公平问题与竞争对供应链协调的互动影响

IF 1.8 Q3 MANAGEMENT Journal of Modelling in Management Pub Date : 2023-03-06 DOI:10.1108/jm2-07-2022-0162
Lirong Wang, Yingjie Lan, Deming N. Zhou
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引用次数: 1

摘要

供应链管理中的目的公平问题最近引起了OM研究界的广泛关注。然而,公平和竞争对供应链协调的综合影响以及它们之间的相互作用尚待彻底研究。设计/方法论/方法作者通过三人Stackelberg博弈模型研究了一个多人供应链,其中一个供应商和两个竞争零售商存在公平问题。这一理论研究提供了不同公平和竞争组合范围下的均衡解。除了理论分析外,作者还进行了标准的经济实验,并利用实验数据估算了结构参数。研究发现,在一定的公平竞争条件下,简单的批发价格可以协调整个供应链。此外,尽管公平问题总是降低批发价格,增加零售商的利润份额,但下游竞争削弱了这种影响,降低了下游参与者的市场份额。实验证实了公平问题的存在以及竞争与公平的相互作用,如理论分析所示。研究局限性/含义考虑到分配公平和同伴诱导公平的更全面的模型可以更好地了解竞争和公平的互动影响。此外,作者遵循了以前的渠道竞争文献,并用线性需求函数对需求进行建模,使博弈决策在闭式解中可跟踪。更通用的需求函数可能会产生不同的解决方案,从而产生新的见解。原创性/价值作者的工作对公平关注和竞争之间的相互作用进行了全面的理论研究,并阐明了文献中竞争效应和公平关注之间的深入联系。
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Interactive impact of fairness concerns and competition on supply chain coordination
Purpose Fairness concerns in the supply chain management have recently caught much attention in the OM research community. The combined effect of fairness and competition on supply chain coordination and the interplay between them, however, have yet to be thoroughly examined. Design/methodology/approach The authors study a multiplayer supply chain with one supplier and two competing retailers with fairness concerns by a three-player Stackelberg game model. This theoretical study provides equilibrium solutions under different ranges of fairness and competition combinations. Besides theoretical analysis, the authors also conduct standard economic experiments and estimate structural parameters using experimental data. Findings The authors find that a simple wholesale price can coordinate the whole supply chain with certain conditions of fairness and competition. Moreover, although fairness concerns always decrease the wholesale price and increase retailers' profit share, downstream competition weakens such effects and decreases downstream players' market share. The experiments confirm the existence of fairness concerns and the interaction of competition and fairness, as shown in the theoretical analysis. Research limitations/implications A more comprehensive model with both distributional and peer-induced fairness considered could generate better insights in the interactive impact of competition and fairness. Moreover, the authors followed the previous channel competition literature and modeled the demand with linear demand function which makes the game decisions trackable in closed form solution. A more general demand function could result in different solutions and thus new insights. Originality/value The authors’ work provides a comprehensive theoretical study of the interaction between fairness concerns and competition and clarifies the in-depth connection between the effects of competition and fairness concerns in the literature.
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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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