Abstract:
The pursuit of a global strategy for environmental sustainability and enhancing urban
mobility was acknowledged by many nations as being dependent on increasing public
transportation. Even with more number of buses, it is unable to attract travelers to bus
service. So, a broad approach is required to understand various clusters of travelers.
Segmentation of travelers is usually done based on socio-economic characteristics such
as income, education, car ownership etc., but there has been no evidence on how
effective this classification was based on the above characteristics. The present study
has been done to identify the best method for segmentation of travelers and to
understand various clusters and attract them based on their needs. For this, cluster
analysis was done to divide users into clusters based on the importance of various travel
attributes. Fuzzy-c clustering was identified as the best clustering method for the present
context using Spearman’s rank correlation. The priority areas for each cluster were
determined by examining passenger factor structures and management schemes for bus
services. Results indicated that users in the two clusters had different travel needs and
their priority areas of intervention for improving bus service also varied. These findings
serve as guidelines for enhancing bus service in Kolkata by taking the travelers’ needs
in each cluster into account. In various situations, the methodology can be applied to
prepare policies and strategies for service improvement.
