2006Transportation Research Board 85th Annual MeetingTransportation Research BoardRequires access

Trip Attraction Characteristics of Neighborhood- and Community-Level Shopping Centers

Shinya Kikuchi

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Abstract

In suburban areas, shopping centers are the main destination for shopping and many other non-work activities today. This paper examines the trip generation characteristics of the neighborhood- and community-level shopping centers. Because a shopping center is set up to promote the synergistic effects of having many different stores in one place in order to attract more visitors, the models of trip generation rate of shopping centers need to account for the internal capture as well as the external capture of trips. Traditionally, the ITE Trip Generation’s model considers the trip generation rate of a shopping center as a function of the gross leasable area (GLA); no differentiation is made regarding the size and function of the shopping center. This study examines three approaches to the estimation of trip generation rate: one, based on the fixed features of the shopping center (GLA and number of stores in the shopping center); two, based on the use of internal capture rate; and three, based on the sum of weighted attraction of individual stores. The models are calibrated using data obtained in northern Delaware. The latter two models incorporate the aspect of internal capture, macroscopically and microscopically, respectively. It is found that these three models can estimate trip generation fairly well. However, given the large variation of the values of coefficients for the second and the third models, the first model is the most reasonable model for practical application.

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What this paper is about

In suburban areas, shopping centers are the main destination for shopping and many other non-work activities today. This paper examines the trip generation characteristics of the neighborhood- and community-level shopping centers. Because a shopping center is set up to promote the synergistic effects of having many different stores in one place in order to attract more visitors, the models of trip generation rate of shopping centers need to account for the internal capture as well as the external capture of trips. Traditionally, the ITE Trip Generation’s model considers the trip generation rate of a shopping center as a function of the gross leasable area (GLA); no differentiation is made regarding the size and function of the shopping center. This study examines three approaches to the estimation of trip generation rate: one, based on the fixed features of the shopping center (GLA and number of stores in the shopping center); two, based on the use of internal capture rate; and three, based on the sum of weighted attraction of individual stores. The models are calibrated using data obtained in northern Delaware. The latter two models incorporate the aspect of internal capture, macroscopically and microscopically, respectively. It is found that these three models can estimate trip generation fairly well. However, given the large variation of the values of coefficients for the second and the third models, the first model is the most reasonable model for practical application.

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Available abstract

In suburban areas, shopping centers are the main destination for shopping and many other non-work activities today. This paper examines the trip generation characteristics of the neighborhood- and community-level shopping centers. Because a shopping center is set up to promote the synergistic effects of having many different stores in one place in order to attract more visitors, the models of trip generation rate of shopping centers need to account for the internal capture as well as the external capture of trips. Traditionally, the ITE Trip Generation’s model considers the trip generation rate of a shopping center as a function of the gross leasable area (GLA); no differentiation is made regarding the size and function of the shopping center. This study examines three approaches to the estimation of trip generation rate: one, based on the fixed features of the shopping center (GLA and number of stores in the shopping center); two, based on the use of internal capture rate; and three, based on the sum of weighted attraction of individual stores. The models are calibrated using data obtained in northern Delaware. The latter two models incorporate the aspect of internal capture, macroscopically and microscopically, respectively. It is found that these three models can estimate trip generation fairly well. However, given the large variation of the values of coefficients for the second and the third models, the first model is the most reasonable model for practical application.

Key concepts: Trip generation, TRIPS architecture, Center (category theory), Attraction, Function (biology), Computer science, Set (abstract data type), Work (physics)

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