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Article
Publication date: 25 April 2024

Minghuan Shou, Furong Jia and Jie Yu

The aging population, a higher proportion of older adults (aged 65+), is considered a global and severe problem, while the information systems (IS) literature on detecting the…

Abstract

Purpose

The aging population, a higher proportion of older adults (aged 65+), is considered a global and severe problem, while the information systems (IS) literature on detecting the relationship between the aging population and the development of electronic commerce (e-commerce) is limited and insufficient. Hence, the main objective of this paper is to examine whether an aging population can moderate the effect of infrastructure constructions on e-commerce sales and whether an aging population can affect e-commerce sales.

Design/methodology/approach

To investigate the relationship between the aging population and e-commerce sales, this study proposes two potential influential mechanisms: moderating the effects of infrastructure development on e-commerce sales and direct influence. Subsequently, a sample of 31 Chinese provinces from 2013 to 2019 is utilized to conduct regression analyses in order to examine these hypotheses.

Findings

The findings suggest that the development of urban transportation infrastructure and network constructions can significantly contribute to the enhancement of e-commerce sales, and the influence cannot be affected by aging population. Furthermore, it is noteworthy that an aging population can have a positive effect on e-commerce sales.

Practical implications

The findings can inform future infrastructure constructions by assessing the potential of infrastructure projects to boost e-commerce sales and examining whether this effect varies in an aging population context.

Originality/value

The findings substantiate the pivotal role of older adults in the e-commerce industry. Moreover, the obtained results establish a positive relationship between an aging population and e-commerce sales, thereby offering diverse perspectives on existing theories.

Details

Industrial Management & Data Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-5577

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