| dc.description.abstract | Indian cities have been witnessing rapid transformation due to the synergistic effect of industrialisation, flourishing-economy, motorisation, population explosion, and
migration. The alarming increase in travel demand as an after effect of the
transformation, and the scarcity in transport infrastructures have exacerbated urban
transport issues such as congestion, pollution, and inequity. Due to the escalating cost of transport infrastructure and the scarcity of resources such as space, there has been an increasing interest in promoting sustainable transportation policy measures for the optimum use of existing resources. Such policy measures mostly target the activitytravel behaviour of individuals to bring about desired changes in the transport sector. However, the responses of individuals to most of the measures are complex or unknown. The current ‘commute trip-based’ aggregate travel demand analysis
strategy followed in most of the Indian cities is inadequate for providing basic inputs to understand the activity-travel behaviour of individuals under such policy
interventions. Furthermore, the current analysis strategy also ignores the activitytravel behaviour of non-workers – who include homemakers, unemployed, and retired
individuals – whose inclusion to transportation planning is relevant when the
proposed policies are mostly ‘citizen-centric’.
Analysis of activity-travel behaviour of non-workers provide important
inputs to transportation planning as their activity-travel behaviour, and responses to
transportation policies are different from that of workers. However, case studies
exploring the activity-travel behaviour of non-workers from Indian cities are very
limited. Appraising the practical importance of this subject, the current research
undertakes a comprehensive analysis of the activity-travel behaviour of non-workers
from a developing country’s context. To fulfil the goal, a series of empirical analysis are conducted on a primary activity-travel weekday survey data collected from
Bangalore city. The analysis provides insightful findings and interpretations
consistent with a developing country’s perspective.
The day-planner format of time use diary, which was observed to have satisfactory performances in developed countries, is apparently have inferior performances in a developing country’s context. Further, the face-to-face method of survey administration is observed to have higher operating and economic efficiencies compared to the drop-off and pick-up method.
The comprehensive analysis of activity-travel behaviour of non-workers indicate that comparing with their counterparts in the developed world (e.g. the U.S.),
non-workers in Bangalore city are observed to have lower activity participation level
(in terms of time allocation and number of stops), higher dependency on walking,
lower trip chaining tendency, and a distinct time-of-day preference for departing to
activity locations. On the other hand, the analysis shows similarities (mode use and
trip chaining) and differences (time allocation and departure time choice) with the findings of the case studies from the developing world (e.g. China). Activity-travel behaviour of non-workers belonging to low-income households is characterised by
lower activity participation level, higher dependency on sustainable transport modes,
and lower trip chaining propensity, compared to other two income groups (middle and
high-income groups). The research also suggests that built environment measures
have their highest impacts on non-workers’ travel decisions related to shopping.
Finally, the joint analysis of activity participation and travel behaviour of non-workers indicate that in-home maintenance activity duration drives the time allocation and travel behaviour of non-workers, and non-workers trade in-home discretionary
activity duration with travel time. The joint analysis also shows that the time spent on
children’s and elders’ activity is an important time allocation of its own.
Keywords: Activity-travel behaviour, Non-worker, Time Use, Income Groups, India | en_US |
