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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/115825

    Title: Big data analysis on the business process and management for the store layout and bundling sales
    Authors: Shu-hsien Liao;Yi-Shan Tasi
    Keywords: Retailing;Business process management;Big data;Database management;Bundling sales, Data mining
    Date: 2019-10-31
    Issue Date: 2019-02-23 12:12:26 (UTC+8)
    Abstract: Purpose – In the retailing industry, database is the time and place where a retail transaction is completed.
    E-business processes are increasingly adopting databases that can obtain in-depth customers and sales
    knowledge with the big data analysis. The specific big data analysis on a database system allows a retailer
    designing and implementing business process management (BPM) to maximize profits, minimize costs and
    satisfy customers on a business model. Thus, the research of big data analysis on the BPM in the retailing is a
    critical issue. The paper aims to discuss this issue.
    Design/methodology/approach – This paper develops a database, ER model, and uses cluster analysis,
    C&R tree and the a priori algorithm as approaches to illustrate big data analysis/data mining results for
    generating business intelligence and process management, which then obtain customer knowledge from the
    case firm’s database system.
    Findings – Big data analysis/data mining results such as customer profiles, product/brand display
    classifications and product/brand sales associations can be used to propose alternatives to the case firm for
    store layout and bundling sales business process and management development.
    Originality/value – This research paper is an example to develop the BPM of database model and big data/
    data mining based on insights from big data analysis applications for store layout and bundling sales in the
    retailing industry.
    Relation: Business Process Management Journal 25(7), p.1783-1801
    DOI: 10.1108/BPMJ-01-2018-0027
    Appears in Collections:[Department of Management Sciences] Journal Article

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