企业的目标。双标准分析与谈判问题

Q4 Engineering
J. Gadomski, L. Kruś
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引用次数: 0

摘要

摘要考虑一个企业的决策过程,其中两个共存的利益集团追求不同的目标。提出了一个基于非新古典生产函数的原始模型。该函数满足R.Frisch提出的条件,这使得研究企业在远离完全竞争的环境中运营并追求利润最大化之外的目标成为可能。提出了一个双准则优化问题,其中两个准则代表了集团的目标:利润最大化和企业相对于资本和劳动力产生的收入最大化。这个问题是在产品市场的两种变体中考虑的,即完全竞争和不完全竞争。分析了问题的解决方案,包括导出的Pareto集。阐述和讨论了帕累托集合知识在企业利益集团之间谈判中的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Objectives of an enterprise. Bi-criteria analysis and negotiation problems
Abstract A decision-making process is considered for a firm, in which two coexisting groups of interests pursue different goals. An original model based on a non-neoclassical production function is proposed. The function satisfies the conditions formulated by R. Frisch, which makes it possible to investigate firms operating in the environment far from the perfect competition and pursuing goals other than profit maximization. A two-criteria optimization problem is formulated with the two criteria representing the goals of the groups: maximization of profit and maximization of income generated by the firm with respect to capital and labor. The problem is considered in two variants of the product market, namely the perfect and the imperfect competition. Solutions of the problem are analyzed including the derived Pareto sets. The importance of knowledge about the Pareto set in negotiations between the groups of interests in the firm is illustrated and discussed.
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来源期刊
Control and Cybernetics
Control and Cybernetics 工程技术-计算机:控制论
CiteScore
0.50
自引率
0.00%
发文量
0
期刊介绍: The field of interest covers general concepts, theories, methods and techniques associated with analysis, modelling, control and management in various systems (e.g. technological, economic, ecological, social). The journal is particularly interested in results in the following areas of research: Systems and control theory: general systems theory, optimal cotrol, optimization theory, data analysis, learning, artificial intelligence, modelling & identification, game theory, multicriteria optimisation, decision and negotiation methods, soft approaches: stochastic and fuzzy methods, computer science,
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