整合馬可夫鏈、貝氏決策及賽局理論探討工廠最適之產銷策略

A Study on Integrating Markov Chain, Bayesian Decision and Game Theory to Explore the Optimal Production and Marketing Strategy of the Factory

本研究針對工廠之生產製程，從原物料投入到最終良品產出，使用統計學信賴水準之方法，計算其投入與產出之轉換係數，並計算各生產系統中之資源投入量，進而計算出各項製程之單位成本，作為計算總成本、總收益及總利潤之基礎，以落實精實生產，進而提升經營績效。另一方面，本研究使用馬可夫鏈理論，對個案公司之產銷策略，進行動態分析，在該產業中，面對各家廠商採取不同產銷策略時，市場會產生哪些變化？這些變化是否會逐漸趨於穩定？其對總成本、總收益和總利潤又會產生哪些影響？最後，本研究使用貝氏決策理論及賽局理論之納許均衡分析，找出我方之最適策略，以達我方市場佔有率最大化或總期望利潤最大化之目標。

This study focuses on the factory’s production process, from raw material input to final good product output, using the statistical reliability level method to calculate the conversion coefficient between input and output, and calculate the amount of resource input in each production system, and then calculate the unit cost of each process using as the basis for calculating total cost, total revenue and total profit to implement lean production and thereby improve operating performance. On the other hand, this study uses Markov chain theory to conduct a dynamic analysis of the production and marketing strategies of the case company. In traditional industry, when various manufacturers adopt different production and marketing strategies, what changes will occur in the market? Will these changes gradually converge? Is the final result stable? What impact will happen on total cost, total revenue and total profit? Finally, this study uses the Nash equilibrium analysis of game theory and Bayesian decision theory to find the optimal strategy to achieve our goal. The goal is to maximize market share or maximize total expected profits.