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You get what you give: theory and evidence of reciprocity in the sharing economy

Author

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  • Davide Proserpio

    (University of Southern California)

  • Wendy Xu

    (Boston University)

  • Georgios Zervas

    (Boston University)

Abstract

We develop an analytical framework of peer interaction in the sharing economy that incorporates reciprocity, the tendency to increase (decrease) effort in response to others’ increased (decreased) effort. In our model, buyers (sellers) can induce sellers (buyers) to exert more effort by behaving well themselves. We demonstrate that this joint increased effort can improve the utility of both parties and influence the market equilibrium. We also show that bilateral reputation systems, which allow both buyers and sellers to review each other, are more responsive to reciprocity than unilateral reputation systems. By rewarding reciprocal behavior, bilateral reputation systems generate trust among strangers and informally regulate their behavior. We test the predictions of our model using data from Airbnb, a popular peer-to-peer accommodation platform. We show that Airbnb hosts that are more reciprocal receive higher ratings and that higher rated hosts can increase their prices. Therefore, reciprocity affects equilibrium prices on Airbnb through its impact on ratings, as predicted by our analytical framework.

Suggested Citation

  • Davide Proserpio & Wendy Xu & Georgios Zervas, 2018. "You get what you give: theory and evidence of reciprocity in the sharing economy," Quantitative Marketing and Economics (QME), Springer, vol. 16(4), pages 371-407, December.
  • Handle: RePEc:kap:qmktec:v:16:y:2018:i:4:d:10.1007_s11129-018-9201-9
    DOI: 10.1007/s11129-018-9201-9
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    References listed on IDEAS

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    Cited by:

    1. Zheng, Zuolong & Li, Ziying & Zhang, Xuwen & Liang, Sai & Law, Rob & Lei, Jiasu, 2023. "Substitution or complementary effects between hosts and neighbors’ information disclosure: Evidence from Airbnb," Journal of Business Research, Elsevier, vol. 161(C).
    2. Rana S. Roshdy & Zhou Erhua, 2020. "Perceived value of ride-hailing providers:The role of algorithmic management, customer dysfunctional behavior and perceived injustice," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 9(7), pages 53-65, December.
    3. Starr, Richard G. & Zhu, Andrew Q. & Frethey-Bentham, Catherine & Brodie, Roderick J., 2020. "Peer-to-peer interactions in the sharing economy: Exploring the role of reciprocity within a Chinese social network," Australasian marketing journal, Elsevier, vol. 28(3), pages 67-80.
    4. Yunke Mai & Bin Hu & Saša Pekeč, 2023. "Courteous or Crude? Managing User Conduct to Improve On-Demand Service Platform Performance," Management Science, INFORMS, vol. 69(2), pages 996-1016, February.
    5. Karl Taeuscher & Eric Yanfei Zhao & Michael Lounsbury, 2022. "Categories and narratives as sources of distinctiveness: Cultural entrepreneurship within and across categories," Strategic Management Journal, Wiley Blackwell, vol. 43(10), pages 2101-2134, October.
    6. Sainaghi, Ruggero & Chica-Olmo, Jorge, 2022. "The effects of location before and during COVID-19," Annals of Tourism Research, Elsevier, vol. 96(C).
    7. Georgios Zervas & Davide Proserpio & John W. Byers, 2021. "A first look at online reputation on Airbnb, where every stay is above average," Marketing Letters, Springer, vol. 32(1), pages 1-16, March.
    8. Michelangelo Rossi, 2019. "How Does Competition Affect Reputation Concerns? Theory and Evidence from Airbnb," CESifo Working Paper Series 7972, CESifo.
    9. Xiang, Diandian & Jiao, Guanzhe & Sun, Bin & Peng, Chenming & Ran, Yaxuan, 2022. "Prosumer-to-customer exchange in the sharing economy: Evidence from the P2P accommodation context," Journal of Business Research, Elsevier, vol. 145(C), pages 426-441.
    10. Feng, Nan & Xu, Nan & Feng, Haiyang & Li, Minqiang, 2022. "Turn on instant booking or not? Decisions of rival hosts," Annals of Tourism Research, Elsevier, vol. 96(C).
    11. Lim, Weng Marc, 2020. "The sharing economy: A marketing perspective," Australasian marketing journal, Elsevier, vol. 28(3), pages 4-13.
    12. Dai Yao & Chuang Tang & Junhong Chu, 2023. "A Dynamic Model of Owner Acceptance in Peer-to-Peer Sharing Markets," Marketing Science, INFORMS, vol. 42(1), pages 166-188, January.
    13. Arslan Aziz & Hui Li & Rahul Telang, 2023. "The Consequences of Rating Inflation on Platforms: Evidence from a Quasi-Experiment," Information Systems Research, INFORMS, vol. 34(2), pages 590-608, June.
    14. Syed Tariq Anwar, 2023. "The sharing economy and collaborative consumption: Strategic issues and global entrepreneurial opportunities," Journal of International Entrepreneurship, Springer, vol. 21(1), pages 60-88, March.
    15. Andrey Fradkin & Elena Grewal & David Holtz, 2021. "Reciprocity and Unveiling in Two-Sided Reputation Systems: Evidence from an Experiment on Airbnb," Marketing Science, INFORMS, vol. 40(6), pages 1013-1029, November.
    16. Kyle Barron & Edward Kung & Davide Proserpio, 2021. "The Effect of Home-Sharing on House Prices and Rents: Evidence from Airbnb," Marketing Science, INFORMS, vol. 40(1), pages 23-47, January.
    17. Gössling, Stefan & Larson, Mia & Pumputis, Aurimas, 2021. "Mutual surveillance on Airbnb," Annals of Tourism Research, Elsevier, vol. 91(C).
    18. Meijian Yang & Enjun Xia, 2021. "A Systematic Literature Review on Pricing Strategies in the Sharing Economy," Sustainability, MDPI, vol. 13(17), pages 1-28, August.
    19. Moriuchi, Emi, 2023. "Encouraging Respect?: Understanding consumers’ perspective on the two-way evaluation system in a sharing economy," Journal of Business Research, Elsevier, vol. 163(C).

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    More about this item

    Keywords

    Peer-to-peer markets; Reputations systems; Reciprocity; Airbnb;
    All these keywords.

    JEL classification:

    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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