Advertisement

Crowd-Based Markets: Technical Progress, Civil and Social Regression

  • Lauren RhueEmail author
Chapter

Abstract

Crowd-based marketplaces facilitate peer-to-peer transactions across a variety of industries such as ride-sharing and crowdfunding. Because of their business model, crowd-based markets encourage users to share information as a means to promote trust and ultimately fuel transactions. To that end, crowd-based markets create technical designs to encourage transparency and those technical elements also introduce racial identity into the platform. This chapter discusses racial disparities in crowd-based markets and describes the economic implications of these disparities. Although crowd-based platforms can enact changes to lower racial bias, such as automated decision-making, the platforms’ economic incentives and values contradict with enforcement of self-regulatory anti-discrimination measures. As the global economy shifts toward more crowd-based solutions, the influence of crowd-based markets extends beyond their user base. Society should act to promote anti-discrimination protections in these crowd-based markets, and there is a call to action at the end of this chapter for governments, platforms, and citizens. Plus, this chapter contributes to the growing call to examine the values embedded in technology instead of viewing technology as “values neutral.”

Keywords

Crowd-based markets Crowdfunding Sharing economy Racial identifiers Racial bias Facial recognition Automation Crowd-based platforms Crowdsourcing Race 

Further Reading

  1. O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. New York, NY: Crown Publishing Group.Google Scholar
  2. Ravenelle, A. (2016, March 13). Belong anywhere? How Airbnb is dismantling generations of civil rights in the name of progress. Available at SSRN https://ssrn.com/abstract=2838219 or http://dx.doi.org/10.2139/ssrn.2838219.
  3. Rhue, L. (2018). An overview of crowd-based markets and racial discrimination. AMCIS 2018 Proceedings, New Orleans. Available at https://aisel.aisnet.org/amcis2018/SocialInclusion/Presentations/1/.
  4. Rhue, L., & Clark, J. (2018). The consequences of authenticity: Quantifying racial signals and their effects on crowdfunding success (Working Paper). Available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2837042.

