Analysis of shopping behavior characteristics in the Keihanshin metropolitan area in Japan based on a person trip survey

ABSTRACT

This study analyzed weekday shopping behavior from a home base to a destination using data from the 4th Keihanshin metropolitan area person trip survey. We first analyzed the relationships between occupation and transportation means, transportation means and travel time, and transportation means and duration of time at the destination. Results of a chi-square test, residual analysis, and correspondence analysis confirmed that employed persons tend to travel by cars while unemployed persons tend to travel by bus or walk. The relationship between travel time and duration of time at the destination was also revealed according to transportation means. Results of a cluster analysis then classified shopping behaviors to expose four patterns. Finally, multiple regression analyzed the degree to which certain variables were related to duration of time at the destination. Results confirmed a strong relationship between duration of time at the destination and travel time. The degree of this factor’s influence on other variables was also clarified. The value of these findings is that the relationship between travel time by means of transportation and the duration of time at the destination was clarified using statistical analysis. We then found a highly accurate equation that estimates the duration of time at a destination from the travel time. If the duration of time at a destination can be estimated, it may be possible to more accurately develop the structure of rest facilities, the number of parking lots, the degree of congestion, and so on, which can be associated with the customer’s usage behavior in a shopping site. This research in this paper contributes to the field of urban analysis and marketing by presenting a new effective method for person trip survey and analysis.

KEYWORDS:

• Person trip survey
• shopping behavior
• transportation means
• travel time
• duration of time at a destination

Acknowledgments

This study was supported by Joint Research Program No.690 at Center for Spatial Information Science (CSIS), The University of Tokyo. We would like to thank Editage (www.editage.com) for English language editing.

Data availability statement

The data that support the findings of this study are available from Center for Spatial Information Science (CSIS), www.csis.u-tokyo.ac.jp/english/. The University of Tokyo, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of CSIS.

Additional information

Funding

This work was supported by Kindai University under a Faculty Assistance and Development Research Grant in 2018 [grant number SR09].

Notes on contributors

Takashi Yamada

Takashi Yamada is a lecturer in the Department of Human Factors Engineering and Environmental Design, Kindai University, Japan. He received a Ph.D. from Keio University, Japan. His research covers human behavior modeling, simulation, and space design analysis in buildings or urban spaces.

Takumi Hayashida

Takumi Hayashida received his B.E. from Kindai University. His research interests include spatial data analysis and shopping behavior.