算法的陷阱：超级平台、算法垄断与场景欺骗

http://www.mcafee.cc/Papers/PDF/DynamicPriceDiscrimination.pdf。

1. Jack Nicas, “Now Prices Can Change from Minute to Minute,”Wall Street Journal, December 14, 2015, http://www.wsj.com /articles/now-pricescan-change-from-minute-to-minute-1450057990.

1. 有一个例外，当执行歧视性定价的增量成本（incrementalcost）超过了增量利润（incremental profit）时，企业就无法从价格歧视中获利。

第10章 完全价格歧视时代的到来？

1. Advertising Week XII, “Journey of Data-Driven Marketing,”Advertising Week, September 28-October 2015, http://www.advertisingweek.com /replay/#date=2015-09-30\~videoid=227\~venue=2;Suzanne Vranica, “Ad Blocking Is the Latest Hot Topic, Media Executives,” Wall Street Journal, September 27, 2015）, http://www.wsj.com/articles/ad-blocking-is-a-hot-topic-for-marketingmediaexecutives-1443259981.

1. James Surowiecki, “In Praise of Efficient Price Gouging,” MIT Technology Review（August 19, 2014）, http://www.technologyreview.com/review/529961 /in-praise-of-efficientprice-gouging/.

1. J. Turow, L. Feldman, and K. Meltzer, K. “Open to Exploitation:America’s Shoppers Online and Offiine,” Report from the Annenberg Public Policy Center of the University of Pennsylvania（June 6, 2005）,http://repository.upenn.edu/asc\_papers/35; Jennifer Valentino-Devries,Jeremy Singer-Vine, and Ashkan Soltani, “Websites Vary Prices, Deals Based on Users’ Information,” Wall Street Journal, December 24, 2012,http://www.wsj.com/articles /SB100014241278873237772045781893918 13881534.

1. Valentino-Devries et al., “Websites Vary Prices, Deals Based on Users’ Information.”

1. Valentino-Devries et al., “Websites Vary Prices, Deals Based on Users’ Information.”

1. Valentino-Devries et al., “Websites Vary Prices, Deals Based on Users’ Information.”

1. Valentino-Devries et al., “Websites Vary Prices, Deals Based on Users’ Information.”

1. Valentino-Devries et al., “Websites Vary Prices, Deals Based on Users’ Information.”

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1. Paragraph 290, House of Lords, Select Committee on European Union, “Online Platforms and the Digital Single Market,” April 20, 2016,10th Report of Session 2015-16, http://www.publications.parliament.uk/pa/ld201516/ldselect/ldeucom/129/129

1. Emily Steel and Julia Angwin, “On the Web’s Cutting Edge,Anonymity in Name Only,” Wall Street Journal, August 4, 2010, http://www.wsj.com /articles/SB10001424052748703294904575385532109190198.

1. Valentino-Devries et al., “Websites Vary Prices, Deals Based on Users’ Information.”

1. Valentino-Devries et al., “Websites Vary Prices, Deals Based on Users’ Information.”

1. Valentino-Devries et al., “Websites Vary Prices, Deals Based on Users’ Information.”

1. Consumer Federation of America, “Report Finds Auto Insurers Charge Higher Premiums in African American Zip Codes,” CFAnews Update（November 24, 2015）, http://consumerfed.org/cfanewsupdate-11242015/.

1. Sal Thomas, “Does Dynamic Pricing Risk Turning Personalisation into Discrimination?” Marketing Magazine, October 22, 2014, http://www.marketingmagazine.co.uk/article/1317995/does-dynamicpricingrisk-turning-personalisation-discrimination.

1. Coupons.com Inc., Form 10-K for the Fiscal Year Ended December

31,2014（2015）, 3, http://www.sec.gov/Archives/edgar/

data/1115128/000156459015001837/coup-10k\_20141231.htm. In 2015,the company changed its name to Quotient Technology Inc.; Coupons.com Inc., “Coupons .com Incorporated Changes Corporate Name to Quotient”（October 6, 2015）, http://investors.coupons.com/investors/pressreleases/press-releases-details/2015/Couponscom-IncorporatedChanges-Corporate-Name-to-Quotient/ default . aspx.

