| Title |
Blockchain-Based Security Factors on Sustainable Supply Chain Management in UK Manufacturing Firms: A Hybrid SEM-ANN Approach |
| ID_Doc |
17311 |
| Authors |
Ali, RF; Jahankhani, H; Ali, K; Hassan, B |
| Title |
Blockchain-Based Security Factors on Sustainable Supply Chain Management in UK Manufacturing Firms: A Hybrid SEM-ANN Approach |
| Year |
2024 |
| Published |
Systems, 12, 6 |
| DOI |
10.3390/systems12060208 |
| Abstract |
Recently, there has been a notable surge in the intricate complexities of global supply chain management (SCM), which is gaining researchers' attention. Supply chain sustainability is put at risk by security issues in blockchain technology that affect everything from infrastructure to management. For sustainable supply chain management (SSCM), these elements are deemed crucial. To address this, the purpose of this research is to examine the impact of blockchain security factors on SSCM among United Kingdom manufacturing firms. Based on the resource-based view (RBV) theory and the Technology-Organisation-Environment (TOE) framework, the research hypotheses and framework were developed. To achieve the research objectives, a hybrid approach that combines structural equation modelling and artificial neural networks (ANNs) was adopted to perform the analysis. The research findings indicate that privacy, network, confidentiality, and managerial factors are vital to promoting SSCM. Furthermore, the ANN analysis highlights that managerial (trust management) and supplier privacy factors are the most important constructs. Unlike prior research that theoretically assumed that all relationships are linear, this has been a novel study that has successfully validated that there exists a nonlinear relationship between the RBV theory and the TOE framework. Based on the outcomes, the study's contributions, its practical implications, and future research avenues are discussed. |
| Author Keywords |
blockchain; security issues; sustainability; supply chain management; Industry 4.0 |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:001256072800001 |
| WoS Category |
Social Sciences, Interdisciplinary |
| Research Area |
Social Sciences - Other Topics |
| PDF |
https://www.mdpi.com/2079-8954/12/6/208/pdf?version=1718360293
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