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Does Demographics Affect Purchase Frequency in Online Retail?

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  • Prateek Kalia

    (Department of Research, Innovation and Consultancy, I.K Gujral Punjab Technical University, Kapurthala, India)

Abstract

This research determines whether association exist between the demographic characteristics of online shoppers, such as education, age, gender, monthly income, occupation, marital status and their online purchase frequency. Web survey has been applied to 308 customers of four most popular e-retailers in India, who have made at least one online purchase in past six months. Based on extensive literature review hypotheses have been developed for six demographic factors i.e. education, age, income, occupation, marital status and gender. A chi-square test has been deployed to check association between demographic factors and purchase frequency. Significant association has been found between two demographic variables i.e. gender, occupation and purchase frequency. Further, a chi-square post hoc test via standard residual method confirmed that purchase frequency of 1-3 times in past six months by student customers contributes significantly to significant omnibus chi-square statistic.

Suggested Citation

  • Prateek Kalia, 2017. "Does Demographics Affect Purchase Frequency in Online Retail?," International Journal of Online Marketing (IJOM), IGI Global, vol. 7(2), pages 42-56, April.
    • Handle: RePEc:igg:jom000:v:7:y:2017:i:2:p:42-56
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJOM.2017040103
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    Cited by:

    1. Sotirios Zygiaris, 2022. "The Impact of Innovation Systems on E-commerce Capacity," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 276-289, March.
    2. Marcin Gąsior, 2021. "Environmental Attitudes and Willingness to Purchase Online—Classification Approach," Sustainability, MDPI, vol. 13(15), pages 1-17, August.
    3. Qing Zhu & Renxian Zuo & Shan Liu & Fan Zhang, 2020. "Online dynamic group-buying community analysis based on high frequency time series simulation," Electronic Commerce Research, Springer, vol. 20(1), pages 81-118, March.

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