Mining Customer Shopping Behavior: A Method Encoding Customer Purchase Decision Attitude

Hsiao-ping Yeh and Tsung-Sheng Chang
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Hsiao-ping Yeh: Department of Marketing and Distribution Management, National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan
Tsung-Sheng Chang: Department of Information Management, Da-Yeh University, Changhua, Taiwan

International Journal of Information Systems in the Service Sector (IJISSS), 2018, vol. 10, issue 1, 16-27

Abstract: Mining customer shopping data is able for business managers to understand and predict customer behavior. However, most practices are focusing on the purchasing goods, i.e. basket analysis. This article collects customer shopping data by observation to systematically discover customer shopping pattern incorporating with customer's purchasing decision time. With Apriori algorithm and the proposed customer purchasing decision pattern examining principle, customer purchase behaviors of with decision attitudes are revealed. This article gets insights at decomposing support and confidence values of an association rule. With the proposed encoding method, decision attitudes on goods in the association rule can be interpreted.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jisss0:v:10:y:2018:i:1:p:16-27

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