ABSTRACT
This study investigates the importance of the determinants affecting the adoption and usage of blockchain-based SCM systems in the context of organizations. Hence, an SLR method was followed to uncover critical determinants in the literature. Then, a research model, including 14 key determinants, was developed based on the TOE Framework. Subsequently, the AHP method was applied to rank the adoption determinants. The findings reveal that environment-related determinants are more critical than technology-related or organization-related determinants.
Additional information
Notes on contributors
Ebru Gökalp
Dr. Ebru Gökalp is a Visiting Academic Fellow at the University of Cambridge, Institute for Manufacturing. Her research interests include digital transformation, business process improvement, business model innovation, software engineering, and management information systems. She received her BS and MS degrees in Industrial Engineering and her PhD degree in Information Systems. Her PhD thesis and working experiences are related to the development of maturity models to guide organizations by assessing their current process capability levels and providing a roadmap for improvement. She is currently an Assistant Professor at Baskent University, Ankara, and also teaching part-time at METU Informatics Institute.
Mert Onuralp Gökalp
Mert Onuralp Gökalp is a PhD Candidate at Informatics Institute in Middle East Technical University, Turkey. His research areas include Data Science, Big Data and, Machine Learning. In Msc, his project was about providing a visual programming model upon big data tools to increase user adoption of big data analytics in IoT domain. Currently, he investigates adoption of data science in businesses to extend benefits that gained from data science. He received his BS degree in Computer Science and Engineering, and Msc. degree in Information Systems. Currently, he is working as a full-time researcher in Middle East Technical University.
Selin Çoban
Selin Çoban received his B.Sc. degree in Biomedical Engineering. Her research areas include data science, big data, machine learning and blockchain. Currently, she is a PhD student and working as a full-time researcher in Informatics Institute at METU.