Michiya Morita, Jose A. D. Machuca, Juan A. Marin-Garcia, Rafaela Alfalla-Luque
{"title":"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","authors":"Michiya Morita, Jose A. D. Machuca, Juan A. Marin-Garcia, Rafaela Alfalla-Luque","doi":"10.1007/s12063-024-00474-4","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":46120,"journal":{"name":"Operations Management Research","volume":"7 1","pages":""},"PeriodicalIF":6.9000,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Drivers of supply chain adaptability: insights into mobilizing supply chain processes. A multi-country and multi-sector empirical research\",\"authors\":\"Michiya Morita, Jose A. D. Machuca, Juan A. Marin-Garcia, Rafaela Alfalla-Luque\",\"doi\":\"10.1007/s12063-024-00474-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":46120,\"journal\":{\"name\":\"Operations Management Research\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-04-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Management Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s12063-024-00474-4\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Management Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s12063-024-00474-4","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
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.
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.