供应链适应性的驱动因素:供应链流程动员的启示。多国多部门实证研究

IF 6.9 2区 管理学 Q1 MANAGEMENT
Michiya Morita, Jose A. D. Machuca, Juan A. Marin-Garcia, Rafaela Alfalla-Luque
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引用次数: 0

摘要

供应链(SC)适应性(SC-Ad)意味着供应链流程应根据预期的结构和市场变化进行改变和调整。然而,当这些变化涉及到从以开发为主向以探索为主的转变时,企业就会因其中的不确定性而面临缺乏灵活性的问题,从而对获得供应链适应性造成障碍。本研究建议通过整合产品/市场战略和 SC 流程的新组合,并确保它们随着时间的推移相匹配,来克服这一障碍。为此,本研究提出了两个 SC-Ad 驱动因素(与 SC 流程(ASCOS)和新产品开发能力(PDC)相关),通过减少不确定性来确保上述契合度,从而确保 SC-Ad 能够应对新出现的竞争变化。根据 PLS-SEM 对测量模型和结构模型进行了评估。ASCOS 和 PDC 的相对重要性采用重要性/性能/分析程序进行分析。使用 PLS、PLS-predict 和 CVPAT 分析模型的样本内和样本外预测能力。方差分析用于比较不同植物组中的 SC-Ad、ASCOS 和 PDC。结果表明,ASCOS 和 PDC 是 SC-Ad 的驱动因素,SC-Ad 值最高的植物是那些 ASCOS 和 PDC 值较高的植物。这拓展了有关 SC-Ad 驱动因素的知识,而这正是一个重要的文献空白。这也间接地为 "双向管理 "这一主题增添了一些新的亮点。a) 268 家工厂的广泛的多国家、多信息和多部门样本,b) 良好的样本外模型预测能力,c) 无异质性问题,这些都支持了这些结果的充分普适性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Drivers of supply chain adaptability: insights into mobilizing supply chain processes. A multi-country and multi-sector empirical research

Drivers of supply chain adaptability: insights into mobilizing supply chain processes. A multi-country and multi-sector empirical research

Supply chain (SC) adaptability (SC-Ad) implies that SC processes should change and adapt to anticipated structural and market changes. However, when these changes are related to shifts from exploitative to explorative focuses, companies face an inflexibility problem because of involved uncertainties, creating a barrier to obtaining SC-Ad. This research proposes to overcome this barrier by integrating new combinations of the product/market strategy and SC processes and securing their fit over time. To get it, this study proposes two SC-Ad drivers (related to the SC process (ASCOS) and new product development competences (PDC)), which secure the aforementioned fit by reducing its uncertainties and thus ensuring a SC-Ad that responds to emerging competitive changes. Measurement and structural models were assessed following PLS-SEM. ASCOS and PDC’ relative importance was analyzed using the importance/performance/analysis procedure. PLS, PLS-predict, and CVPAT were used to analyze model’s in-sample and out-of-sample predictive capacity. ANOVA was used to compare SC-Ad, ASCOS and PDC in different plant groups. Results suggest that ASCOS and PDC are SC-Ad’s drivers, and that the plants with highest SC-Ad values are those with the higher ASCOS and PDC’ values. This expand knowledge about SC-Ad drivers, which represents an important literature gap. In an indirect way, some new light is also added to the topic of ambidextrous management. The adequate generalizability of these results is supported by a) a wide multi-country, multi-informant, and multi-sector sample of 268 plants, b) a good out-of-sample model predictive capacity c) no heterogeneity issues.

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来源期刊
CiteScore
6.20
自引率
23.30%
发文量
104
期刊介绍: Operations Management Research is a peer-reviewed journal that focuses on rapidly publishing high-quality research in the field of operations management. It aims to advance both the theory and practice of operations management across a wide range of topics and research paradigms. The journal covers all aspects of operations management, including manufacturing, supply chain, health care, and service operations. It welcomes various research methodologies, such as case studies, action research, surveys, mathematical modeling, and simulation. The goal of Operations Management Research is to promote research that enhances both the theory and practice of operations management, as it is an applied discipline. The journal also publishes Academic Notes, which are special papers that address research methodologies, the direction of the operations management field, and other topics of interest to academicians. Additionally, there is a demand for shorter and more focused research articles in operations management, which this journal aims to fulfill.
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