Sources of influences on customers' trust in ride-sharing: why use experience matters?

Zhen Shao, Yue Guo, Xiaotong Li*, Stuart Barnes

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)

Abstract

Purpose: Despite the growing popularity of ride-sharing in China, our understanding regarding users' trust and behavioral intention toward this new type of hailing service is still limited. This study aims to examine the joint influences of institution-based, process-based and characteristic-based antecedents on customers' trust and continuance intention toward ride-sharing. Furthermore, the study aims to investigate if the relative influences of institution-based and process-based antecedents on trust are contingent upon customers' prior experience. Design/methodology/approach: Drawing upon trust-building literature and the elaboration-likelihood model, we developed a research model and conducted an online survey to users of Didi, the largest ride-sharing platform in China. We used the structural equation modeling technique to analyze the collected data and examine the proposed research model. Findings: Ther major research findings of the study suggest that structural assurance, government support, platform reputation and disposition to trust exhibit significant and different degrees of influences on customers' trust beliefs and continuance intention toward ride-sharing. A multi-group analysis further suggests that customers with less use experience focus more on government support and platform reputation, while customers with more use experience are more likely influenced by structural assurance. Originality/value: The study contributes to the extant literature by identifying the joint influences of institutional-based, process-based and characteristic-based antecedents on users' continuance intention of ride-sharing service and uncovers the mediation mechanism of trust and perceived risk. Moreover, the study refines the boundary condition of the proposed research model by revealing the moderating effect of use experience.

Original languageEnglish
Pages (from-to)1459-1482
Number of pages24
JournalIndustrial Management and Data Systems
Volume120
Issue number8
DOIs
Publication statusAccepted/In press - 1 Jan 2020

Keywords

  • Elaboration-likelihood model
  • Ride-sharing
  • Trust building
  • Use experience

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