Sourcing strategies for competing manufacturers in the toy industry

IF 1.8 Q3 MANAGEMENT

Journal of Modelling in Management Pub Date : 2023-09-14 DOI:10.1108/jm2-03-2023-0059

Peiyi Liang, Feng Yang, Feifei Shan

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Abstract

Purpose This paper aims to examine the optimal sourcing strategies and pricing decisions of competing toy manufacturers and to discuss how manufacturers’ decisions are impacted by competition. Design/methodology/approach The authors consider a single-period model to characterise the competition between two competing toy manufacturers. Both of them are free to choose between virgin material and recycled material. The authors consider two types of consumers: sensitive consumers who are concerned about product safety and prefer the toy made of virgin material and insensitive consumers who do not care what material is used in the toy. The competing manufacturers play a Cournot competition. Findings The results reveal a special case of a win-win situation for both the manufacturer and the consumer. In addition, an increasing number of sensitive consumers does not always raise the price of virgin-material toys. Practical implications The authors derive the manufacturer’s equilibrium sourcing strategies, corresponding market-clearing prices and profits obtained. Originality/value The paper investigates how toy manufacturers’ optimal sourcing strategies are impacted by competition, considering market segments.

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玩具行业竞争厂商的采购策略

本文旨在研究竞争玩具制造商的最优采购策略和定价决策，并讨论竞争对制造商决策的影响。设计/方法/方法作者考虑了一个单周期模型来描述两个相互竞争的玩具制造商之间的竞争。他们都可以自由选择原始材料和回收材料。作者考虑了两种类型的消费者:敏感的消费者，他们关心产品安全，更喜欢用原始材料制成的玩具;不敏感的消费者，他们不在乎玩具中使用的是什么材料。相互竞争的制造商进行古诺竞争。研究结果揭示了制造商和消费者双赢的特殊情况。此外，越来越多的敏感消费者并不总是提高原始材料玩具的价格。作者推导出制造商的均衡采购策略、相应的市场出清价格和获得的利润。本文在考虑市场细分的情况下，研究了竞争对玩具制造商最优采购策略的影响。

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

Journal of Modelling in Management MANAGEMENT-

CiteScore

5.50

自引率

12.50%

发文量

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.