Assessing Service Quality of Ride Hailing Bike Service within Kathmandu Valley
Date
2024-07
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
I.O.E
Abstract
Adopting a sustainable transportation approach necessitates a shift towards eco-friendly travel modes, such as ride-hailing bike services like Pathao and Indrive. These services which have introduced a potentially transformative change to Nepal's transportation landscape are prominent in Kathmandu valley, as evidenced by their daily ridership and public recognition. Being a relatively new concept, assessing its service quality is crucial for its continued viability. Evaluating perceived service quality involves a complex decision making process that considers various observed and unobserved factors. This study evaluates the service quality of Pathao and Indrive bike services using structure equation modeling to identify unobserved influencing factors. Six latent factors were identified through factor analysis. An empirical model was developed to understand the interactions among key variables affecting service quality. SPSS 22 and SPSS Amos 21 were used for model development. The study found that user safety is the most significant latent variable influencing service quality followed by service features and application efficiency. The heterogeneity among users regarding different service quality attributes were also analyzed. This study will provide valuable insights to improve these services, enhancing their effectiveness and usability and provide clarity to inform suitable policy decisions.
Description
Adopting a sustainable transportation approach necessitates a shift towards eco-friendly travel modes, such as ride-hailing bike services like Pathao and Indrive. These services which have introduced a potentially transformative change to Nepal's transportation landscape are prominent in Kathmandu valley, as evidenced by their daily ridership and public recognition. Being a relatively new concept, assessing its service quality is crucial for its continued viability.
Keywords
Structural Equation Modeling, Factor Analysis, Latent Variables