Empirical Examination of Users’ Adoption of the Sharing Economy in China Using an Expanded Technology Acceptance Model

Yupeng Liu,Yutao Yang

doi:10.3390/su10041262

Abstract

With the popularity of sharing-based applications such as bicycle and car sharing, the sharing economy has attracted considerable global attention. The factors that affect users’ adoption of the sharing economy must be identified to facilitate the promotion of low-carbon lifestyles and help enterprises attract more active users. By employing the technology acceptance model (TAM) and herd behavior, this study implemented an expanded TAM and identified several factors affecting behavioral intention (BI) toward the sharing economy. A questionnaire was used to obtain the data, which were analyzed through structural equation modeling. The results revealed that perceived usefulness (PU) and perceived ease of use (PEOU) are the main factors affecting BI. Moreover, trust (TRU) was identified as a mediator of subjective norm (SN) and PEOU. Imitating others (IMI) affects BI, and SN affects TRU, PU, and PEOU. Gender moderates SN and IMI. This paper indicates that to improve users’ BI, enterprises should enhance PU, PEOU, and TRU; cooperate with organizations to enhance SN; and guide potential users to imitate others.

Highlights

As a prominent business ecosystem, the sharing economy and its applications encompass substantial market potential
Our data had a high content validity because the questionnaires were translated from international authoritative studies and experts were consulted before the formal investigation; our expanded technology acceptance model (TAM) was based on a literature review, practical analysis, and theoretical integration
Because each concept in this study was measured using multiple indices, we measured the degree to which each indicator reflected the measured concepts to determine whether the items reflected the concepts that were assigned for measurement

Summary

Introduction

As a prominent business ecosystem, the sharing economy and its applications encompass substantial market potential. House sharing (e.g., Airbnb), car sharing (e.g., DiDi Kuaidi), knowledge sharing (e.g., Wikipedia), and bicycle sharing (e.g., Mobike) are some examples of this trend Among these applications, bicycle sharing is one of the most representative of the sharing economy in China [3]; we explored the factors affecting users’ adoption of the sharing economy by studying their adoption of bicycle-sharing applications. According to a report published by iResearch (2017), the number of monthly active users of bicycle-sharing applications at the beginning of 2017 was approximately 10 million, which is less than half the global users (more than 20 million) and less than 10% of the users of transportation-sharing applications (more than 100 million) [7] Despite their initial popularity, bicycle sharing and the sharing economy are yet to receive wide adoption among users. The factors affecting users’ behavioral intention (BI) toward the sharing economy requires exploration

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Conclusion