行为代理模型:对运营和供应链研究的修正概念和启示

IF 2.8 4区 管理学 Q2 MANAGEMENT
Luis R. Gomez-Mejia, Geoff Martin, Veronica H. Villena, Robert M. Wiseman
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引用次数: 10

摘要

近年来的COVID - 19危机和地缘政治破裂凸显了运营和供应链管理(OSCM)对企业和社会的重要性。OSCM高管如何在不确定的情况下做出决策,他们如何平衡不同利益相关者的竞争需求?行为代理模型(BAM)在管理文献中得到了广泛的应用,它将高管作为分析单位,就像行为科学研究一样,将其嵌入其中;相比之下,许多供应链风险管理研究已经检查了公司层面的风险。我们回顾了BAM文献及其核心结构,改进了其原始预测,确定了可以利用BAM的OSCM执行决策上下文,并强调了使用BAM的研究机会。我们的目标是为进一步的风险研究提供一个平台,将BAM应用于OSCM执行决策领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The behavioral agency model: Revised concepts and implications for operations and supply chain research

The COVID 19 crisis and geopolitical ruptures of recent years have highlighted the importance of operations and supply chain management (OSCM) to firms and society. How do OSCM executives make decisions under uncertainty, and how do they balance the competing needs of various stakeholders? The behavioral agency model (BAM), which has been widely used in the management literature, focuses on the executive as the unit of analysis, like the behavioral science research in which it is embedded; by contrast, much of the supply chain risk management research has examined risk at the level of the firm. We review BAM literature and its core constructs, refine its original predictions, identify OSCM executive decision contexts that could take advantage of BAM, and highlight research opportunities using BAM. We aim to provide a platform for further risk research applying BAM in the domain of OSCM executive decision-making.

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来源期刊
DECISION SCIENCES
DECISION SCIENCES MANAGEMENT-
CiteScore
12.40
自引率
1.80%
发文量
34
期刊介绍: Decision Sciences, a premier journal of the Decision Sciences Institute, publishes scholarly research about decision making within the boundaries of an organization, as well as decisions involving inter-firm coordination. The journal promotes research advancing decision making at the interfaces of business functions and organizational boundaries. The journal also seeks articles extending established lines of work assuming the results of the research have the potential to substantially impact either decision making theory or industry practice. Ground-breaking research articles that enhance managerial understanding of decision making processes and stimulate further research in multi-disciplinary domains are particularly encouraged.
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