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This paper presents a state-of-the practice neighborhood shopping travel demand model. The model structure is designed to incorporate decisions across five dimensions of shopping travel, including decisions of: (1) household tour frequency; (2) participating party; (3) shopping tour type; (4) mode, and (5) destination choices using a tour-based nested-logit model. As a neighborhood model, we have also captured the interrelated effects of three main factors associated with shopping travel decisions both within and outside of the neighborhood, including the residential location within the neighborhood, the neighborhood regional setting and the household structure. The model was validated using the travel data collected in three neighborhoods located in the Puget Sound region, WA. Results show that household socio-demographics have significant effects on the decisions for household tour frequency, mode and destination choices, while the characteristics of the traveling party have considerable impacts on the decisions for tour type. The level of service and the zone attractions influence decisions about mode and destination choices. The day of week variable (weekday versus weekend) is statistically significant in all models, indicating that weekday shopping travel decisions differ from weekend, across all five dimensions of interest. The paper concludes with a discussion about how the model can be used to examine policy-related neighborhood issues (e.g. accessibility).

Despite the popularity of the neotraditional development concept, attempts to investigate the effectiveness of various mixed-use core (MUC) designs in terms of induced localized walking trips are rare. In this study, we use the logsum measure of accessibility derived from a random utility model to investigate how neighborhood design and regional setting affect mode and destination choices for shopping and how these effects vary by income and day of week. We then use the random utility model to simulate changes in the design configuration of the neighborhood MUC and evaluate the effects of the changes on within-neighborhood-accessibility and travel-decision parameters. Our results provide insight on how traditional neighborhood residents choose destinations and modes for their shopping travel and how the geometric design of the MUC can affect travel decisions. We found that local and regional accessibility have interrelated effects on the choice decisions of traditional residents, which results in variations in travel decisions over neighborhood space. In addition, these variations appear even after controlling for income groups and day of week. In simulations evaluating the effectiveness of alternative MUC designs, we find that the optimal MUC design is the one that maximizes proximity to all residential locations in the neighborhood. That is, MUC designs that are confined to the center of the neighborhood are less effective in inducing within-neighborhood shopping.

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