1. Coupons.com Inc., “Coupons.com Incorporated Changes Corporate Name to Quotient.”

1. Coupons.com Inc., Form 10-K for the Fiscal Year Ended December 31, 2014, 5.

1. Coupons.com Inc., Form 10-K for the Fiscal Year Ended December 31, 2014, 5.

1. Coupons.com Inc., Form 10-K for the Fiscal Year Ended December，4。

1. Executive Office of the President, Big Data and Differential Pricing（Washington, DC: Executive Office of the President）, February 2015, p.12,

https://www.whitehouse.gov/sites/default/files/whitehouse\_files/docs/Big\_Da文中称，“会员制度是最早应用大数据手段开展个性化定价的方式。顾客加入某项会员活动后，他们通常会提供一些个人信息给商家，同时也会对商家追踪消费记录的行为表示认可。反过来，顾客也会因此得到一些福利，比如航空公司优质会员的免费升舱、零售商店的会员特价等。除此以外，一些零售商还会与专业的信息科技公司合作，针对不同消费者提供定制优惠券，它们可能被印在了收银条的背面，或是在推销中被特别赠予。专长于此的企业声称，消费者使用定制化优惠券的概率要远远高于那些随机派发的优惠券（25:1）”。

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1. Charles Duhigg, “How Companies Learn Your Secrets,” New York Times Sunday Magazine, February 16, 2012, http://www.nytimes.com/2012/02/19 /magazine/shopping-habits.html? pagewanted=all&\_r=0.

1. Charles Duhigg, “How Companies Learn Your Secrets,” New York Times Sunday Magazine, February 16, 2012, http://www.nytimes.com/2012/02/19 /magazine/shopping-habits.html? pagewanted=all&\_r=0.

1. Charles Duhigg, “How Companies Learn Your Secrets,” New York Times Sunday Magazine, February 16, 2012, http://www.nytimes.com/2012/02/19 /magazine/shopping-habits.html? pagewanted=all&\_r=0.

1. Charles Duhigg, “How Companies Learn Your Secrets,” New York Times Sunday Magazine, February 16, 2012, http://www.nytimes.com/2012/02/19 /magazine/shopping-habits.html? pagewanted=all&\_r=0.

1. Target, Privacy Policy, October 1, 2015, http://www.target.com/spot/privacy -policy#section1.

1. Target, Privacy Policy, October 1, 2015, http://www.target.com/spot/privacy -policy#section1.

1. Target, Privacy Policy, October 1, 2015, http://www.target.com/spot/privacy -policy#section1.

1. Target, Privacy Policy, October 1, 2015, http://www.target.com/spot/privacy -policy#section1.

1. Target, Privacy Policy, October 1, 2015, http://www.target.com/spot/privacy -policy#section1.

1. Target, Privacy Policy, October 1, 2015, http://www.target.com/spot/privacy -policy#section1.

1. Duhigg, “How Companies Learn Your Secrets.”

1. Duhigg, “How Companies Learn Your Secrets.”

1. Duhigg, “How Companies Learn Your Secrets.”

1. Duhigg, “How Companies Learn Your Secrets.”

1. Brad Howarth, “How Tesco’s Loyalty Card Transformed Customer Data Tracking,” CMO（May 21, 2015）, http://www.cmo.com.au/article/575497/how-tesco-loyalty-card- transformed -customer- datatracking /; Krish Swarmy, “Analyzing Tesco — The Analytics behind a Top-Notch Loyalty Program,” Big Data Analytics（August 21, 2011）,http://stat-exchange.blogspot.com/2011/08 /analyzing-tesco-analyticsbehind-top.html.

1. McKinsey & Company, Making Loyalty Pay: Lessons from the innovators（McKinsey & Company, July 2013）.

1. “The Card Up Their Sleeve,” The Guardian, July 19, 2003,http://www .theguardian.com/lifeandstyle/2003/jul/19/shopping.features.

1. Alex Chisholm（CMA chief executive）, Why “Sleepers”Can’t Always Be Left to “Sleep,” CCRP 2016 Competition Policy Roundtable（London: Competition Markets Authority, January 25,2016）, https://www.gov.uk/government/speeches/alex-chisholm-onconsumerengagement-in-a-digital-world.

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1. Coupons.com Inc., “Coupons.com Incorporated Changes Corporate Name to Quotient.”

