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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/77272

    Title: Analysis on repeat-buying patterns
    Authors: Chiang, Ding-An;Wang, Yi-Hsin;Chen, Shao-Ping
    Contributors: 淡江大學資訊工程學系
    Keywords: Sequential pattern mining;Periodic mining;Repeat-buying behavior;Temporal data mining;Time interval sequential pattern
    Date: 2010-12
    Issue Date: 2012-06-14 10:16:31 (UTC+8)
    Publisher: Amsterdam: Elsevier BV
    Abstract: Consumer market has several characteristics in common such as repeat-buying over the relevant time frame, a large number of customers, and a wealth of information detailing past customer purchases. Analyzing the characterizations of repeat-buying is necessary to understand and adapt to dynamics of customer behaviors for company to survive in a continuously changing environment. The aim of this paper is to develop a methodology to detect the existence of repeat-buying behavior and discover the potential period of the repeat-buying behavior. We propose a new mathematical model to capture the characteristics of repeat-buying behavior. The algorithms based on our previous works then proposed to provide a scheme to discover periodicity and trends of the purchase. Two fundamental repeat-buying types have been identified and analyzed. Any repeat-buying scenarios can be expressed as the combination of the two fundamental types. The proposed mathematical model coupled with our prior works on cyclic modeling form a systematic process to uncover the characteristics of repeat-buying phenomenon. The experiments against a domestic consumer goods company are provided. The experimental results show that the proposed model can predict likely periodic purchase more precisely than previous studies.
    Relation: Knowledge-Based Systems 23(8), pp.757-768
    DOI: 10.1016/j.knosys.2010.04.012
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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