Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/42337
標題: Assessing users' product-specific knowledge for personalization in electronic commerce
作者: 張樹之
Chang, S.E.
Changchien, S.W.
Huang, R.H.
關鍵字: personalization
electronic commerce
product knowledge
web usage
mining
artificial neural network
web site
recommendations
navigation
systems
model
期刊/報告no:: Expert Systems with Applications, Volume 30, Issue 4, Page(s) 682-693.
摘要: While many electronic commerce (EC) companies are adopting one-to-one marketing approaches using various personalization technologies to make their products and services unique for the purpose of attracting and retaining customers and improving their completion edges in the EC ecosystem, which, nevertheless, has low entrance barriers for new players to join and further intensify the competition, none or few of them consider a fundamental issue-the user's product-specific knowledge. Our research proposed to add this new domain of the customer's knowledge on appropriate target products into the personalization process as a part of the overall EC strategy for businesses. In this paper, we present our initial design for assessing the user's product-specific knowledge using the proposed innovative method for detecting it directly in a non-intrusive way without asking users to answer or fill out any types of questionnaires. Our method is based on customer's on-line navigation behaviors by analyzing their navigation patterns through pre-trained artificial neural networks. An empirical study designed for a case of EC store selling digital cameras was conducted in our research to prove the concept, and a good preliminary result was derived from the study. For the purpose of comparing the performances between the conventional approach of using questionnaire and the proposed innovative approach of navigation pattern mining, a questionnaire based approach for evaluating the user's product-specific knowledge was designed and incorporated into our knowledge level assessment system (KLAS). Our study result shows that although the pure questionnaire-based KLAS is intrusive and may not be accepted by some users, for those users willing to complete the questionnaire, the proposed navigation pattern approach can be combined with the questionnaire-based approach to create a hybrid KLAS which has a significantly improved accuracy rate in detecting the customer's product knowledge level. (c) 2005 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/11455/42337
ISSN: 0957-4174
文章連結: http://dx.doi.org/10.1016/j.eswa.2005.07.021
Appears in Collections:科技管理研究所

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