References

  1. Acquisti, A., & Fong, C. (2016). An experiment in hiring discrimination via online social networks. Available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2031979.
  2. Ayres, I., Banaji, M., & Jolls, C. (2015). Race effects on eBay. The RAND Journal of Economics, 46(4), 891–917.CrossRefGoogle Scholar
  3. Banks, P. (2019). Cultural justice and collecting: Challenging the underrecognition of African American artists. In G. D. Johnson, K. D. Thomas, A. K. Harrison, & S. G. Grier (Eds.), Race in the marketplace: Crossing critical boundaries (pp. 213–226). New York: Palgrave Macmillan.Google Scholar
  4. Barocas, S., & Levy, K. (2016). What customer data collection could mean for workers. Harvard Business Review. Available at https://hbr.org/2016/08/the-unintended-consequence-of-customer-data-collection.
  5. Bertrand, M., & Mullainathan, S. (2004). Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. American Economic Review, 94(4), 991–1013.Google Scholar
  6. Booth, A. L., Leigh, A., & Varganova, E. (2012). Does ethnic discrimination vary across minority groups? Evidence from a field experiment. Oxford Bulletin of Economics and Statistics, 74(4), 547–573.Google Scholar
  7. Boudreau, M. C., & Robey, D. (2005, January–February). Enacting integrated information technology: A human agency perspective. Organization Science, 16(1), 3–18.Google Scholar
  8. Buolamwini, J. and Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. In Conference on Fairness, Accountability and Transparency.Google Scholar
  9. Crawford, K. (2013). The hidden biases in big data. Harvard Business Review. Available at https://hbr.org/2013/04/the-hidden-biases-in-big-data.
  10. Dahlin, L., Clark, J., & Rhue, L. (2018). Crowdfunding community formation: Fundraiser race and gender homophily (Working Paper).Google Scholar
  11. Edelman, B. G., & Luca, M. (2014). Digital discrimination: The case of Airbnb.com (Harvard Business School NOM Unit Working Paper [14-054]).
  12. Edelman, B., Luca, M., & Svirsky, D. (2017). Racial discrimination in the sharing economy: Evidence from a field experiment. American Economic Journal: Applied Economics, 9(2), 1–22.Google Scholar
  13. Ert, E., Fleischer, A., & Magen, N. (2016). Trust and reputation in the sharing economy: The role of personal photos in Airbnb. Tourism Management, 55, 62–73.CrossRefGoogle Scholar
  14. Friedman, B., Kahn, P. H., Jr., & Borning, A. (2006). Value sensitive design and information systems. In P. Zhang & D. Galletta (Eds.), Human–computer interaction in management information systems: Foundations (pp. 348–372). Armonk, NY and London, UK: M.E. Sharpe.Google Scholar
  15. Gant, A. C. (2016). Holiday rentals: The new gentrification battlefront. Sociological Research Online, 21(3), 1–9.Google Scholar
  16. Hadfield, G. (2017, November 22). World needs 21st century regulation to police gig economy. The Financial Times. Available at https://www.ft.com/content/71a2dea6-a505-11e7-8d56-98a09be71849.
  17. Hagiu, A., & Wright, J. (2015). Multi-sided platforms. International Journal of Industrial Organization, 43, 162–174.CrossRefGoogle Scholar
  18. Jamerson, T. (2019). Race, markets, and digital technologies: Historical and conceptual frameworks. In G. D. Johnson, K. D. Thomas, A. K. Harrison, & S. G. Grier (Eds.), Race in the marketplace: Crossing critical boundaries (pp. 39–54). New York: Palgrave Macmillan.Google Scholar
  19. Laouénan, M., & Rathelot. R. (2017). Ethnic discrimination on an online marketplace of vacation rental. https://hal.archives-ouvertes.fr/hal-01514713/document.
  20. Lee, D. (2016). How Airbnb short-term rentals exacerbate Los Angeles’s affordable housing crisis: Analysis and policy recommendations. Harvard Law and Policy Review, 10, 229.Google Scholar
  21. Murphy, L. W. (2016, September 8). Airbnb’s work to fight discrimination and build inclusion. A Report Submitted to Airbnb. Available at https://blog.atairbnb.com/wp-content/uploads/2016/09/REPORT_Airbnbs-Work-to-Fight-Discrimination-and-Build-Inclusion.pdf?3c10be.
  22. O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. New York, NY: Crown Publishing Group.Google Scholar
  23. Penman, M., Vedantam, V., & Nesterak, M. (2016). #AirbnbWhileBlack: How hidden bias shapes the sharing economy. NPR. Available at https://www.npr.org/2016/04/26/475623339/-airbnbwhileblack-how-hidden-bias-shapes-the-sharing-economy.
  24. Perry, V. (2019). A loan at last? Race and racism in mortgage lending. In G. D. Johnson, K. D. Thomas, A. K. Harrison, & S. G. Grier (Eds.), Race in the marketplace: Crossing critical boundaries (pp. 173–192). New York: Palgrave Macmillan.Google Scholar
  25. Pope, D. G., & Sydnor, J. R. (2011). What’s in a picture? Evidence of discrimination from Prosper.com. Journal of Human Resources, 46(1), 53–92.CrossRefGoogle Scholar
  26. Ravenelle, A. (2016, March 13). Belong anywhere? How Airbnb is dismantling generations of civil rights in the name of progress. Available at SSRN https://ssrn.com/abstract=2838219 or http://dx.doi.org/10.2139/ssrn.2838219.
  27. Reinhold, S., & Dolnicar, S. (2017). Chapter 2—The sharing economy. In S. Dolnicar (Ed.), Peer-to-peer accommodation networks: Pushing the boundaries (pp. 15–26). Oxford: Goodfellow Publishers. https://dx.doi.org/10.23912/9781911396512–3600.
  28. Rhue, L., & Clark, J. (2018). The consequences of authenticity: Quantifying racial signals and their effects on crowdfunding success (Working Paper). Available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2837042.
  29. Rosa-Salas, M. (2019). Making the mass white: How racial segregation shaped consumer segmentation. In G. D. Johnson, K. D. Thomas, A. K. Harrison, & S. G. Grier (Eds.), Race in the marketplace: Crossing critical boundaries (pp. 21–38). New York: Palgrave Macmillan.Google Scholar
  30. Singer, N. (2018, April 8). A tough task for Facebook: European-type privacy for all. New York Times. Available at https://www.nytimes.com/2018/04/08/technology/a-tough-task-for-facebook-european-type-privacy-for-all.html.
  31. Smith, S. S. (2010). Race and trust. Annual Review of Sociology, 36, 453–475.CrossRefGoogle Scholar
  32. Stanoevska-Slabeva, K., Lenz-Kesekamp, V., & Suter, V. (2017). Platforms and the sharing economy: An analysis EU H2020 Research Project Ps2Share—Participation, privacy, and power in the sharing economy, 2017. Available at https://www.bi.edu/globalassets/forskning/h2020/ps2share_platform-analysis-paper_final.pdf.
  33. Sundararajan, A. (2016). The sharing economy: The end of employment and the rise of crowd-based capitalism. Cambridge: MIT Press.Google Scholar
  34. Sundararajan, A. (2018). Crowd-based capitalism, digital automation, and the future of work. University of Chicago Legal Forum, 2017 (Article 19). Available at https://chicagounbound.uchicago.edu/uclf/vol2017/iss1/19.
  35. Tabuchi, H. (2018, June 19). How the Koch brothers are killing public transit projects around the country. New York Times. Available at https://www.nytimes.com/2018/06/19/climate/koch-brothers-public-transit.html.
  36. Tjaden, J. D., Schwemmer, C., & Khadjavi, M. (2017). Ride with me: Ethnic discrimination in social markets (Kiel Working Paper No. 2087). Available at https://www.econstor.eu/bitstream/10419/167311/1/89502831X.pdf.
  37. Tomboc, G. (2013). The lemons problem in crowdfunding. The John Marshall Journal of Information Technology & Privacy Law, 30(2), 253 (2013–2014).Google Scholar
  38. Welch, C. (2017, April 28). Some Airbnb hosts will face racial discrimination tests in California. The Verge. Available at https://www.theverge.com/2017/4/28/15475982/airbnb-discrimination-tests-california.
  39. Ye, T., Pierce, C., Alahmad, R., & Robert, L. P. (2017). Race and rating on sharing economy platforms: The effect of race similarity and reputation on trust and booking intention in Airbnb. Proceedings of the 38th International Conference on Information Systems (ICIS 2017) in Seoul, Korea. Available at http://aisel.aisnet.org/icis2017/Peer-to-Peer/Presentations/4/.
  40. Younkin, P., & Kuppuswamy, V. (2017). The colorblind crowd? Founder race and performance in crowdfunding. Management Science, 64(7), 3269–3287.Google Scholar
  41. Younkin, P., & Kuppuswamy, V. (2019). Discounted: The effect of founder race on the price of new products. Journal of Business Venturing, 34(2), 389–412.Google Scholar

Copyright information

© The Author(s) 2019

Authors and Affiliations

  1. 1.School of BusinessWake Forest UniversityWinston-SalemUSA

Personalised recommendations