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ATS International Journal
Editor in Chief: Prof. Alessandro Calvi
Address: Via Vito Volterra 62,
00146, Rome, Italy.
Mail to: alessandro.calvi@uniroma3.it

Factors shaping user satisfaction in ride-hailing: evidence from personal vehicle owners

S. Deb, K. Bhagwat
Pages: 157-176

Abstract:

Background: In the context of small and medium sized cities of India, where car ownership is prevalent, it is essential to explore how personal vehicle owners perceive and utilize Ride Hailing Service (RHS). This study aims to fill the gap in literature by focusing on this specific user group and examining the socio-economic characteristics affecting their satisfaction. Methods: A survey of 718 car owners in Guwahati, India, collected data on socio-economic characteristics and RHS attributes. Using Structural Equation Modelling (SEM), we analysed these factors through SERVQUAL’s five dimensions—empathy, responsiveness, assurance, tangibility, and reliability—plus app features. Results: Empathy towards the users of RHS emerged as the most critical factor for user satisfaction, followed by responsiveness, assurance, tangibility, and reliability. Lower-income users prioritized empathy and responsiveness, higher-income users emphasized responsiveness and assurance, and male users valued empathy and responsiveness while females prioritized assurance.  Policy implications: The study recommends inclusive policies to address varying perceptions among socio-economic groups, promoting RHS adoption and reducing car ownership in urban areas. Novelty: While RHS studies focus largely on large cities, this research targets Guwahati, a medium-sized Indian city, filling a literature gap on smaller urban centres in emerging economies. This study contributes region-specific insights into RHS satisfaction and provides a foundation for policies promoting RHS as a car ownership alternative, especially relevant for India's mid-sized urban areas facing unique transportation challenges.
Keywords: Ride Hailing Service; Structural Equation Modeling; users’ perception; socio-economic characteristics; qualitative data analysis

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