Loyalty Programs in the Sharing Economy: Optimality and Competition

TL;DR

This paper analyzes how sharing economy platforms can design optimal loyalty programs to maximize revenue, considering market heterogeneity and competition, and finds that multi-threshold programs outperform simple bonuses.

Contribution

It characterizes the optimal loyalty program for homogeneous users and introduces a simple, implementable multi-threshold loyalty program for heterogeneous markets.

Findings

Multi-threshold loyalty programs achieve optimal revenue in heterogeneous markets.

Sophisticated loyalty programs outperform simple sign-up bonuses.

Heterogeneity level influences loyalty program and pricing effectiveness.

Abstract

Loyalty programs are important tools for sharing platforms seeking to grow supply. Online sharing platforms use loyalty programs to heavily subsidize resource providers, encouraging participation and boosting supply. As the sharing economy has evolved and competition has increased, the design of loyalty programs has begun to play a crucial role in the pursuit of maximal revenue. In this paper, we first characterize the optimal loyalty program for a platform with homogeneous users. We then show that optimal revenue in a heterogeneous market can be achieved by a class of multi-threshold loyalty program (MTLP) which admits a simple implementation-friendly structure. We also study the performance of loyalty programs in a setting with two competing sharing platforms, showing that the degree of heterogeneity is a crucial factor for both loyalty programs and pricing strategies. Our results show that sophisticated loyalty programs that reward suppliers via stepwise linear functions outperform simple sign-up bonuses, which give them a one time reward for participating.