ANNOUNCEMENTS
Transport systems play a significant role in socio-economic development and impact a city's human health (HH) status through multiple pathways. Many factors such as a city's-built environment (BE), people travel behaviour (TB), travel patterns, and the socioeconomic status of urban commuters influence the transport system. A vast amount of literature is available in silos that evaluates the relationship between these components, particularly in the context of developed countries. So far, the research community has not agreed on the underlying nexus between BE, TB, and HH. Given this, the present study aims to (i) assess the relationship (both intensity and magnitude) between BE, TB and HH; (ii) identify the factors that influence the travel patterns and TB of urban commuters; (iii) conceptualise and develop a nexus model between BE, TB and environmental health (EH) which can be used to understand the transport scenario of different cities; (iv) test the conceptualized model by taking Delhi as a case study and finally (v) develop an empirical model that can predict the likely travel mode choice of a commuter.
The study adopted an integrated approach to evaluate the nexus between BE, TB and EH by taking case examples of four neighbourhoods of Delhi, including Dwarka, Vasant Kunj, Rajouri Garden and Connaught Place (CP) within a structural equation modelling (SEM) framework. Along with GIS-based BE characterization of four neighbourhoods, primary data regarding the BE of neighbourhoods, travel patterns, TB and sociodemographic profile of working individuals was collected from 1506 respondents for two-time periods, i.e., 2005 and 2019 to conduct a semi-longitudinal evaluation of the underlying nexus. An overlay analysis using satellite data was conducted to assess the BE characteristic changes in the four neighbourhoods between 2005 and 2019, which was further correlated with changing travel patterns of commuters over the same period. Multinomial logistic regression (MLR) was adopted to first identify the pertinent factors that influence the TB of respondents. After identifying the important factors, the simultaneous impact of these factors on travel mode choice decision (TB of commuters) was evaluated using SEM analysis.
BE characteristic mapping of the study sites for 2005 and 2019 revealed different orders of changes in the functional classes of the localities, with maximum changes observed in Dwarka and minimum in CP. A 31% increase from 643ha in 2005 to 844ha in 2019 was observed in the total built-up area of Dwarka with significant increase in transit facilities, especially metro services. A similar transition was observed in Vasant Kunj, which experienced an increase in the residential and commercial areas by ~44% (69 in 2005 to 99ha in 2019) and 81% (20ha in 2005 to 36.4ha in 2019), respectively. In contrast, CP and Rajouri Garden being older communities that are developed to the maximum of their capacities, did not witness many changes in their BE over this time-period. A similar trend of BE changes was also reflected from the primary data collected by the respondents regarding accessibility to different facilities within their neighbourhoods between 2005 and 2019.
Modal share analysis indicated that private vehicle, PV, use increased by 21% between 2005 and 2019, with the highest rise in 4-wheeled vehicle use. Bus use declined by 32%, while the metro ridership witnessed an increase of 20% during this period, suggesting a transition in the mobility patterns of the city. A comparative evaluation of modal share among the four neighbourhoods highlighted the potential impact of BE on TB of respondents. Access to transit facilities emerged as an important determinant of travel mode choice. For instance, metro ridership increased by 19%, 23%, 28% and 9% between 2005 and 2019 in Dwarka, Rajouri Garden, CP, and Vasant Kunj, respectively. Similarly, CP with the highest bus stop density and bus frequencies had the highest bus use of 28% in 2019 among all the four neighbourhoods. Further, MLR results showed a statistically significant impact of socio-economic status and attitude emerged on travel mode choice, especially private vehicles. A statistically significant negative association was observed between access to transit and private vehicle usage, i.e., respondents tended to use public transport if it was accessible and offered first and last-mile connectivity.
The associations that emerged from exploratory and MLR analysis was further verified by SEM, which revealed the existence of a multidimensional and complex nexus between BE, TB and EH (BETH nexus) which operates at different spatial scales. Temporal evaluation of the nexus in 2005 and 2019 revealed that the relative impact of different factors on travel mode choice decision can change with geographies and time. It was observed that BE was the most important influencing factor (factor loading=0.766) for determining the choice for private vehicle among all other factors in 2005 but was not a significant factor in 2019. The relative impact of factors on the selection of private vehicle for daily travel in 2005 was BE>Socio-Economic Status (SES)>Attitude (Pro-PV) which changed to Attitude (Pro-PV)>SES>Vehicle Ownership, VO in 2019. This indicated a transition in the relative importance of factors over time, thus highlighting a nexus between these components. Finally, after establishing the BETH nexus model, an empirical model based on the findings of SEM analysis was developed to predict the likelihood of an individual to choose a particular mode of transport. A moderate agreement model with a kappa coefficient value of 0.47 was developed to predict individual's likelihood to choose 2-W, 4-W and Public Transport, PT with an accuracy of 73%, 62% and 89%, respectively.
Conclusively, a reinforcing relationship was observed among all the components of BETH nexus, which corroborates the need to not view urban planning, transportation, human health, and human psychology as separate entities but as complex and inextricably interlinked systems that can help achieve a sustainable transportation system also the intended sustainable development goals of a city. The study provides an approach to adopt practical and implementable solutions for re-informing the transport systems of developing cities, specifically in India.
Key Words of the Research: Transport system, Travel behaviour, Built environment, Environmental health, Nexus, Sustainable transportation.
