Demand-side Reputation and Matching on On-demand Platforms: Evidence from a Field Experiment
Ruigang Jia, Peijian Song, Wenyu Yang, and Liangding Jia
International Journal of Electronic Commerce,
Volume 30, Number 4, 2026, pp. 507-536.
Abstract:
On-demand platforms create uncertainty not only for customers choosing suppliers, but also for suppliers when selecting and serving customers, and high-cost customers may depart from expectations and norms. However, while prior literature has largely focused on supply-side information asymmetry and identified supply-side reputation as a key governance tool, the understanding of demand-side reputation is limited. We study the effects of disclosing demand-side reputation information using a field experiment on a freight service platform. Exploiting the rollout of a demand-side reputation system, we find that the matching performance is enhanced with supportive evidence of reduction in search friction and demand-side quality improvement; the matching quality is improved, which is consistent with a decline in moral hazard. The moderating analyses reveal that these effects are stronger for customers with lower ex ante quality, while market thickness strengthens the effect on matching performance but not on matching quality. These findings extend the platform and reputation system research by showing that demand-side reputation improves platform-level matching outcomes, and suggest that on-demand platforms can use demand-side reputation as a core governance mechanism while complementing it with additional design features as users adapt strategically.