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Yi-lin Sun


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Journal of Zhejiang University SCIENCE A 2017 Vol.18 No.3 P.234-244


Diversity in diversification: an analysis of shopping trips in six-week travel diary data

Author(s):  Yi-lin Sun, Ari Tarigan, Owen Waygood, Dian-hai Wang

Affiliation(s):  School of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China; more

Corresponding email(s):   yilinsun@zju.edu.cn

Key Words:  Shopping behavior, Grocery shopping, Shopping locations and frequency, Shopping travel patterns, Shopping trips

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Yi-lin Sun, Ari Tarigan, Owen Waygood, Dian-hai Wang. Diversity in diversification: an analysis of shopping trips in six-week travel diary data[J]. Journal of Zhejiang University Science A, 2017, 18(3): 234-244.

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author="Yi-lin Sun, Ari Tarigan, Owen Waygood, Dian-hai Wang",
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%T Diversity in diversification: an analysis of shopping trips in six-week travel diary data
%A Yi-lin Sun
%A Ari Tarigan
%A Owen Waygood
%A Dian-hai Wang
%J Journal of Zhejiang University SCIENCE A
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%DOI 10.1631/jzus.A1500198

T1 - Diversity in diversification: an analysis of shopping trips in six-week travel diary data
A1 - Yi-lin Sun
A1 - Ari Tarigan
A1 - Owen Waygood
A1 - Dian-hai Wang
J0 - Journal of Zhejiang University Science A
VL - 18
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SP - 234
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A1500198

Diversification in shopping, a long-pursued subject in consumer behavior analysis, is approached from a broad perspective of the diversity in daily travel patterns, which may or may not involve shopping trips, as well as the diversity in shopping locations and frequency. The focus of this analysis is on the heterogeneity across individuals in the ways in which they each diversify their respective shopping behavior. This study explores differences across individuals in the variations of their shopping travel patterns across days. Treating the day-of-the-week evolution of shopping travel patterns as a stochastic process, characteristics of diversification are quantified for respective individuals. Finally, heterogeneity across individuals is identified using an array of statistical methods. The analysis, based on results of a six-week travel diary survey in Germany with geo-coded activity locations, reveals the effects of individual, household, and urban attributes on diversification in shopping behavior, including that full-time workers with medium incomes (4000–4999 Deutsche Mark per month) tend to have more variations in their shopping engagement.

The paper investigates the end consumers' attitudes and preferences in shopping activities. In particular, the effects due to living in different urban areas are also pointed out. The paper is well written and the analysis are well described. The results are very interesting and useful for understanding and improving urban planning.


创新点:1. 使用连续6周的数据进行动态交通行为分析;2. 建立二元逻辑回归模型,识别个体间购物出行模式的异质性。
方法:1. 通过描述性统计分析,解析不同群体之间的购物行为的差异、每周购物天数的分布以及每周每人购物天数的标准偏差(表1、图1和2);2. 通过回归模型分析,得出解释变量对购物地点和频率的影响结论(表2和3);3. 构建二元逻辑回归模型,识别个体间购物出行模式的异质性,找出具有常规购物行为的群体(表4)。
结论:1. 低收入和卡尔斯鲁厄居住地对日常购物目的地的多样性呈正影响关系,而全职工作和男性对日常购物目的地的多样性呈负影响关系;2. 连续6周的日常购物出行次数受到35~44岁的年龄范围、2500~2999德国马克的家庭月收入以及市中心居住地区的积极影响;3. 购物地点和频率的多样性是随着个人属性和居住地点以系统的方式变化。


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