Understanding Users' Recommendation Intention of Taxi-hailing Apps: An Internal Perception Perspective

Users’ recommendation intention has drawn greater intention by both scholars and managers under the context of electronic commerce. Based on TAM (Technology Acceptance Model), this study aims to examine factors affecting users’ recommendation intention of Taxi-hailing apps in Chinese context. Structural equation model is used in this study. Data collected from 261 Taxi-hailing apps users. The results show the following key interesting findings: (1) both perceived usefulness and perceived ease of use have positive effect on users’ perceived benefits; (2) perceived benefits has positive effect on users’ trust, while perceived privacy risk has negative effect on users’ trust; (3) users’ trust has positive effect on users’ recommendation intention; (4) perceived benefits acts as a partial mediator between perceived usefulness/users’ trust and perceived ease of use/users’ trust, and users’ trust acts as a partial mediator between perceived benefits and users’ recommendation intention. Implications for researchers and practice are discussed.