风险规避企业不完全细分市场中的过程均值选择与价格差异

IF 1.9 3区 工程技术 Q3 MANAGEMENT
Syed Asif Raza, Srikrishna Madhumohan Govindaluri
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引用次数: 0

摘要

在本文中,我们提出了一个优化工艺平均值、产品价格和生产数量的集成模型。这种优化是在考虑了不完全细分市场中价格差异的影响的情况下进行的,在这个市场中,需求泄漏很常见。通过抽样检验将生产过程生产的产品分配到两个细分市场。为了优化工艺平均值、定价和生产量,制定了一个多目标模型,该模型最大化(i)风险承受企业跨部门的预期总风险调整利润,(ii)满意度,即超过总风险调整预期利润目标的概率,以及(iii)两个相互冲突的目标,预期总风险调整利润和满意度。根据模型的复杂性,可以开发基于导数的闭式解或启发式解程序。这个问题在流程工业中得到了应用。对模型进行了详细的数值模拟,结果表明,风险规避程度越高,预期风险调整后的总利润越低,但实现目标利润的概率越高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Process mean selection and price differentiation in an imperfectly segmented market for a risk-averse firm
In this paper we propose an integrated model for optimising the process mean, the price of products, and the production quantity. This optimisation is conducted considering the impact of price differentiation in an imperfectly segmented market where demand leakages are common. The products that are produced by the production process are assigned to two market segments using sampling inspection. For optimisation of the process mean, pricing, and production quantities, a multi-objective model is formulated that maximises (i) The expected total risk-adjusted profit across segments for a risk-tolerant firm, (ii) The satisficing level, that is, the probability of exceeding a target set for total risk-adjusted expected profit, and (iii) The two conflicting objectives, expected total risk-adjusted profit and satisficing level. Depending on the complexity of models, either derivative-based closed form solutions or heuristic solution procedures are developed. The problem finds applications in process industries. A detailed numerical simulation is performed to corroborate the models, and it shows that a higher risk aversion results in a lower total expected risk-adjusted profit but a higher probability of achieving the target profit.
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来源期刊
IMA Journal of Management Mathematics
IMA Journal of Management Mathematics OPERATIONS RESEARCH & MANAGEMENT SCIENCE-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
CiteScore
4.70
自引率
17.60%
发文量
15
审稿时长
>12 weeks
期刊介绍: The mission of this quarterly journal is to publish mathematical research of the highest quality, impact and relevance that can be directly utilised or have demonstrable potential to be employed by managers in profit, not-for-profit, third party and governmental/public organisations to improve their practices. Thus the research must be quantitative and of the highest quality if it is to be published in the journal. Furthermore, the outcome of the research must be ultimately useful for managers. The journal also publishes novel meta-analyses of the literature, reviews of the "state-of-the art" in a manner that provides new insight, and genuine applications of mathematics to real-world problems in the form of case studies. The journal welcomes papers dealing with topics in Operational Research and Management Science, Operations Management, Decision Sciences, Transportation Science, Marketing Science, Analytics, and Financial and Risk Modelling.
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