A. Makui, S. Seyedhosseini, P. Esmaeili, S. Sadjadi
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Analysis of Labor-Management Negotiation based on Chicken Evolutionary Game and Catastrophe Theory
This paper aims to conduct a research on the labor-management negotiation in chicken evolutionary game models through catastrophe theory. The both players can compromise or not during the negotiation. The "no compromise" strategy for labor means threat to strike and for management is ignoring labors' demands. Since the model of this research is chicken game, if on player decides to dig in, the optimum decision for other is to compromise, however it is costly to be calling a chicken by the rivals. In the process of evolution, players reevaluate their options to update the payoffs in case of gradual and continuous changes which may happen in effective variables of strategy selection. The continuous changes could cause a catastrophic change in system’s state and its collapse by a strike or lockout. ESS analysis and determining catastrophe threshold in the chicken evolutionary game will be done with the aim of giving managerial insights that help the players to prevent making decisions that could cause unsuccessful negotiation.
期刊介绍:
Journal of Industrial Engineering International is an international journal dedicated to the latest advancement of industrial engineering. The goal of this journal is to provide a platform for engineers and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of industrial engineering. All manuscripts must be prepared in English and are subject to a rigorous and fair peer-review process. Accepted articles will immediately appear online. The journal publishes original research articles, review articles, technical notes, case studies and letters to the Editor, including but not limited to the following fields: Operations Research and Decision-Making Models, Production Planning and Inventory Control, Supply Chain Management, Quality Engineering, Applications of Fuzzy Theory in Industrial Engineering, Applications of Stochastic Models in Industrial Engineering, Applications of Metaheuristic Methods in Industrial Engineering.