Abstract:
Active transport is the type of transport defined where human efforts and energy is spent. It includes all forms of Non-motorised forms of transport including cycling, walking, where physical activity is involved. It might also include public transport where walking and cycling is involved for longer trips in from of access and ingress trips or as a feeder to Public transport. University students and population are more likely to use/adapt active transport as a mode of commute in comparison to the general
population (Bonham et al, 2013). The university campuses and its adjoining area are capable of promoting active transportation. The university campuses form part of major trip attractors and generators, and the sustainability goal of universities go in hand with the promotion of active transport amongst its staff, workers and most importantly students (Whalen et al, 2013). Market segmentation is an approach to cluster the individuals who share some common characteristics that help to formulate
more precise strategies favourable to segmented population (Hair et al., 1998). In the field of transportation planning, there can be three different kinds of travellers such as Captive Motorized transit users, Captive Active transit users and, Potential Active transit users. Captive Active transport users are those who chose to walk or bicycle because of the lack of travel choice or the other motorized means of transport modes are out of their financial means. Captive active transport users continue to walk or
cycle even if they are unhappy with walking or cycling experience. Potential active transport users are those who are not walking or cycling yet but hold the potential to shift toward active transport if conditions are in favour of them. These are very much sensitive to the quality of mode service and can easily shift from one mode to other. Captive motorized users are those who are very much addicted to motorized vehicle usage and do not hold any kind of potential to shift to non-motorized modes of transport due to their socio-economic status (Jacques et al, 2013). This dissertation tries to capture the perception of attitudinal, subjective and objective parameters and
segment the students into the three predefined clusters of a Non-Residential College In Indore through K-means Clustering analysis and calibrate the induced shift by proposing a Public Bicycle Sharing (PBS) Docking Point near the college by Binary Logistics Regression analysis using IBM-SPSS Statistics software.
