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

Operations Management Research(2024)

引用 0|浏览0
暂无评分
摘要
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.
更多
查看译文
关键词
Supply chain adaptability,Supply chain processes’ inflexibility,Product development,Product/market strategy,Ambidextrous management,High performance manufacturing,PLS
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要