1. 有关移动用户的行为追踪的内容，详见：Chris Cooper,“Nordstrom Stores Tracking Customers’ Cell Phones,” Stop Cell Phone Tracking（February 11, 2013）, http://www.stopcellphonetracking.com/nordstrom-tracking-customers-cellphones/; Chris Cooper, “This Is How Retail Stores Track Your Smartphone,” Stop Cell Phone Tracking（June 3,2013）, http://www.stopcellphonetracking.com/this-is-how-retail-stores-track-yoursmartphone-video/。有关个性化店内定位追踪技术的介绍，详见：Verne Kopytoff, “Stores Sniff Out Smartphones to Follow Shoppers,” MIT Technology Review（November 12, 2013）, http://www.technology review.com/news/520811/stores-sniff-out-smartphones-to-followshoppers/。

1. Clare McDonald, “Almost 30% of Retailers Use Facial Recognition Technology to Track Consumers in Store,” ComputerWeekly.com（September 15, 2015）, http://wwwcomputerweekly.com/news/4500253499/Almost30-of-retailersuse-facial-recognition-technology-to-track-consumers-instore; Jimmy Rose, “How Facial Recognition Will Change Shopping in Stores,” Extreme Tech（June 23, 2015）, http://www.extremetech.com/ mobile/208815-howfacial-recognition-will-change-shopping-in-stores;James Hercher, “Shopper Behavior Begins In-Store — But Brick-andMortars Need Tech to Harness It,” Ad Exchanger（July 8, 2015）, http://adexchanger.com/data exchanges/shopper-behavior-begins-in-store-butbrick-and-mortars-need-techto-harness-it/（文中提到，“值得注意的是，许多新开业的零售店都格外 依赖这种面部识别技术。一家名为AdMobilize的公司刚刚在近期获得 160万美元的投资，而该公司的主业是在实体店内安装具备面部识别技 术的摄像头，以实现收集消费者在店内活动的数据”）; Heather Fletcher, “Facial Recognition:Ads Target Consumers for You,” Target Marketing（October 5, 2015）,http://www.targetmarketingmag.com/article/facial-recognition-adstargetconsumers / ［“据‘透明度市场研究’（Transparency Market Research）的预测，到了2020年，全球面部识别技术市场的体量将达到 27亿美元”］。

1. Federal Trade Commission, Spring Privacy Series: Mobile Device Tracking,（February 19, 2014）, https://www.ftc.gov/newsevents/eventscalendar/2014/02/spring-privacy-series-mobile-device-tracking.

1. In re Nomi Technologies, Inc., FTC No. 132 3251（April 23,

2015）,https://www.ftc.gov/system/files/documents/cases/150423nomicmpt.p

1. In re Nomi Technologies, Inc., FTC No. 132 3251（April 23,

2015）,https://www.ftc.gov/system/files/documents/cases/150423nomicmpt.p

1. Federal Trade Commission, Statement of Chairwoman Ramirez,Commissioner Brill, and Commissioner McSweeny in the Matter of Nomi Technologies, Inc.（April 23, 2015）, https://www.ftc.gov/system/files/documents/public\_statements/638351/15042 pdf.

1. Federal Trade Commission, Data Brokers: A Call for Transparency and Accountability（May 2014）, ii-iii, https://www.ftc.gov/system/files/documents /reports/data-brokers-calltransparency-accountability-reportfederal-trade-commission-may-

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39（1987）: 84-97.

1. David Streitfeld, “Some Online Bargains May Only Look Like One,” New York Times, April 13, 2016, http://www.nytimes.com/2016/04/14/technology /some-online-bargains-mayonly-looklike-one.html?smprod=nytcore-iphone&smid=nytcore- iphoneshare&\_ r =0.

1. David Streitfeld, “Some Online Bargains May Only Look Like One,” New York Times, April 13, 2016, http://www.nytimes.com/2016/04/14/technology /some-online-bargains-mayonly-looklike-one.html?smprod=nytcore-iphone&smid=nytcore- iphoneshare&\_ r =0.

1. 锚定效应是指当人们需要对某个事件做定量估测时，会将某些特定数值作为起始值，起始值像锚一样制约着估测值。在做决策的时候，会不自觉地给予最初获得的信息过多的重视。作为一种心理现象，锚定效应普遍存在于生活的方方面面，第一印象和先入为主是其在社会生活中的表现形式。

1. European Data Protection Supervisor, Mobile Health: Reconciling Technological Innovation with Data Protection, Opinion 1/2015（May 21, 2015）, para.29, https://secure.edps.europa.eu/EDPSWEB/webdav/site/mySite/shared/Docume 05-21\_Mhealth\_EN.pdf.

第11章 近乎完美的行为歧视

1. 一篇商业文章的作者提出，以下几大情绪波动交织在一起影响了消费者做出购买决定：

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