Do wholesale pricing strategies matter during asymmetric disruptions? A game theoretic analysis

IF 1.8 Q3 MANAGEMENT Journal of Modelling in Management Pub Date : 2023-08-29 DOI:10.1108/jm2-12-2022-0289
S. Raju, Rofin T.M., P. S, Jagan Jacob
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Abstract

Purpose In most economies, there are rules from the market regulators or government to sell at an equal wholesale price (EWP). But when one upstream channel is facing a negative demand disruption and another positive, EWP can create extra pressure on the disadvantageous supply chain partner, which faces negative disruption. The purpose of this study is to analyse the impact of EWP and the scope of the discriminatory wholesale price (DWP) during disruptions. Design/methodology/approach For the study, the authors used a dual-channel supply chain consisting of a manufacturer, online retailer (OR) and traditional brick-and-mortar (BM) retailer. Stackelberg game is used to model the interaction between the upstream and downstream channel partners, and the horizontal Nash game to analyse the interaction within downstream channel partners. For modelling asymmetric disruption, the authors took instances from the lock-down and post-lock-down periods of the COVID-19 pandemic, where consumers flow from BM retailer to OR store. Findings By analysing the disruption period, the authors found that this asymmetric disruption is detrimental to the BM channel, favourable to OR and has no impact on the manufacturer. But with DWP, the authors found that the profit of the BM channel and manufacturer can be increased during disruption. Though the profit of the OR decreased, it was found to be higher than in the pre-disruption period. Under DWP, the consumer surplus increased during disruption, making it favourable for the customers also. Thus, DWP can aid in creating a win-win strategy for all the supply chain partners during asymmetric disruption. Later as an extension to the study, the authors analysed the impact of the consumer transfer factor and found that it plays a crucial role in the optimal decisions of the channel partner during DWP. Originality/value Very scant literature analyses the intersection of DWP and disruptions. To the best of the authors’ knowledge, this study, for the first time uses DWP as a tool to help the disadvantageous supply chain partner during asymmetric disruptions. The study findings will assist the government, market regulators and manufacturers in revamping the wholesale pricing policies and strategies to help the disadvantageous supply chain partner during asymmetric disruption.
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在不对称中断期间,批发定价策略是否重要?博弈论分析
目的在大多数经济体中,市场监管机构或政府都有以同等批发价格出售的规定。但是,当一个上游渠道面临负面需求中断,而另一个则面临正面需求中断时,EWP可能会给面临负面中断的不利供应链合作伙伴带来额外压力。本研究的目的是分析EWP的影响以及中断期间歧视性批发价格(DWP)的范围。设计/方法/方法在本研究中,作者使用了由制造商、在线零售商(OR)和传统实体零售商(BM)组成的双渠道供应链。Stackelberg对策用于对上下游渠道伙伴之间的互动进行建模,水平Nash对策用于分析下游渠道伙伴内部的互动。为了模拟非对称破坏,作者从新冠肺炎疫情的封锁期和封锁后时期入手,消费者从BM零售商流向OR商店。结果通过分析中断期,作者发现这种不对称中断对BM通道不利,有利于OR,对制造商没有影响。但通过DWP,作者发现BM渠道和制造商的利润可以在中断期间增加。尽管OR的利润有所下降,但发现其高于中断前的时期。在DWP下,消费者盈余在中断期间增加,这也有利于客户。因此,DWP可以帮助在不对称中断期间为所有供应链合作伙伴制定双赢战略。后来,作为该研究的延伸,作者分析了消费者转移因素的影响,发现它在DWP期间对渠道合作伙伴的最佳决策起着至关重要的作用。原创性/价值很少有文献分析DWP和中断的交叉点。据作者所知,本研究首次将DWP作为一种工具,在不对称中断期间帮助不利的供应链合作伙伴。研究结果将有助于政府、市场监管机构和制造商修改批发定价政策和战略,以在不对称中断期间帮助不利的供应链合作伙伴。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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