S
Sachin S. Kamble
Researcher at EDHEC Business School
Publications - 112
Citations - 6435
Sachin S. Kamble is an academic researcher from EDHEC Business School. The author has contributed to research in topics: Supply chain & Multiple-criteria decision analysis. The author has an hindex of 22, co-authored 94 publications receiving 2612 citations. Previous affiliations of Sachin S. Kamble include National Institute of Industrial Engineering.
Papers
More filters
Journal ArticleDOI
Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives
TL;DR: A systematic and extensive review of research that captures the dynamic nature of industry 4.0 has been presented in this article, where 85 papers were classified in five research categories namely conceptual papers on Industry4.0, human-machine interactions, machine-equipment interactions, technologies of Industry 4., and sustainability.
Journal ArticleDOI
Understanding the Blockchain technology adoption in supply chains-Indian context
TL;DR: This paper develops, and statistically validates a model for understanding the user perceptions on BT adoption, based on the integration of three adoption theories- technology acceptance model (TAM), technology readiness index (TRI), and the theory of planned behaviour (TPB).
Journal ArticleDOI
Modeling the blockchain enabled traceability in agriculture supply chain
TL;DR: The findings from the study suggest that traceability was the most significant reason for BT implementation in ASC followed by auditability, immutability, and provenance, which will help the practitioners to design the strategies forBT implementation in agriculture, creating a real-time data-driven ASC.
Journal ArticleDOI
Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications
TL;DR: In this paper, the authors proposed an application framework for the practitioners involved in the agri-food supply chain that identifies the supply chain visibility and supply chain resources as the main driving force for developing data analytics capability and achieving the sustainable performance.
Journal ArticleDOI
Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry
TL;DR: This study is first of its kind to identify industry 4.0 adoption barriers and develop hierarchical relationships between them using interpretive structural modeling (ISM) and fuzzy MICMAC methodology in the Indian manufacturing context.