AI Article Synopsis
- * A structural model is developed to identify and analyze logistics capability factors (LCFs) that enhance logistics performance using expert-based interpretive structural modeling and cross-impact matrix multiplication.
- * The study identifies key factors, with demand management interface (DMI) being crucial in improving logistics capability, followed by the importance of information management and technological innovation, offering insights for both theory and practice in supply chain management.
Article Abstract
Supply chain disruptions and global pandemics have revealed vulnerabilities within the logistics industry in recent years. Consequently, there has been a growing emphasis across various industries on enhancing logistics capabilities. The focus on improving logistics performance through capability factors has shifted the paradigm toward prioritizing these factors. In light of this transition, this study develops a structural model to identify the logistics capability factors (LCFs) that contribute to logistics performance. To define the interrelationships and interdependencies among LCFs, expert-based interpretive structural modeling (ISM) combined with cross-impact matrix multiplication applied to classification (MICMAC) is used. A complex ISM model and a MICMAC diagram, based on driving and dependency power, are constructed to determine and categorize LCFs. The findings indicate that the demand management interface (DMI) of service capability is a pivotal factor in enhancing logistics capability, followed by the significance of information management and technological innovation capabilities. The results of this study have several implications for understanding the relationships among LCFs and for extending knowledge through the application of the ISM-MICMAC technique. Both theoretical and managerial insights are highlighted, providing guidance for supply chain leaders and operational managers.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11617766 | PMC |
| http://dx.doi.org/10.1016/j.heliyon.2024.e40539 | DOI Listing |
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