Support of advanced technologies in supply chain processes and sustainability impact
This paper aims to present a study of the type of advanced technologies used across manufacturing supply chains in supporting the main processes of the supply chain operations reference model (SCOR). It also intends to identify a set of sustainable performance indicators (environmental, economic, an...
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Veröffentlicht in: | Applied sciences 2021-04, Vol.11 (7), p.1-26, Article 3026 |
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Sprache: | eng |
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Zusammenfassung: | This paper aims to present a study of the type of advanced technologies used across manufacturing supply chains in supporting the main processes of the supply chain operations reference model (SCOR). It also intends to identify a set of sustainable performance indicators (environmental, economic, and social) suitable to evaluate a supply chain 4.0 (SC4.0). To attain this objective, based on the literature review, a conceptual model is proposed. The multiple case study is used with a cross-case comparison to identify the type of advanced technologies more commonly used in SC4.0, and the performance indicators more suitable for assessing a SC4.0 sustainability performance. A sample of ten case studies was considered with companies belonging to different manufacturing SCs, from different countries, and belonging to different echelons. Main findings revealed that the level of adoption of advanced technologies in the Supply Chain SCOR processes varies amongst the case studies. Some technologies are quite commonly used among the several SCOR processes and companies while others are seldom applied. Some indicators were also identified that are regarded as very or extremely suitable to evaluate the sustainability performance of a SC4.0. The main contribution of this research to the body of knowledge is the empirical insights on the SC4.0 field and on Supply Chain Sustainability performance measurement. The results provide guidelines for the selection of advanced technologies to support SC processes and for the design of sustainable SC4.0 performance measurement systems.
This work has been funded by national funds through FCT—Fundação para a Ciência e a Tecnologia, I.P., Projects UIDB/05037/2020, UIDB/04058/2020 and UIDB/00319/2020. |
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ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app11073026 |