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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68842


    Title: 檢驗奇摩拍賣平台 消費者跨商品類別的再購行為;Examine Consumer’s Repurchase Behavior across Product Categories of Yahoo! Auction Website
    Authors: 邢哲源;Hsing,Che-Yuan
    Contributors: 資訊管理學系
    Keywords: 再購行為;RFM模型;跨商品類別;Repurchase behavior;Across Product category;RFM model
    Date: 2015-07-28
    Issue Date: 2015-09-23 14:44:53 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 電子商務的競爭激烈,唯有忠誠的顧客才能為業者創造利潤,因此線上的賣家與平台業者都需要關注顧客的再購行為。過去針對單一商品類別的研究發現買家過去的消費行為,亦即RFM模型的變數,包括最近一次交易間隔天數、購買次數、總交易金額和平均交易金額均會影響顧客的再購行為。本研究透過跨商品類別交易資料的收集,目的在描述買家在不同的商品類別的消費行為和再購行為,並探討RFM模型變數對於消費者再購行為的影響是否有所不同。除了考慮顧客對於賣家的再購行為之外,也考慮顧客對於拍賣平台的再購行為。
    本研究蒐集自2014年10月至2015年3月奇摩拍賣所有商品類別的資料,包含買家和賣家配對的交易資料以及買家和平台配對的交易資料,使用羅吉斯迴歸分析探討RFM模型變數對賣家再購以及平台再購的影響。本研究發現所有商品類別的RFM變數均對賣家再購和平台再購有顯著的影響,也發現不同的商品類別,買家的再購行為表現會有所不同。本研究的主要貢獻為:(1)針對Yahoo!所有商品類別實證RFM模型可以用來預測消費者的再購行為;(2)消費者在Yahoo!的消費行為和再購行為的敘述統計可以做後續相關研究的對照和參考。
    ;With the severe competition in e-commerce, only loyal customers benefit e-business’s profitability. This is why sellers and e-marketplace businesses must concern online consumers’ repurchase behavior. Previous studies, focusing on single product category, have shown that the past consumption behavior of customers, i.e., the RFM model variables including the elapsed time since last trading, the number of purchases, the total monetary and the average monetary of transactions, affect customer’s repurchase behavior. This study aims to describe both consumer’s purchasing behavior and repurchase behavior across product categories, and examine the differences in the effects of RFM variables on repurchase behavior from both the seller’s perspective and e-marketplace perspective.
    In this study we collect all transactions data between buyers and sellers in all product categories of Yahoo! auction website from October 2014 to March 2015. Logistic regression analysis is used analyze the effects of RFM model variables on the repurchase behavior with respect to the seller and to the e-marketplace. We find that the effects of all RFM model variables are significant on the repurchase behavior from both perspectives across all product categories, and the differences in these effects are reported. The main contribution of this study are: (1) the appropriation of RFM model variables to predict the repurchase behavior is empirically examined and verified through all product categories of Yahoo! Auction website, (2) the descriptive statistics of the consumer’ s purchase behavior and repurchase behavior can be referenced by the relevant future studies in e-commerce.
    Appears in Collections:[資訊管理研究所] 博碩士論文

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