Identification of neighborhood typology for potential transit-oriented development

While a good number of studies have defined neighborhood typologies based on transit-oriented development (TOD) factors, the literature offers limited clues for the identification of neighborhood types that are likely to be designated as TODs. The present study fills this gap through the use of a cluster-multilevel modeling approach for examining the underlying effects of urban structure on travel behavior among different neighborhood types. A two-step cluster analysis on spatial data from 47 neighborhoods of the Delhi metropolitan region has resulted in six neighborhood types. The study verifies the developed typology through the analysis of significant differences in terms of socio-demographic, and travel behavior variables, and found that the typology is valid. Besides, individual multilevel regression (MLR) models were developed using 5553 individual responses from all neighborhoods of typology. The MLR models were evident that the urban structure has an apparent effect and explains about one-third of the total variation in the distance traveled, assuming that other factors such as residential self-selection, land values, and environment may explain the remaining effects. This study has identified that the 'transit' type has shown consistent relationships between urban structure and vehicle kilometers traveled (VKT), thereby replicate TOD as a concept. The findings from the study are useful as a prescription tool for planners, policymakers, and government authorities to compare the performance of TOD characteristics within existing and planned neighborhoods. The modeling results are easy to be interpreted and are transferable to other Indian cities.