IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i4p1696-d1341526.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/4/1696/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/4/1696/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi Li, 2020. "Internet Development and Structural Transformation: Evidence from China," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(1), pages 1-8.
    2. Yingying Zhang Zhang & Chun Yee Wong & Alessandro Comai, 2024. "Child Labor in Social Media: Exploring a Decade of YouTube Data," Working Papers EMS_2024_04, Research Institute, International University of Japan.
    3. Izabela Mlynarzewska-Borowiec, 2022. "Digital Competitiveness Gap between the US and EU Member States in the 21st Century," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 364-380.
    4. Thomas H.W. ZIESEMER, 2012. "Worker remittances and government behaviour in the receiving countries," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 3, pages 37-59, December.
    5. Rubio-Andrés, Mercedes & Ramos-González, Mª del Mar & Sastre-Castillo, Miguel Ángel & Gutiérrez-Broncano, Santiago, 2023. "Stakeholder pressure and innovation capacity of SMEs in the COVID-19 pandemic: Mediating and multigroup analysis," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    6. Zimei Liu & Yezhi Ren & Yanlan Mei, 2022. "How Does Internet Use Promote Farmer Entrepreneurship: Evidence from Rural China," Sustainability, MDPI, vol. 14(24), pages 1-15, December.
    7. 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.
    8. Zhao Qu & Shanshan Zhang & Chunbo Zhang, 2017. "Patent research in the field of library and information science: Less useful or difficult to explore?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 205-217, April.
    9. Cui Zhang & Xiongjin Feng & Yanzhen Wang, 2022. "Technology Spillovers among Innovation Agents from the Perspective of Network Connectedness," Mathematics, MDPI, vol. 10(16), pages 1-17, August.
    10. Iryna Kalenyuk & Liudmyla Tsymbal, 2021. "Assessment of the intellectual component in economic development," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4793-4816, June.
    11. Haddoud, Mohamed Yacine & Kock, Ned & Onjewu, Adah-Kole Emmanuel & Jafari-Sadeghi, Vahid & Jones, Paul, 2023. "Technology, innovation and SMEs' export intensity: Evidence from Morocco," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    12. Anhang Chen & Huiqin Zhang & Yuxiang Zhang & Junwei Zhao, 2024. "Manufacturers’ digital transformation under carbon cap-and-trade policy: investment strategy and environmental impact," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    13. Md Maruf Hossan Chowdhury & Mohammad Tarikul Islam & Imran Ali & Mohammed Quaddus, 2024. "The role of social capital, resilience, and network complexity in attaining supply chain sustainability," Business Strategy and the Environment, Wiley Blackwell, vol. 33(3), pages 2621-2639, March.
    14. Martínez-Caro, Eva & Cegarra-Navarro, Juan Gabriel & Alfonso-Ruiz, Francisco Javier, 2020. "Digital technologies and firm performance: The role of digital organisational culture," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    15. Arif Imam Suroso & Idqan Fahmi & Hansen Tandra, 2022. "The Role of Internet on Agricultural Sector Performance in Global World," Sustainability, MDPI, vol. 14(19), pages 1-10, September.
    16. Dharm Dev Bhatta & Muddassar Sarfraz & Larisa Ivascu & Marius Pislaru, 2023. "The Nexus of Corporate Affinity for Technology and Firm Sustainable Performance in the Era of Digitalization: A Mediated Model," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
    17. Gnangnon, Sèna Kimm & Iyer, Harish, 2018. "Does bridging the Internet Access Divide contribute to enhancing countries' integration into the global trade in services markets?," Telecommunications Policy, Elsevier, vol. 42(1), pages 61-77.
    18. Alfonso Marino & Paolo Pariso, 2021. "Digital economy: technological, organizational and cultural contexts for the development of cooperation in Europe," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 9(2), pages 363-383, December.
    19. Simplice A. Asongu, 2021. "The Effects of Mobile Phone Technology, Knowledge Creation and Diffusion on Inclusive Human Development in Sub-Saharan Africa," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(3), pages 1367-1398, September.
    20. Xi, Xi & Ren, Feifei & Yu, Lean & Yang, Jing, 2023. "Detecting the technology's evolutionary pathway using HiDS-trait-driven tech mining strategy," Technological Forecasting and Social Change, Elsevier, vol. 195(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1696-:d:1341526. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.