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A Market Convergence Prediction Framework Based on a Supply Chain Knowledge Graph

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  • Shaojun Zhou

    (National Numerical Control Systems Engineering Research Center, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yufei Liu

    (The CAE Center for Strategic Studies, Chinese Academy of Engineering, Beijing 100088, China)

  • Yuhan Liu

    (National Numerical Control Systems Engineering Research Center, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

Market convergence challenges socially sustainable supply chain management (SSSCM) due to the increasing competition. Identifying market convergence trends allows companies to respond quickly to market changes and improve supply chain resilience (SCR). Conventional approaches are one-sided and biased and cannot predict market convergence trends comprehensively and accurately. To address this issue, we propose a framework based on info2vec that solves the problem of matching multidimensional data by using the technology layer as the focal layer and the supply chain as the supporting layer. The framework enriches the supply chain dimension with the technology dimension. A knowledge graph is constructed to facilitate cross-domain information connectivity by integrating different data sources. The nodes in the knowledge graph were characterized using a representation learning algorithm, which enhanced feature mining during supply chain and market convergence. Changes in market demand were predicted based on link prediction experiments. Market convergence has an impact on firm cooperation and, thus, on SCR. The framework recommends potential technological and innovative cooperation opportunities for firms. In this way, it has been demonstrated to improve SSSCM through network resilience experiments. This method predicts market convergence efficiently based on the supply chain knowledge graph, which provides decision support for enterprise development.

Suggested Citation

  • Shaojun Zhou & Yufei Liu & Yuhan Liu, 2024. "A Market Convergence Prediction Framework Based on a Supply Chain Knowledge Graph," Sustainability, MDPI, vol. 16(4), pages 1-20, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1696-:d:1341526
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    References listed on IDEAS

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    1. Li, Xin & Xie, Qianqian & Jiang, Jiaojiao & Zhou, Yuan & Huang, Lucheng, 2019. "Identifying and monitoring the development trends of emerging technologies using patent analysis and Twitter data mining: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 687-705.
    2. Huub Meijers, 2014. "Does the internet generate economic growth, international trade, or both?," International Economics and Economic Policy, Springer, vol. 11(1), pages 137-163, February.
    3. Mohammad Alghababsheh & David Gallear, 2021. "Socially Sustainable Supply Chain Management and Suppliers’ Social Performance: The Role of Social Capital," Journal of Business Ethics, Springer, vol. 173(4), pages 855-875, November.
    4. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    5. Lee, Misuk & Cho, Youngsang, 2015. "Consumer perception of a new convergence product: A theoretical and empirical approach," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 312-321.
    6. Muddassar Sarfraz & Kausar Fiaz Khawaja & Heesup Han & Antonio Ariza-Montes & Juan Manuel Arjona-Fuentes, 2023. "Sustainable supply chain, digital transformation, and blockchain technology adoption in the tourism sector," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    7. Seongkyoon Jeong & Jong-Chan Kim & Jae Young Choi, 2015. "Technology convergence: What developmental stage are we in?," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 841-871, September.
    8. Zulkaif Ahmed Saqib & Luo Qin & Rashid Menhas & Gong Lei, 2023. "Strategic Sustainability and Operational Initiatives in Small- and Medium-Sized Manufacturers: An Empirical Analysis," Sustainability, MDPI, vol. 15(7), pages 1-20, April.
    9. Del Giudice, M. & Scuotto, V. & Garcia-Perez, A. & Messeni Petruzzelli, A., 2019. "Shifting Wealth II in Chinese economy. The effect of the horizontal technology spillover for SMEs for international growth," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 307-316.
    10. Miguel Reyna-Castillo & Paola Selene Vera Martínez & Lisette Farah-Simón & Nadima Simón, 2023. "Social Sustainability Orientation and Supply Chain Performance in Mexico, Colombia and Chile: A Social-Resource-Based View (SRBV)," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
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