Advertisement

The Dark Side of Big Data: Personal Privacy, Data Security, and Price Discrimination

  • Yang LiuEmail author
  • Connor Greene
Chapter

Abstract

New information technologies enable big data collection, analysis, and forecasting. Based on big data, firms now have the capability to manipulate consumers, deliver personalized advertisements, and apply price discrimination policies. On the other hand, concerns about personal privacy and data security arise with big data. This chapter discusses concerns regarding the dark side of big data through observations of results for consumers led by firms sharing and using these data.

Keywords

Big data Privacy Security Safety Malpractice Transparency 

References

  1. Big Data and Differential Pricing. (2015). The White House President Barack Obama. Retrieved from https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/docs/Big_Data_Report_Nonembargo_v2.pdf
  2. Calo, R. (2014). Digital market manipulation. George Washington Law Review, 82(4), 995–1051. 57p. Database: Business Source Ultimate.Google Scholar
  3. Chen, Z., Choe, C., & Matsushima, N. (2018). Competitive personalized pricing. ISER Discussion Paper. Retrieved from https://www.monash.edu/business/economics/research/publications/publications2/0218Copetitivechenchoe.pdf
  4. Citron, D. K., & Pasquale, F. A. (2014). The scored society: Due process for automated predictions. Washington Law Review, 89(1), 33. Washington Law Review Association.Google Scholar
  5. Duhigg, C. (2012). How companies learn your secrets. New York Times Magazine, February 16. Retrieved from https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html
  6. Furman, J., & Simcoe, T. (2015). The economics of big data and differential pricing. The White House President Barack Obama. Retrieved from https://obamawhitehouse.archives.gov/blog/2015/02/06/economics-big-data-and-differential-pricing
  7. Hacker, P., & Petkova, B. (2017). Reining in the big promise of big data: Transparency, inequality, and new regulatory frontiers. Northwestern Journal of Technology & Intellectual Property, 15(1), 1–42. Northwestern University.Google Scholar
  8. Kamenica, E., Mullainathan, S., & Thaler, R. (2011). Helping consumers know themselves. The American Economic Review, 101(3), 417–422. American Economic Association.CrossRefGoogle Scholar
  9. Keller, J. (2013). iPhone users pay higher cell phone bills than any other smartphone user. iMore. Retrieved from https://www.imore.com/iphone-users-biggest-cash-cows-carriers
  10. Machlup, F. (1955). Characteristics and types of price discrimination. NBER chapters. In Business concentration and price policy (pp. 397–440). National Bureau of Economic Research, Inc.Google Scholar
  11. Michael, R., & Mohammed, R. (2015). Who’s paying more to tour these United States? Price differences in international travel bookings. Technology Science.Google Scholar
  12. Newcomer, E. (2017, May 19). Uber starts charging what it thinks you’re willing to pay. Bloomberg. Retrieved from https://www.bloomberg.com/news/articles/2017-05-19/uber-s-future-may-rely-on-predicting-how-much-you-re-willing-to-pay
  13. Paczkowski, J. (2013). iPhone users rack up the highest carrier bills. All Things D. Retrieved from http://allthingsd.com/20130130/wireless_bills_by_os_android_ios/
  14. Payton, T., Schmidt, H. A., & Claypoole, T. (2014). Privacy in the age of big data: Recognizing threats, defending your rights, and protecting your family. Lanham, MD: Rowman & Littlefield Publishers.Google Scholar
  15. Podesta, J., Pritzker, P., Moniz, E. J., Holdren, J., & Zients, J. (2014). Big data: Seizing opportunities, preserving values. Executive Office of the President. Retrieved from https://obamawhitehouse.archives.gov/sites/default/files/docs/20150204_Big_Data_Seizing_Opportunities_Preserving_Values_Memo.pdf
  16. The Economist. (2014, September 11). Getting to know you. Retrieved from https://www.economist.com/special-report/2014/09/11/getting-to-know-you
  17. Thomas, R. (2012). Non-risk price discrimination in insurance: Market outcomes and public policy. The Geneva Papers on Risk and Insurance. Issues and Practice, 37(1), 27–46. Palgrave Macmillan.CrossRefGoogle Scholar
  18. Townley, C., Morrison, E., & Yeung, K. (2017). Big data and personalized price discrimination in EU competition law. Yearbook of European Law, 36(1), 683–748. 66p. Publisher: Oxford University Press/USA.CrossRefGoogle Scholar
  19. Wu, Y. Q. (2018). 用苹果手机打车、看电影、买机票比安卓贵?记者亲测被大数据“杀熟”. Shen Zhen Shang Bao. Retrieved from http://www.sohu.com/a/226569266_355791

Copyright information

© The Author(s) 2020

Authors and Affiliations

  1. 1.Fitchburg State UniversityFitchburgUSA
  2. 2.Southern New Hampshire UniversityHooksettUSA

Personalised recommendations