Predictive models of intent to repurchase based on customer data

Hong Joo Lee ()

Edelweiss Applied Science and Technology, 2024, vol. 8, issue 4, 1174-1187

Abstract: As the business environment becomes ever more complex, predicting future buying patterns has become increasingly important. Moreover, there has been growth in the number of consumers focusing on health and self-care given rapid societal and economic changes. This shift is leading to heightened interest in athleisure wear and an increase in sales volume in this domain. It is accordingly necessary for companies in this field to establish marketing strategies based on predicting consumers’ future purchases to maintain continuous growth and competitiveness. This paper surveyed 400 consumers who purchased athleisure wear and established a predictive model for consumer buying behavior using Multivariate Discriminant Analysis. This paper found that a brand's authenticity and the purchaser’s involvement in sports were significant factors prediction customers’ repurchase behavior. Companies should accordingly engage in authentic business practices and consider clothing designs and marketing strategies that can connect consumers' daily lives with their sports activities.

Keywords: Authenticity; Intention to repurchase; Multivariate discriminant analysis. Sports involvement. (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:ajp:edwast:v:8:y:2024:i:4:p:1174-1187:id:1492

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