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 to avoid paying the platform commissions. This paper investigates properties of services that make them vulnerable or resistant to leakage. Methodology: We develop two game-theoretical models that capture service providers' and customers' decisions whether to conduct their business on or off the platform. In the base model, we assume that customers are equipped with information to select their desired providers on the platform, whereas in the extension, we assume customers are randomly matched with available providers by the platform. Results: Leakage occurs if and only if the value of the counterparty risk from off-platform transactions is neither too small nor too large. Across both models, platforms tend to be more immunized against leakage as customer valuations for service increase or their waiting costs decrease. In the base model, platforms with larger provider pool sizes tend to be more immunized against leakage. In the extension, platforms that feature higher proportions of high quality providers or lower heterogeneity in service quality are more resistant to leakage. Finally, by comparing the degree of leakage or the platform's expected profit between both settings, we find that neither model of perfect information nor the imperfect information setting dominates the other for 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 and upskilling providers, as well as the conditions under which revealing provider quality information to customers can help to curb leakage.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.