Selecting the reliable supplier by using the advisor agents

Abstract

Purpose This paper aims to enhance the successful interaction between buyers and suppliers who use intelligent agents by presenting a computational model to detect the most reliable supplier agent according to advice of an advisor agent. Design/methodology/approach In this case, the authors study the most representative models in agent environments. According to these analysis criteria, a computational model was presented to compute the reliability of supplier agents and then select the most reliable one. To evaluate the proposed method, the experimentation was carried out in two stages. First, the average accuracy of model in computing the reliability was evaluated by comparing a random selection method. Second, the performance of the model in detecting the most reliable supplier was evaluated in an agent environment by applying trust network game as a simulator. Findings The experimental results revealed that the proposed method can detect the most reliable supplier accurately in both consistent and oscillating agent environments. Originality/value The authors believe that the proposed model will be beneficial to enhance the fulfillment of purchasing between buyers and suppliers.