Liang Ma, Xin Zhang and Gao Shan Wang

This study examines factors affecting users’ intention to recommend bike-sharing apps from the perspective of internal and external benefits perception. Since the end of 2016, bike sharing has suddenly taken off in China, and competition is fierce. Bike-sharing users’ intention to recommend bike apps is particularly important as it can help operators attract more potential users. However, little research to date has focused on bike-sharing users’ intention to recommend bike apps in the Chinese context. This study aims to fill this research gap using structural equation modelling. Data were collected from 209 bike-sharing app customers and the results show the following key findings: (1) the usefulness of the bike-sharing app is the most important factor contributing to users’ intention to recommend, followed by economic incentive and ease of use; (2) users’ trust that interacts with perceived ease of use has positive effect on users’ intention to recommend, while users’ trust that interacts with economic incentive has negative effect on users’ intention to recommend. Implications for researchers and practice are discussed.

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