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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/50396

    Title: Mining marketing maps for business alliances
    Authors: 廖述賢;Liao, Shu-hsien;Chang, Wen-jung;Lee, Chai-chen
    Contributors: 淡江大學經營決策學系
    Keywords: Business alliance;Marketing maps;Database marketing;Data mining;Association rules;Knowledge extraction
    Date: 2008-10
    Issue Date: 2010-08-09 16:44:38 (UTC+8)
    Publisher: Oxford: Pergamon
    Abstract: A business can strengthen its competitive advantage and increase its market share by forming a strategic alliance. With the help of alliances, businesses can bring to bear significant resources beyond the capabilities of the individual co-operating firms. Thus how to effectively evaluate and select alliance partners is an important task for businesses because a successful corporation partner selection can therefore reduce the possible risk and avoid failure results on business alliance. This paper proposes the Apriori algorithm as a methodology of association rules for data mining, which is implemented for mining marketing map knowledge from customers. Knowledge extraction from marketing maps is illustrated as knowledge patterns and rules in order to propose suggestions for business alliances and possible co-operation solutions. Finally, this study suggests that integration of different research factors, variables, theories, and methods for investigating this research topic of business alliance could improve research results and scope.
    Relation: Expert Systems with Applications 35(3), pp.1338-1350
    DOI: 10.1016/j.eswa.2007.08.052
    Appears in Collections:[Department of Management Sciences] Journal Article

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