Does e-shopping increase walking time willingness to reach in-store locations? Exploring the spatial effects

ABSTRACT

The studies analyzing the relationships between e-shopping and transport mostly ignore the effects in active mobility. This paper complements current research by studying how e-shopping affects individual walking time willingness to reach daily and non-daily retail opportunities, taking the city of Zaragoza, Spain as a case study. First, a questionnaire is administered, followed by a generalised ordered logit regression model analysis. Then, a gravity-based model is used to compare present walking accessibility levels to retail with an exploratory 2030 scenario based on the regression results. The results indicate a positive association between the frequency of e-shopping and the individual time willingness to reach daily and non-daily retail on foot. They also show that high-educated people tend to have lower time-willingness to reach both types of retail. For non-daily retail, women shopping online are more likely to spend more time on walking, while having children under 12 years old and having a car are negatively associated with walking time-willingness. The exploratory 2030 scenario shows a relevant increase of walking accessibility to daily and non-daily retail. The paper closes with a discussion on how the obtained findings can provide guidelines to improve policies that promote walking and active lifestyles.

KEYWORDS:

• Walkability; e-shopping; accessibility
• gravity-based model
• policymaking

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Family refers to those respondents who declared living single or in a couple but with children

2 The following question was used: “What is the maximum time that you are willing to walk to reach non-daily retail?” This is a translation from the original in Spanish into English.

3 “Daily retail” included food stores (e.g., bakeries, groceries). “Non-daily retail” included health and body care (e.g. gym, convenience store); leisure (e.g. cinema, bars); fashion (e.g. clothes, accessories, shoes); household goods (e.g. furniture, DIY stores); technology stores (e.g. computer stores, mobile phone); other retail (e.g. travel agency, car dealership).

4 The questionnaire did not include questions related to attitudes/preferences towards shopping. The authors are aware that and an endogeneity issue might exist.

Additional information

Funding

This work was supported by H2020 Marie Skłodowska-Curie Action ‘iCHRONOS: The effects of Information and Communications Technology on transport-related social exclusion for vulnerable populations’ [grant number 101026011] and ‘VIR2ALL: Virtual reality for simulating a new generation of collaborative future scenarios to integrate land use and transport’. Ministerio de Ciencia e Innovación. Gobierno de España [grant number PID2021-123954NB-C21].