Model of Consumer Participation in Urban Transportation Platforms: A Mixed-Methods Approach
Keywords:
Consumer behavior, Consumer participation, Sharing economy, Urban transportation platforms, Ride, hailing platforms, Mixed, methods researchAbstract
Objective: This study aimed to develop and validate a model of consumer participation in urban transportation platforms in Iran.
Methodology: This applied study used a mixed-methods design conducted in three sequential phases. In the first phase, a systematic literature review and meta-analysis were carried out on 42 selected quantitative studies to identify the preliminary determinants of consumer participation in sharing-economy and ride-hailing platforms. In the second phase, qualitative data were collected through semi-structured interviews with 14 experts, including senior specialists from urban transportation platforms and university professors and specialists in marketing. The interview data were analyzed through open, axial, and selective coding. In the third phase, the conceptual model was tested through a quantitative survey of 396 users of Snapp and Tapsi, the two leading ride-hailing platforms in Iran. Data were collected using a researcher-developed questionnaire based on the findings of the meta-analysis and qualitative phase, designed on a five-point Likert scale. The validity and reliability of the instrument were confirmed through Cronbach’s alpha, composite reliability, average variance extracted, and the Fornell–Larcker criterion. The data were analyzed using Structural Equation Modeling in SmartPLS.
Findings: The inferential results indicated that economic factors, perceived benefits, cultural factors, platform characteristics, marketing factors, psychological factors, service quality, demographic factors, attitude, satisfaction, perceived risk, and perceived barriers had significant effects on consumer participation. Economic factors showed a significant path coefficient of 0.255, platform characteristics 0.183, service quality 0.221, attitude 0.230, and satisfaction 0.152. Perceived risk and perceived barriers significantly reduced consumer participation. However, environmental factors were not significant, with a path coefficient of -0.004 and a t-value of 0.101. Social factors were also rejected, with a path coefficient of 0.071 and a t-value of 1.436. The goodness-of-fit index was 0.453, indicating strong model fit and predictive quality.
Conclusion: The final model demonstrated that consumer participation in Iranian urban transportation platforms is a multidimensional phenomenon shaped mainly by economic, psychological, service-related, attitudinal, satisfaction-related, risk-related, and barrier-related factors. The model provides a practical framework for platform managers, urban policymakers, and researchers studying sharing-economy services in developing countries.
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