Mergers Between On-Demand Service Platforms: The Impact on Consumer Surplus and Labor Welfare

Posted: 11 Oct 2018

See all articles by Xiaogang Lin

Xiaogang Lin

South China University of Technology

Tao Lu

Erasmus University Rotterdam (EUR) - Rotterdam School of Management (RSM)

Xin Wang

Hong Kong University of Science & Technology (HKUST) - Dept. of Industrial Engineering and Decision Analytics

Date Written: September 18, 2018

Abstract

This paper studies the impact of mergers between on-demand service platforms on consumer surplus and labor welfare. We analyze a game-theoretical model in which customers choose between platforms based on prices and expected waiting times, and agents base decisions about which platform to work for on wages and the probability of getting jobs. Driven by these two features, we find that mergers between on-demand service platforms have several welfare implications that have not been documented by previous research. While a merger reduces competition, we show that customers may benefit from a merger due to the risk-pooling effect and reduced waiting times; moreover, if customers are very sensitive to delay, this benefit can spill over to the labor force via cross-side network externalities. We further establish that a win-win-win outcome, in which merging firms, customers and agents are all better off, can always be achieved if the merged platform commits to certain ratios between prices and wages. This implies that antitrust agencies can enforce restrictions on the payout ratios to protect both consumers and agents. Finally, we illustrate our main insights by implementing our model in numerical experiments calibrated using real data from large on-demand ride-sharing platforms.

Keywords: Mergers and Acquisitions, On-Demand Service Platform, Consumer Surplus, Labor Welfare, Sharing Economy

Suggested Citation

Lin, Xiaogang and Lu, Tao and Wang, Xin, Mergers Between On-Demand Service Platforms: The Impact on Consumer Surplus and Labor Welfare (September 18, 2018). Available at SSRN: https://ssrn.com/abstract=3251761

Xiaogang Lin

South China University of Technology ( email )

Wushan
Guangzhou, AR Guangdong 510640
China

Tao Lu (Contact Author)

Erasmus University Rotterdam (EUR) - Rotterdam School of Management (RSM) ( email )

Rotterdam
Netherlands

Xin Wang

Hong Kong University of Science & Technology (HKUST) - Dept. of Industrial Engineering and Decision Analytics ( email )

Hong Kong

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