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The Drivers of Social Preferences: Evidence from a Nationwide Tipping Field Experiment

Author

Listed:
  • Bharat Chandar
  • Uri Gneezy
  • John A. List
  • Ian Muir

Abstract

Even though social preferences affect nearly every facet of life, there exist many open questions on the economics of social preferences in markets. We leverage a unique opportunity to generate a large data set to inform the who’s, what’s, where’s, and when’s of social preferences through the lens of a nationwide tipping field experiment on the Uber platform. Our field experiment generates data from more than 40 million trips, allowing an exploration of social preferences in the ride sharing market using big data. Combining experimental and natural variation in the data, we are able to establish tipping facts as well as provide insights into the underlying motives for tipping. Interestingly, even though tips are made privately, and without external social benefits or pressure, more than 15% of trips are tipped. Yet, nearly 60% of people never tip, and only 1% of people always tip. Overall, the demand-side explains much more of the observed tipping variation than the supply-side.

Suggested Citation

  • Bharat Chandar & Uri Gneezy & John A. List & Ian Muir, 2019. "The Drivers of Social Preferences: Evidence from a Nationwide Tipping Field Experiment," NBER Working Papers 26380, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:26380
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Nearly two-thirds of Uber riders never tip, study finds
      by ? in ScienceBlog.com on 2019-10-25 14:00:01
    2. ¿Hombres o mujeres? Descubre quiénes dan mejores propinas en Uber
      by ? in El Diario NYEl Diario NY on 2019-10-28 17:04:54

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    Cited by:

    1. Morris, Eric A. & Zhou, Ying & Brown, Anne E. & Khan, Sakib M. & Derochers, John L. & Campbell, Harry & Pratt, Angela N. & Chowdhury, Mashrur, 2020. "Are drivers cool with pool? Driver attitudes towards the shared TNC services UberPool and Lyft Shared," Transport Policy, Elsevier, vol. 94(C), pages 123-138.
    2. Dyussembayeva, Shynar & Viglia, Giampaolo & Nieto-Garcia, Marta & Mattila, Anna S., 2022. "Would you like to add a gratuity? When explicit requests hamper tipping," Journal of Business Research, Elsevier, vol. 139(C), pages 908-917.
    3. Bharat K. Chandar & Ali Hortaçsu & John A. List & Ian Muir & Jeffrey M. Wooldridge, 2019. "Design and Analysis of Cluster-Randomized Field Experiments in Panel Data Settings," NBER Working Papers 26389, National Bureau of Economic Research, Inc.
    4. Walter W. Zhang & Sanjog Misra, 2022. "Coarse Personalization," Papers 2204.05793, arXiv.org.
    5. Conlisk, Sarah, 2021. "Tipping in Crises: Evidence from Chicago Taxi Passengers during COVID-19," OSF Preprints brvhp, Center for Open Science.
    6. Damon Alexander & Christopher Boone & Michael Lynnb, 2021. "The Effects of Tip Recommendations on Customer Tipping, Satisfaction, Repatronage, and Spending," Management Science, INFORMS, vol. 67(1), pages 146-165, January.
    7. Frank, David G. & Lynn, Michael, 2020. "Shattering the Illusion of the Self-Earned Tip: The Effect of a Restaurant Magician on Co-Workers’ Tips," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 87(C).

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    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • D64 - Microeconomics - - Welfare Economics - - - Altruism; Philanthropy; Intergenerational Transfers

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