, 160–66. See also algorithmic technology; data harvesting produsers

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Stewart, Nicholas, 42, 220 supplementary employment. See hobbyist drivers; part-time drivers surge manipulation, 98, 99 fig., 113, 128–37, 242n39. See also incentive pricing; price discrimination surveillance: of drivers, 138–39; of journalists, 13–14, 161; of passengers by dashcams, 11, 104–5, 140 Sweeney, Latanya, 112 Syria, 29 Tadesse (driver

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The Undercover Economist: Exposing Why the Rich Are Rich, the Poor Are Poor, and Why You Can Never Buy a Decent Used Car

by Tim Harford  · 15 Mar 2006  · 389pp  · 98,487 words

The Limits of the Market: The Pendulum Between Government and Market

by Paul de Grauwe and Anna Asbury  · 12 Mar 2017

Competition Demystified

by Bruce C. Greenwald  · 31 Aug 2016  · 482pp  · 125,973 words

How Markets Fail: The Logic of Economic Calamities

by John Cassidy  · 10 Nov 2009  · 545pp  · 137,789 words

More Joel on Software

by Joel Spolsky  · 25 Jun 2008  · 292pp  · 81,699 words

The Conservative Nanny State: How the Wealthy Use the Government to Stay Rich and Get Richer

by Dean Baker  · 15 Jul 2006  · 234pp  · 53,078 words

Anarchy State and Utopia

by Robert Nozick  · 15 Mar 1974  · 524pp  · 146,798 words

Cheap: The High Cost of Discount Culture

by Ellen Ruppel Shell  · 2 Jul 2009  · 387pp  · 110,820 words

Rentier Capitalism: Who Owns the Economy, and Who Pays for It?

by Brett Christophers  · 17 Nov 2020  · 614pp  · 168,545 words

Shadow Libraries: Access to Knowledge in Global Higher Education

by Joe Karaganis  · 3 May 2018  · 334pp  · 123,463 words

High-Frequency Trading

by David Easley, Marcos López de Prado and Maureen O'Hara  · 28 Sep 2013

Statistical Arbitrage: Algorithmic Trading Insights and Techniques

by Andrew Pole  · 14 Sep 2007  · 257pp  · 13,443 words

The Measure of Progress: Counting What Really Matters

by Diane Coyle  · 15 Apr 2025  · 321pp  · 112,477 words

Mongolia - Culture Smart!: The Essential Guide to Customs & Culture

by Alan Sanders  · 1 Feb 2016  · 122pp  · 37,785 words

Digital Minimalism: Choosing a Focused Life in a Noisy World

by Cal Newport  · 5 Feb 2019  · 279pp  · 71,542 words

The Curse of Bigness: Antitrust in the New Gilded Age

by Tim Wu  · 14 Jun 2018  · 128pp  · 38,847 words

When the Wolves Bite: Two Billionaires, One Company, and an Epic Wall Street Battle

by Scott Wapner  · 23 Apr 2018  · 302pp  · 80,287 words

Restarting the Future: How to Fix the Intangible Economy

by Jonathan Haskel and Stian Westlake  · 4 Apr 2022  · 338pp  · 85,566 words

Poorly Made in China: An Insider's Account of the Tactics Behind China's Production Game

by Paul Midler  · 18 Mar 2009  · 254pp  · 14,795 words

Crude Volatility: The History and the Future of Boom-Bust Oil Prices

by Robert McNally  · 17 Jan 2017  · 436pp  · 114,278 words