Abstract
This paper describes potential applications of multi-attribute preference models (MAPM) in e-commerce and offers some guidelines for their implementation. MAPM are methodologies for modeling complex preferences that depend on more than one attribute or criterion, and include multi-attribute utility theory, conjoint analysis, and the Analytic Hierarchy Process. There are numerous examples of applications in e-commerce that would benefit from the acquisition of information regarding the preferences of a consumer, a customer, an advice seeker, or a decision maker. Here, the focus is on applications of MAPM models in B2C and B2B websites, where preferences of consumers are assessed for the purpose of identifying products or services that closely match their needs. In this paper, we provide an overview of decision aids with the MAPM approach, emphasizing how the MAPM structure of an individual’s preferences may be assessed. This discussion is illustrated with examples of the use of alternative MAPM assessment approaches that are incorporated in existing websites. We then discuss how MAPM applications should be tailored for success in these environments.
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