The Interplay of Earnings, Ratings, and Penalties on Sharing Platforms: An Empirical Investigation

32 Pages Posted: 18 Jun 2020 Last revised: 6 Sep 2022

See all articles by Yuqian Xu

Yuqian Xu

University of North Carolina (UNC) at Chapel Hill - Kenan-Flagler Business School

Baile Lu

National University of Defense Technology - College of Systems Engineering

Anindya Ghose

New York University (NYU) - Leonard N. Stern School of Business

Hongyan Dai

Central University of Finance and Economics

Weihua Zhou

Zhejiang University

Date Written: May 24, 2020

Abstract

On-demand delivery through sharing platforms represents a rapidly expanding segment of the global workforce. The emergence of sharing platforms enables gig workers to choose when and where to work, allowing them to do so in a flexible manner. However, such flexibility brings notorious challenges to platforms in managing the gig workforce. Thus, understanding the incentive and behavioral issues of gig workers in this new business model is inherently meaningful. This paper investigates how the incentive mechanisms of sharing platforms—earnings, ratings, and penalties—affect the working decisions of gig workers and their nuanced relationships. To achieve this goal, we utilize data from one leading on-demand delivery platform with over 50 million active consumers in China and implement a two-stage Heckman model with instrumental variables to estimate the impact of earnings, ratings, and penalties. We first show that better ratings motivate gig workers to work more. However, interestingly, when ratings are employed together with earnings, the two positive effects of ratings and earnings can be substitutes for each other. Second, we reveal that higher past penalties discourage workers from working more, whereas, interestingly, workers with higher past penalties tend to be more sensitive toward an increase in earnings.
Finally, we conduct follow-up surveys to understand the underlying mechanisms of the observed moderating effects from both psychological and economic perspectives. The ultimate goal of this work is to provide managerial implications to help platform managers understand how earnings, ratings, and penalties work together to affect gig workers' working decisions and how to manage high- and low-quality workers.

Keywords: incentives, behavior, delivery, sharing platform, gig worker, rating, penalty, earning

Suggested Citation

Xu, Yuqian and Lu, Baile and Ghose, Anindya and Dai, Hongyan and Zhou, Weihua, The Interplay of Earnings, Ratings, and Penalties on Sharing Platforms: An Empirical Investigation (May 24, 2020). NYU Stern School of Business, Available at SSRN: https://ssrn.com/abstract=3609132 or http://dx.doi.org/10.2139/ssrn.3609132

Yuqian Xu (Contact Author)

University of North Carolina (UNC) at Chapel Hill - Kenan-Flagler Business School ( email )

McColl Building
Chapel Hill, NC 27599-3490
United States

Baile Lu

National University of Defense Technology - College of Systems Engineering ( email )

Hunan, 410073
China

Anindya Ghose

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

Hongyan Dai

Central University of Finance and Economics ( email )

No 39. Xueyuan South Road
Haidai District
Beijing, 100081
China

Weihua Zhou

Zhejiang University ( email )

38 Zheda Road
Hangzhou, Zhejiang 310058
China

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