Determining mode shift elasticity based on household income and travel cost

Abstract

The present study focuses on changes in the behavior of travelers belonging to various monthly income groups from a transit deficient metropolitan city, when the travel cost of present mode changes. Socio-economic, demographic, and travel characteristics were collected using a well-structured questionnaire. To capture the mode shift behavior, perception of travelers (willingness to shift) for different travel cost change scenarios were also recorded. Households were categorized into four income group levels based on the statistical Post-Hoc technique to corroborate the effect of income levels on mode shift behavior. After that, travel demand elasticity analysis was carried out with variation in travel cost using Shrinkage Ratio Technique, to comprehend the sensitivity of travelers in different income groups towards mode choice due to changes in travel cost. The results indicated that the low-income group (LIG) travelers are more sensitive to price change compared to the high income group (HIG) travelers. Subsequently, the shift behavior from the existing private modes to public transport was modeled using Binary Logistic Regression for different income groups, to comprehend the combined effect of monthly income and changes in travel cost on mode shift behavior. It was observed that concerning low-income group (LIG), other three income groups enjoyed higher satisfaction (higher utility) for personalized travel mode at a specific value of travel cost and hence, a lesser shift towards public transportation was observed. Interestingly, identical shift behavior was observed among different income groups for a certain range of travel cost values. Further, sensitivity analyses of the developed mode shift model are performed by considering the changes in In-Vehicle Travel time (IVT) and Travel Cost (TC) of present private mode. Indifference curves with travel cost and travel time were then developed based on a non-linear utility function for different income groups. The curves explain the level-of-service and utility difference of available travel modes based on travel cost and travel time.