A Hybrid Simulation-based Duopoly Game Framework for Analysis of Supply Chain and Marketing Activities
Dong Xu, Chao Meng, Qingpeng Zhang, Puneet Bhardwaj, Young-Jun Son

TL;DR
This paper introduces a hybrid simulation framework combining system dynamics and agent-based modeling to analyze duopoly strategies in supply chain and marketing, addressing complex decision variables and consumer behaviors.
Contribution
It presents a novel simulation-based approach for duopoly game analysis that integrates multiple strategic decisions and consumer social network effects, surpassing traditional closed-form models.
Findings
Identification of pure strategy equilibriums in duopoly scenarios
Analysis of game stability, strictness, and robustness
Statistical validation of equilibrium outcomes
Abstract
A hybrid simulation-based framework involving system dynamics and agent-based simulation is proposed to address duopoly game considering multiple strategic decision variables and rich payoff, which cannot be addressed by traditional approaches involving closed-form equations. While system dynamics models are used to represent integrated production, logistics, and pricing determination activities of duopoly companies, agent-based simulation is used to mimic enhanced consumer purchasing behavior considering advertisement, promotion effect, and acquaintance recommendation in the consumer social network. The payoff function of the duopoly companies is assumed to be the net profit based on the total revenue and various cost items such as raw material, production, transportation, inventory and backorder. A unique procedure is proposed to solve and analyze the proposed simulation-based game,…
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