An Investigation on Sharing Economy Mobile Service Adoption: How Perceived Risk, Value, and Price Interact?

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Abstract

Originally developing from redistribution of idle resources, the sharing economy has expanded rapidly since its emergence because it enhances the efficiency of asset utilization through paid rentals of surplus resources, creating a win-win situation between users and re-source owners, and the subversive business opportunities brought by its business model attract global attention. However, related research on discussing user’s adoption towards sharing economy mobile services (M-services) is still lacking. As we know, a solid understanding of user perception enables a more robust definition of better market alignment. The contribution of this study is to discuss the key elements of sharing economy M-service adoption by including contingencies in which low and high user experience existed. We applied three theories – perceived risk (including security uncertainty and performance uncertainty), perceived value (perceived usefulness), and perceived price – and hypothesized that each had a different effect on sharing economy M-service adoption. The hypotheses were tested by multi-group SEM approach with 509 responses in Taiwan. Our findings verified that users’ perceived usefulness is a major driver to the widespread adoption of sharing economy M-services for both low and high- experienced contingencies. Also, the effects of security uncertainty and performance uncertainty are both mediated by perceived usefulness for high experienced users; while the mediated effect of perceived price does not exist. In addition, there were significant differences in the influence of perceived price on adoption intention in low and high-experienced contingencies, and thus illustrated different strategies have to be proposed for sharing economy M-service marketing. Implications and future research is suggested.

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APA

Lin, S. P., & Chan, Y. H. (2019). An Investigation on Sharing Economy Mobile Service Adoption: How Perceived Risk, Value, and Price Interact? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11572 LNCS, pp. 312–325). Springer Verlag. https://doi.org/10.1007/978-3-030-23560-4_23

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