A service-oriented analysis of online product classification methods

Authors:
Melody Y. Kiang;Qiang Ye;Yuanyuan Hao;Minder Chen;Yijun Li
Affiliations:
Information Systems Department, College of Business Administration, California State University, Long Beach, United States;School of Management, Harbin Institute of Technology, China;Department of Information Technology Management, Agricultural Bank of China, No. 69, Jianguomen NeiAvenue, Dongcheng District, Beijing, China;Martin V. Smith School of Business and Economics, California State University Channel Islands, United States;School of Management, Harbin Institute of Technology, China
Venue:
Decision Support Systems
Year:
2011

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Abstract

Studies of Internet market have found that consumers' purchasing behaviors including information search, channel selection, and brand evaluation processes are impacted by the product/service types. In this research, we perform a comprehensive review of existing online product classification methods. An in-depth analysis of the rationale behind each method was studied, and important product characteristics were determined for integrating different approaches. Grounded on the theory of the components of perceived risk in product purchase and the recently emerged service science, the integrated classification will help companies to better understand the online consumer purchasing behavior and to design their e-commerce strategies accordingly. Survey results indicate that the integrated classification is an effective way to classify products and services marketed on the Internet.