Service Quality on Online Platforms: Empirical Evidence about Driving Quality at Uber

Susan Athey, Juan Castillo and Bharat Chandar
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Bharat Chandar: Stanford U

Research Papers from Stanford University, Graduate School of Business

Abstract: The rise of marketplaces for goods and services has led to changes in the mechanisms used to ensure high quality. We analyze this phenomenon in the Uber market, where the system of pre-screening that prevailed in the taxi industry has been diminished in favor of (automated) quality measurement, reviews, and incentives. This shift allows greater flexibility in the workforce but its net effect on quality is unclear. Using telematics data as an objective quality outcome, we show that UberX drivers provide better quality than UberTaxi drivers, controlling for all observables of the ride. We then explore whether this difference is driven by incentives, nudges, and information. We show that riders’ preferences shape driving behavior. We also find that drivers respond to both user preferences and nudges, such as notifications when ratings fall below a threshold. Finally, we show that informing drivers about their past behavior increases quality, especially for low-performing drivers.

JEL-codes: D83 L91 O33 (search for similar items in EconPapers)
Date: 2024-09
New Economics Papers: this item is included in nep-mac, nep-nud, nep-pay, nep-reg and nep-tre
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Working Paper: Service Quality on Online Platforms: Empirical Evidence about Driving Quality at Uber (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:ecl:stabus:3894

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