Estimating mode choice of motorized two-wheeler commuters under the influence of combined travel demand management measures: An ICLV modeling approach

Several studies have reported the need for combining multiple Travel Demand Management (TDM) measures for minimizing the use of private vehicles. However, a detailed empirical analysis is needed to substantiate the theory and understand the factors influencing the resultant mode choice behavior. This paper presents a stated choice experiment study to examine the mode choice behavior under the influence of a combined TDM package of Congestion Pricing (CP) and Public Bike Sharing (PBS). The case study area is the old city of Ahmedabad, which is in the western state of Gujarat, India. A stated choice experiment was conducted, wherein a total of 1,719 data points randomly collected from 573 motorized two-wheeler commuters were used to simultaneously estimate an Integrated Choice and Latent Variable (ICLV) model for work trips in the study area. In addition to the observable variables associated with an individual's socioeconomic and trip characteristics, the model also includes the psychological theory of ValueAttitude-Behavior (VAB) in the choice modeling framework. The results show that there exists a statistically significant influence of values of benevolence and stimulation as well as attitudes towards the flexibility of mode, environment, and health in explaining individual preferences. Furthermore, the modeling results also suggest that the combined TDM measures are likely to significantly influence mode choice decisions as opposed to standalone TDM measures.