A dynamic analysis of the firms in oligopoly market structure: a case study

IF 1.8 Q3 MANAGEMENT Journal of Modelling in Management Pub Date : 2024-08-09 DOI:10.1108/jm2-01-2024-0023
Reza Basiri, Mansour Abedian, Saeed Aghasi, Zahra Dashtaali
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Abstract

Purpose Over the last years, powerful advances in the area of dynamic games have enriched game theory and made it more applicable to the modeling of real-world competitive strategies. The study of strategic behaviors of firms in an oligopoly market has received little attention, even though real firms have been shown to compete in output and in price in a single industry. The purpose of this study is to propose a game-theoretic approach to studying strategic behaviors of firms in an oligopoly market structure. Design/methodology/approach This approach was developed to study market dynamics and pricing strategic behavior of firms that have the possibility of deciding to be one of the two types (price-maker or price-taker) and reconsider the choice overtime on the basis of their current insights and knowledge and their experience. Firms try to improve their performance in the competitive market in a strategic way, by considering their steady-state profits and choosing the best type given the other firms’ types, actions and interactions. Findings The results of the present study confirm the previous study that the Cournot market is a stable market, where each firm can be a price-maker and enjoy individual learning as well as social learning. On the contrary, the market with price-takers only is never stable, and, therefore, the Walrasian equilibrium may not be supported in some instances. The Cournot market loses its stability as the number of firms in the market increases due to the fact that it will be more profitable for a firm to switch to price-taking when the number of firms is high enough. In such a situation, when the number of price-takers increases, there are no stable markets and price dynamics are destabilized. Originality/value The study and modeling of real-world competitive strategies would enhance the understanding of oligopoly markets. The study of strategic behaviors of firms in an oligopoly market has received little attention, even though real firms have been shown to compete in output and in price in a single industry as price-takers and price-makers.
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寡头垄断市场结构中企业的动态分析:案例研究
目的在过去几年中,动态博弈领域取得的巨大进步丰富了博弈论,使其更适用于现实世界的竞争战略建模。对寡头垄断市场中企业战略行为的研究却鲜有人关注,尽管现实中的企业已经证明在单一行业中存在产量和价格竞争。本研究的目的是提出一种博弈论方法,用于研究寡头垄断市场结构中企业的战略行为。本方法旨在研究企业的市场动态和定价战略行为,这些企业有可能决定成为两种类型(价格制定者或价格接受者)中的一种,并根据其当前的洞察力、知识和经验随时重新考虑选择。本研究的结果证实了之前的研究,即库诺市场是一个稳定的市场,每个企业都可以成为价格制定者,并享受个人学习和社会学习。相反,只有价格接受者的市场从来都不稳定,因此,瓦尔拉斯均衡在某些情况下可能得不到支持。库诺市场会随着市场中企业数量的增加而失去稳定性,这是因为当企业数量足够多时,企业转为价格接受者会更有利可图。在这种情况下,当价格接受者的数量增加时,就不存在稳定的市场,价格动态也就不稳定了。原创性/价值对现实世界竞争战略的研究和建模将加深对寡头垄断市场的理解。对寡头垄断市场中企业战略行为的研究很少受到关注,尽管现实中的企业在单一行业中作为价格接受者和价格制定者进行产量和价格竞争。
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来源期刊
CiteScore
5.50
自引率
12.50%
发文量
52
期刊介绍: Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.
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