4.7 Article

A method for analyzing the daily variation in the spatial pattern of market area

期刊

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jretconser.2020.102336

关键词

Destination; Visitors; Market area analysis; Daily pattern

类别

资金

  1. JSPS KAKENHI [16H01830, 18K18535, 19H02375]
  2. Grants-in-Aid for Scientific Research [19H02375, 18K18535, 16H01830] Funding Source: KAKEN

向作者/读者索取更多资源

Market area analysis is an important research topic, but the daily patterns have not been fully analyzed. The market area is larger on weekends and smaller on Christmas days. A new procedure with three measures and statistical methods has been proposed to evaluate and visualize the spatial differences in market areas between different days.
Market area analysis has long been an important research topic in retailing, marketing, and geography. Numerous studies have been conducted in the literature to describe and understand the market area and consumers' behavior. The daily pattern of the market area, however, has not yet been fully analyzed. The market area of department stores and shopping malls is larger on weekends than on weekdays. Many shops and restaurants are closed on Christmas days, which shrinks the market area of shopping malls. To describe and grasp these patterns, this paper proposes a new procedure for analyzing the daily pattern of the market area. Three measures evaluate the difference in the market area between different days and the variation within a day group. A loglikelihood based statistical measure visualizes the spatial difference in the market area between different days. A method for detecting anomalous days on which the market areas are quite different from those of other days. The proposed procedure is applied to the analysis of the visitors of five towns in Tokyo. The results indicate the effectiveness of the procedure as well as provide useful findings for understanding the daily pattern of visitors to the towns.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据