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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/124135
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/124135

    Title: 零售購物籃的連結與群集分析
    Analysis of Links and Communities in Retail Market Basket
    Authors: 黃懷萱
    Huang, Huai-Hsuan
    Contributors: 莊皓鈞

    Chuang, Hao-Chun
    Chou, Yen-Chun

    Huang, Huai-Hsuan
    Keywords: 購物籃分析
    Market basket analysis
    Product network analysis
    Community detection
    Social network analysis
    Date: 2019
    Issue Date: 2019-07-01 10:46:27 (UTC+8)
    Abstract: 本研究發展一套應用社群網路分析於零售業的併買分析方法,實際以國內知名便利商店之產品交易資料進行實作。首先,透過不同的權重設計表達產品併買的實際強度及金流,並賦予權重意義。此外,透過社群偵測分析產品的併買關係,若產品間的關係緊密則自成一群,並針對劃分後的社群衡量每一群體的價值與重要性。接著,更進一步以網路中心性為衡量指標找出關鍵產品與橋樑產品。最後,則透過最長鏈結關係,找出產品間除了直接併買關係之外的間接併買關係。透過這一套分析方法能清楚地探討產品交易數據中的併買關係及找出網路中具有價值的社群與產品,以協助零售業者對於交易資料能有更全面的分析與應用,進而制定更完善的決策和推出更貼近消費者需求的行銷策略與活動,提升企業的營收與獲利。
    This research develops a set of techniques for analysis of co-purchased in the retail industry using social network analysis (SNA), and actually implements those techniques on the transaction data from the domestic well-known convenience stores. First, different weighting methods are used to express the actual strengths and cash flows of co-purchased products. In addition, this research uses the community detection to identify co-purchased products from transaction data. If a set of products are frequently purchased together, they form a self-contained community whose internal connections are stronger than external connections. Also, the value and importance of each community will be measured. This research further uses the metrics from the network analysis to identify roles of products among communities. Finally, on top of products purchased together, this research uses the longest link to identify the indirect relationships of co-purchased products. Overall, this research aims to propose an analysis method to better understand co-purchased products from the transaction data. We visually represent co-purchased products using product network, evaluate networks via different weights, and discover relationships among products from the network. The proposed method should help retailers better understand their transaction data, and hence provide information to improve their marketing strategies.
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    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G1063560062
    Data Type: thesis
    DOI: 10.6814/THE.NCCU.MIS.005.2019.A05
    Appears in Collections:[資訊管理學系] 學位論文

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