An analysis of international coauthorship networks in the supply chain analytics research area
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DOI: 10.1007/s11192-017-2370-6
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Cited by:
- Muhammad Noman Shafique & Ammar Rashid & Sook Fern Yeo & Umar Adeel, 2023. "Transforming Supply Chains: Powering Circular Economy with Analytics, Integration and Flexibility Using Dual Theory and Deep Learning with PLS-SEM-ANN Analysis," Sustainability, MDPI, vol. 15(15), pages 1-23, August.
- Kalaitzi, Dimitra & Tsolakis, Naoum, 2022. "Supply chain analytics adoption: Determinants and impacts on organisational performance and competitive advantage," International Journal of Production Economics, Elsevier, vol. 248(C).
- Qiang Du & Jiajie Zhou, 2022. "Evolution of Low Carbon Supply Chain Research: A Systematic Bibliometric Analysis," IJERPH, MDPI, vol. 19(23), pages 1-20, November.
- Šubelj, Lovro & Fiala, Dalibor & Ciglarič, Tadej & Kronegger, Luka, 2019. "Convexity in scientific collaboration networks," Journal of Informetrics, Elsevier, vol. 13(1), pages 10-31.
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Keywords
Social network analysis; Coauthorship networks; Big data analytics; Business analytics; Supply chain analytics;All these keywords.
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