Recognizing Customer Knowledge Level towards Products for Recommendation in Electronic Commerce

Authors

S. Wesley Changchien, Institute of Electronic Commerce, National Chung Hsing University, Taichung, Taiwan, ROCFollow
Ru-Hui Huang, Department of Information Management, Chaoyang University of Technology, Taichung County, Taiwan, ROCFollow

Document Type

Article

Abstract

A powerful online recommendation system in Electronic Commerce (EC) must know its targeted customers well and employ effective marketing strategies. Market research is a very important way to know the customers well. For high-tech products with great variety such as computers, cellular phones, and digital cameras, customers’ knowledge level towards products may have a decisive influence on their purchase decision. While many online recommendation systems focus on utilizing data mining techniques in user profile and transaction data, this paper presents a method for recognizing customer knowledge level as a preprocess for more effective online recommendation in EC. The method consists of two Back Propagation Networks (BPN) and predicts based on customer characteristics and online navigation behaviors. A simple simulated digital camera EC store case study was conducted and the good preliminary result implies the good potential of the proposed method.

Recommended Citation

Changchien, S. Wesley and Huang, Ru-Hui, "Recognizing Customer Knowledge Level towards Products for Recommendation in Electronic Commerce" (2003). ICEB 2003 Proceedings (Singapore). 74.
https://aisel.aisnet.org/iceb2003/74