Evaluating the Utility of Web-Based Consumer Support Tools Using Rough Sets

On the Web, many popular e-commerce sites provide consumers with decision support tools to assist them in their commerce-related decision-making. Many consumers will rank the utility of these tools quite highly. Data obtained from web usage mining analyses, which may provide knowledge about a user’s online experiences, could help indicate the utility of these tools. This type of analysis could provide insight into whether provided tools are adequately assisting consumers in conducting their online shopping activities or if new or additional enhancements need consideration. Although some research in this regard has been described in previous literature, there is still much that can be done. The authors of this paper hypothesize that a measurement of consumer decision accuracy, i.e. a measurement preferences, could help indicate the utility of these tools. This paper describes a procedure developed towards this goal using elements of rough set theory. The authors evaluated the procedure using two support tools, one based on a tool developed by the US-EPA and the other developed by one of the authors called cogito. Results from the evaluation did provide interesting insights on the utility of both support tools. Although it was shown that the cogito tool obtained slightly higher decision accuracy, both tools could be improved from additional enhancements. Details of the procedure developed and results obtained from the evaluation will be provided. Opportunities for future work are also discussed.