Abstract—In recent years, accidents and product recalls caused by product defects have become major problems in numerous industries worldwide. However, most of existing research studying product recalls adopted empirical approaches. To improve product recall systems, we studied social simulation using a multi-agent system with co-evolution model. This research is important, because empirical approaches are no longer adequate for the complex and diverse modern society. Discussions using quantitative and predictive approaches, including agent-based simulation, are therefore expected. In this study, we propose a new model: Money Importance Factor, for considering consumers’ diverse monetary sense. We conducted a simulation experiment, and we discovered the possibility that consumers are willing to buy more expensive and higher-quality products for preventing product accidents, when the products have a large risk of accidents apparently from their attributes. In addition, we have also found that it is important to make an impression or a recognition of product recalls better through improving social systems. We believe this work can contribute to supporting not only government staffs for improving product recall systems, but also executive officers of product companies for deliberating their strategy of recall decisions.
Index Terms—Evolutionary computation, human modeling, multi-agent simulation, multi-objective optimization.
Tetsuroh Watanabe and Kazuo Furuta are with the Department of Technology Management for Innovation, School of Engineering, the University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan (e-mail: watanabe@cse.t.u-tokyo.ac.jp, furuta@rerc.t.u-tokyo.ac.jp).
Taro Kanno is with the Department of Systems Innovation, School of Engineering, the University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan (e-mail: kanno@sys.t.u-tokyo.ac.jp).
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Cite: Tetsuroh Watanabe, Taro Kanno, and Kazuo Furuta, "Social Simulation for Analyzing Product Recall Systems Using Co-evolution Model Considering Consumers’ Diverse Monetary Sense," International Journal of Modeling and Optimization vol. 8, no. 1, pp. 46-54, 2018.
