Business model patterns in the sharing economy

Abstract

Sharing platforms struggle to remain financially viable and preserve their prosocial and environmental aspirations; therefore, effort to empirically study successful sharing economy business models (SEBMs) is needed. The aim of this research is to identify business model patterns among existing SEBMs in order to suggest business model attributes that support successful implementation. Patterns describe one or several recurring business model attributes observed among existing business models. This study investigates 63 SEBMs across 93 different configuration options. The k-medoids clustering approach was used to identify configuration options recurring repeatedly across the data. The empirical results were triangulated with existing business model patterns from literature. The study presents a framework to describe and analyse SEBMs; eight prototypical patterns, with a corresponding list of relevant business model attributes; and six solution patterns unique to the sharing economy. The patterns – as well as insights across locations, shared practices, and platform types – advance knowledge on the sharing economy. Furthermore, these patterns support sharing platforms to communicate, learn, and experiment, ideally supporting successful implementation of SEBMs.