Citation

Verma A, Verma M, Sarangi P, Yadav V, M M. Journal of Choice Modelling 2021; 38: e100267.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.jocm.2021.100267

PMID

unavailable

Abstract

Activity travel pattern of pilgrims in a religious setting is a complex process. Extant literature on religious tourism has taken minimal efforts in addressing such complexity, which has led to a paucity of information on preferred activity participation destinations and trip chain sequences of pilgrims. So, the present research objective is two-fold. First, to examine the causal effects of socio-demographics and daily local temperature on activity participation, trip chain type, and time allocation of individuals using structural equation modeling (SEM) that can help identify the dominant activity patterns. Second is to explore the impact of socio-demographic variables and activity patterns on the propensity of stop-making behavior using an ordered logit (OL) framework to better plan and manage the influx of flows. The primary data was collected using an activity-travel diary by taking the case study of the Kumbh Mela event, which is considered as the world's largest mass religious gathering, held at Ujjain, India, in 2016. From the results, it is observed that Males have a lower tendency to take multiple stops for primary religious activities and have simple trip chains. An increase in the members of a family visiting Kumbh decreases their overall time spent across various activities. As the mercury (temperature) rises, it reduces tourist's participation in recreational and discretionary activities. Individuals who participate in primary and secondary religious activities tend to spend more time at Kumbh as compared to individuals who primarily visit for recreational purposes. These empirical findings provide meaningful insights for managing large religious events.

Language: en

Keywords

Activity participation; Episode duration; Kumbh mela; Ordered logit model (OL); Propensity of stops; Structural equation modeling (SEM)