Article ID Journal Published Year Pages File Type
381732 Engineering Applications of Artificial Intelligence 2007 11 Pages PDF
Abstract

For a given service demand, it is necessary to select a suitable service provider among many possibilities. An accurate selection is difficult when consumers do not have a significant history with many of the service providers and thus need to interact with others to make informed selections. In traditional approaches, consumers rate the service providers and exchange these ratings among each other. Contrary to traditional, rating-based service provider selection, this paper advocates an objective, experience-based approach in which consumers record their experiences with service providers rather than the overall, subjective ratings. A consumer's experience with a provider captures the requested service and the delivered service in terms of service-specific attribute values. When an experience is transferred from one service consumer to another, the receiving consumer evaluates the experience using her own evaluation criteria. By sharing experiences, service consumers can model service providers accurately and thus make better selections for their needs. Rating-based strategies use highly subjective information for decision making since ratings depend on satisfaction criteria of the rater. However, the proposed method uses experiences, which do not include any interpretation. Comparisons of experience-based and rating-based strategies show that the experience-based approach results in higher customer satisfaction rates in many real-life settings.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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