Nonmotorized Commuting Behavior of Middle-Income Working Adults in a Developing Country

Abstract

Although non-motorized transport (NMT) offers economic, environmental, and health benefits to individuals and communities, understanding non-motorized travel behavior is a challenging task due to complex interactions of a wide range of factors. Whilst behavioral models offer a conceptual framework to understand human behavior, their use in the study of travel behavior in developing countries is still in its infancy. This study uses three behavioral models-the theory of planned behavior, the theory of triadic influence, and the ecological model of health behavior-to identify potential factors influencing intentions and behavior toward the use of NMT by middle-income working adults, inhabiting Chittagong City Corporation (CCC) area of Bangladesh. A total of 720 middle-income working adults (aged between 18 and 65 years) was randomly selected and interviewed at major commercial and retail business areas of the CCC. Multiple linear and binary logistic models were developed to quantify the extent of the influence of different factors on non-motorized mode choice behavior. Results indicated that personal factors (proximal) such as attitude, subjective norm, and behavioral control influence respondents' intentions and motivation in choosing NMT. However, the current use of NMT was less controlled by intention, while factors associated with the social, cultural, and built environment had (distal) significant influence. The findings of this study could assist urban planners in adopting structural and non-structural measures to promote NMT use.

Assessing the performance of public transport services in a developing country: A case study using data envelopment analysis

“…Many industries, factories, offices, garments, and shopping centers are located in the CCC, so the local bus service plays a very important role in the movement of people within the zone (Zannat et al., 2014). Other types of motorised and non‐motorised vehicles (e.g., rickshaw, autorickshaw which is driven by compressed natural gas (CNG), human hauler, private car) operate within the area (Zannat et al., 2021). There are currently 10 routes traversed by the public bus service, 17 routes for human haulers, and 16 routes for CNG powered auto‐rickshaws.…”

Modeling Departure Time Choice of Car Commuters in Dhaka, Bangladesh

“…), state of technological advancement (e.g., reliable internet access and uninterrupted power supply to work from home) and transport landscape (e.g., car ownership levels, public transport accessibility, paratransit, etc.). All these lead to significant differences in activity and travel behavior (7,17,18) and affect the transferability of the models (17)(18)(19). Further, modeling frameworks formulated for the developed countries are very often not directly applicable in the context of developing countries where detailed socio-demographic information and fine-scale spatial and temporal data are not available (7).…”