Managing Service Reputation with Vague Sets

By guaranteeing the requested Quality of Service (QoS), service providers can enhance consumer satisfaction and improve the service reputation as a result. However, non-functional QoS attributes such as consumer satisfaction and service reputation are not easily measured due to their complexity and the vagueness and imprecision inherent in the human decision-making process. Accordingly, the present study proposes a service evaluation model based on Dempster-Shafer evidence theory, in which the ambiguity in the evidence regarding the consumer satisfaction for a particular service is handled using the concept of vague sets. The global reputation score of a set of competing services is appropriately measured by synthesizing both the weights of criterion and the consumer satisfaction with QoS thru fuzzy aggregation. An example of cloud service selection is used to demonstrate the proposed approach. The validity of the proposed approach is demonstrated using a cloud service selection problem for illustration purposes. It is shown that the outranking results are identical to those obtained using the well-known TOPSIS method. Overall, the results show that the proposed method effectively handles the vagueness inherent in the human thought process and therefore provides a rational means of outranking a set of service alternatives based on the evidence provided in consumer feedback reports.