EXPLORATION OF PROSPECTS AND CHALLENGES OF RIDE SHARING IN DEVELOPING COUNTRIES: A CASE STUDY IN DHAKA CITY

Abstract

Public transportation largely contributes to the mobility needs of people which are increasing across the world due to rapid urbanization. Dhaka is Bangladesh's capital city and the country's economic center. Due to an increase in the number of motorized and non-motorized vehicles, roads in Dhaka are extremely congested. Ridesharing is a mode of transportation service that provides greater flexibility and availability on certain routes and is managed by private companies and individuals. Ridesharing is still a relatively new mode of transportation, and there is still a lot of room for growth. To remain competitive and influence customer behavior, service organizations must enhance service quality (SQ). Excellent service involves comprehension of customer feedback. SQ is the hypothetical consequence of a customer's anticipations and perceptions after obtaining service. The main objective of this study is to explore the prospects and challenges of ridesharing in developing countries. A three-step methodology is employed for this research. A Questionnaire survey was conducted in the first step. Second step is interview survey to the operators and third step is data analysis and model development. The questionnaire survey was done to obtain information and users' perceptions about informal ridesharing, while an interview survey was done to gather operators' perceptions. Survey was done in 12 different locations of Dhaka city. The questionnaire had 27 variables all together. 700 questionnaires were distributed for the study. After checking the completeness 628 questionnaires were ultimately chosen for data analysis. The third step addresses SEM model development. Collected data was filtered and a few models were developed to comprehend the relationship between ridesharing service quality and other servicerelated variables. Goodness of fit were checked for each model by trial and error in respect of inserting different variables. Finally, the best model was selected from the developed models based on their fit-indices and resemblance with real life practices. Among four of the developed models, M4 is selected as the best (CFI = 0.97, RMSEA = 0.082, SRMR = 0.068, AIC = 32512.92). M4 is constructed with four endogenous variables, ten exogenous variables and one latent variable. From results of M4, income , trip purpose, safety perception, preschedule trip, willingness to pay fare, and improvement in ridesharing influence SQ positively inferring that by improving those variables ridesharing SQ may be enriched. Among the variables comfort level, safety perception, and willingness to pay for ridesharing, have influence on ridesharing SQ.