Assessing User Contentment in Long-Distance Public Transport: An Analytical Approach Utilizing Principal Component and Regression Analysis
DOI:
https://doi.org/10.3126/injet.v2i1.72578Keywords:
Passenger Satisfaction, Public Transportation, Principal Component Analysis, Long route, VariableAbstract
This study assesses the performance of long-route public transport services, considering passenger contentment as a key metric through the application of a passenger satisfaction approach. A self-rating questionnaire with a 5-point Likert scale was used to rate 16 different variables. The variables were selected after a literature review and consulting with relevant stakeholders. Data collected from com passengers were analyzed to determine the passengers’ comfort and satisfaction using Principal Components Analysis (PCA) and Regression Analysis. Variables with higher-than-average scores indicate that passengers are satisfied with that variable.16 variables with strong correlation among each other were collapsed into different component using PCA. Furthermore, the components extracted from PCA along with two extra variables that are age and sex were regressed to find the mean passenger satisfaction score. This research fills the gap by specifically targeting long-distance public transport in Nepal, an area that has not been extensively studied. It explores the perceptions of passengers regarding the facilities provided by long-route public transport services and identifies the major factors contributing to passenger satisfaction. Previous studies have often emphasized factors such as service quality, comfort, and safety in urban bus services, but there is a notable lack of research addressing the unique challenges and passenger experiences associated with long-distance bus travel. This study can offer theoretical assistance in devising relevant strategies to enhance the satisfaction level of public commuters.
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