標題: 電子商務推薦系統對消費者購物的接受行為之研究 -以新北市民為例
Consumer’s Behavior Intentions of Recommender Systems in E-Commerce - a Case Study of New Taipei City
作者: 莊筑鈞
包曉天
陳光華
Chuang, Chu-Chun
Pao, Hsiao-Tien
Chen, Guang-Hwa
管理科學系所
關鍵字: 電子商務;推薦系統;科技接受模型;E-Commerce;Recommender Systems;Technology Acceptance Model
公開日期: 2017
摘要: 智慧型手機的興起提升網路普及率,同時帶動電子商務交易額的成長。網路商店紛紛利用各種廣告向消費者傳播產品訊息,往往讓消費者面對龐大的資訊而無從選擇。推薦系統應運而生,依據消費者的喜好推薦相關的商品,幫助消費者做決策。不論是世界前幾大的網路零售商Amazon、Wal-Mart、Staples或是本土的Yahoo奇摩購物中心、PChome24h購物、博客來等等,無不希望提供更精準的推薦清單,增加消費者購買的機會。推薦系統隨著消費者的需求不斷演進,提供消費者不同的消費體驗。 本研究以Davis於1989年提出之科技接受模型(TAM)作為研究架構,將使用者特性及推薦系統特性視為外部變數,以結構方程式分析此兩類外部變數如何影響消費者使用推薦系統的態度及意願。其中,使用者特性以商品知識作為代表因子,推薦系統特性則以知覺準確性、商品多樣性以及商品新穎性三者作為代表因子。 研究發現,消費者越了解商品,會認為推薦系統越有用且越容易操作;消費者認為推薦系統越準確,會認為推薦系統越有用且越容易操作;推薦系統的商品越多樣化,消費者會認為推薦系統越有用;然而系統推薦越多新商品,並不會影響消費者對系統在有用程度及易用程度上的認知;有用程度及易用程度的認知會正向影響消費者的使用態度,進一步正向影響其使用意願。
The popularity of the mobile device gives rise to the growth of internet adoption and booms the e-commerce market. Numerous online stores make every effort to spread various advertisements, which make consumers be bombarded with the information and have difficulty making choices. Therefore, the recommender systems were invented and advise consumers what they need. Nowadays, Amazon, Wal-Mart, Staple, the world’s largest online retailers, contributing the recommender systems to stimulate the demand, so as the local online retailers in Taiwan like Yahoo shopping mall, PChome24h shopping, books.com., and so on. When the demand changes, the recommender systems will be improved and provide different consumer experiences. This study adopts the TAM model proposed by Davis (1989) as the framework and organizes the variables with exogenous variables such as user attributes and the features of system. The study uses Structural Equation Modeling to analyze the relationship between the variables and their impacts on the attitude and the intention. The user attribute is composed with the expertise. The features of system are composed with the perceived accuracy, the diversity and the novelty. The study finds out that user attributes affect both perceived ease of use and perceived usefulness significantly. Perceived accuracy affect both perceived ease of use and perceived usefulness significantly. The diversity affects perceived usefulness significantly. However, the novelty has no effect on the two variables. Perceived ease of use and perceived usefulness affect attitude and then affect behavior intention significantly as well.
URI: http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070453131
http://hdl.handle.net/11536/140774
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