The DOI matches its Crossref record; 91 of the 91 references it cites were found in a registry or an index.
Data-driven supply chain capabilities and performance: A resource-based view
Open accessAbstract
Despite the importance and relevance of data-driven supply chains, there has been very limited empirical research that investigates how big data-driven supply chains affect supply chain capabilities. Drawing on the resource-based view, this study explores the effect of data-driven supply chain capabilities on financial performance. The data for this study were gathered from China’s manufacturing industry and analysed using structural equation modelling. The results indicate that a data-driven supply chain has a significant positive effect on the four dimensions of supply chain capabilities. Coordination and supply chain responsiveness are positively and significantly related to financial performance.
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El Baz, J., & Ruel, S. (2021) · International Journal of Production Economics · doi:10.1016/j.ijpe.2020.107972 · Cited by 868
Wang, C., Zhang, Q., & Zhang, W. (2020) · Research in Transportation Business & Management · doi:10.1016/j.rtbm.2020.100557 · Cited by 293
Circular economy practices and industry 4.0 technologies: A strategic move of automobile industry
Yu, Z., Khan, S. A. R., & Umar, M. (2022) · Business Strategy and the Environment · doi:10.1002/bse.2918 · Cited by 280
Influencing models and determinants in big data analytics research: A bibliometric analysis
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Metadata
- Authors
- Yu, W., Chavez, R., Jacobs, M. A., & Feng, M.
- Venue
- Transportation Research Part E: Logistics and Transportation Review
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 114
- Pages
- 371-385
- ISSN
- 1366-5545 (ISSN-L)
- OpenAlex
- W2596781423
- Cited by
- 300
- References
- 91
- FWCI
- 28.01
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
