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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 …