Off-Platform Threats in On-Demand Services

Eryn Juan He (), Sergei Savin (), Joel Goh () and Chung-Piaw Teo ()
Additional contact information
Eryn Juan He: David Eccles School of Business, The University of Utah, Salt Lake City, Utah 84112
Sergei Savin: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Joel Goh: Department of Analytics and Operations, NUS Business School, Singapore 119245; Global Asia Institute, National University of Singapore, Singapore 119076; Institute of Operations Research and Analytics, National University of Singapore, Singapore 119245
Chung-Piaw Teo: Department of Analytics and Operations, NUS Business School, Singapore 119245; Institute of Operations Research and Analytics, National University of Singapore, Singapore 119245

Manufacturing & Service Operations Management, 2023, vol. 25, issue 2, 775-791

Abstract: Problem definition : Online platforms that provide on-demand services are often threatened by the phenomenon of leakage , where customer-provider pairs may decide to transact “off-platform” to avoid paying commissions to the platform. This paper investigates properties of services that make them vulnerable or resistant to leakage. Academic/practical relevance: In practice, much attention has been given to platform leakage, with platforms experimenting with multiple approaches to alleviate leakage and maintain their customer and provider bases. Yet, there is a current dearth of studies in the operations literature that systematically analyze the key factors behind platform leakage. Our work fills this gap and answers practical questions regarding the sustainability of platform. Methodology : We develop two game-theoretical models that capture service providers’ and customers’ decisions whether to conduct transactions on or off the platform. In the first (“perfect information”) model, we assume that customers are equipped with information to select their desired providers on the platform, whereas in the second (“imperfect information”) model, we assume customers are randomly matched with available providers by the platform. Results : For profit maximizing platforms, we show that leakage occurs if and only if the value of the counterparty risk from off-platform transactions exceeds a threshold. Across both models, platforms tend to be more immunized against leakage as provider pool sizes increase, customer valuations for service increase, their waiting costs decrease, or variability in service times are reduced. Finally, by comparing the degree of leakage between both settings, we find that neither model dominates the other across all parameter combinations. Managerial implications : Our results provide guidance to existing platform managers or entrepreneurs who are considering “platforming” their services. Namely, based on a few key features of the operating environment, managers can assess the severity of the threat of platform leakage for their specific business context. Our results also suggest how redesigning the waiting process, reducing service time variability, upskilling providers can reduce the threat of leakage. They also suggest the conditions under which revealing provider quality information to customers can help to curb leakage.

Keywords: on-demand services; platform leakage; sustainable operations; game theory; queueing theory (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:25:y:2023:i:2:p:775-791

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