Platform-mediated reputation systems in the sharing economy and incentives to provide service quality: The case of ridesharing services

Abstract

Sharing economy platforms often use reputation systems to actively perform a 'regulatory'/control role, by excluding from access to the platform users with ratings below a given threshold. We provide a multiple case study analysis of 9 platforms and investigate through a simple inter-temporal choice model the effect of the design of this specific application of online rating systems on users/providers' incentives to ensure a high level of service quality. Compliance with the platform's behavioural rules is imperfect even with perfect reviews and even if riders cannot switch across platforms. It can be increased by linking remuneration to performance and by increasing the opportunity cost of reintegrating the endowment of reputation, also by influencing providers' perception of the magnitude of this cost. Thus, there may be an efficiency rationale for the controversial choice to willingly preserve riders' uncertainty as to the operation of the algorithm and for portability of reputation.

How should we understand the digital economy in Asia? Critical assessment and research agenda

“…In the ride-sharing context, Basili and Rossi (2020) conducted multiple case studies of booking platform providers across several service domains. They studied how the choices consumers made to gauge the quality of their services and reputation systems affect the incentives, effort and performance of drivers to comply with the firms’ service quality standards.…”

Drivers of Supplier Participation in Ride-Hailing Platforms

“…Some ride-hailing platforms provide a passenger rating system. It allows consumers to build an online reputation and hence allows drivers to review and evaluate passengers [10], leading to a safer work environment for drivers. Also, some ride-hailing platforms offer a substitute phone number function, which shows a dummy number for drivers and passengers when they communicate.…”

Research directions for sharing economy issues

“…Yet, we wish to make the journal's perspective clear in terms of its leadership's openness to new disciplines and interdisciplinary research. Extraordinary advances are possible based on responsible research and innovation (Boons and Bocken, 2018;Jirotka et al, 2017), new design science approaches for sharing economy settings (Hevner et al, 2004; and research on new algorithms for reputation and recommendations (Basili and Rossi, 2020;Sun et al, 2019). Of equally-high relevance are enhanced applications for causal inference, big data methods, and computational social science (Chang et al, 2014, and new machine and Internet-based experimental, ML and AI approaches.…”