IDEAS home Printed from https://ideas.repec.org/a/spr/infsem/v18y2020i4d10.1007_s10257-019-00402-1.html
   My bibliography  Save this article

RETRACTED ARTICLE: Research on the optimization of the supplier intelligent management system for cross-border e-commerce platforms based on machine learning

Author

Listed:
  • Ying Yang

    (Northeast Asian Studies College of Jilin University)

Abstract

At present, with the continuous development of the intelligent system, it is used in many industries. In e-commerce industry, the intelligent system has also been used, especially in supplier management. Based on the machine learning theory, this paper studies the optimization of the supplier management intelligent system of cross-border e-commerce platforms. Based on the wisdom algorithm and machine learning perspective, the optimization of cross-border e-commerce platform supplier credit system is studied in this paper. Firstly, the calculation of the traditional supplier credit evaluation is optimized by introducing the decision matrix algorithm of the difference matrix and the cloud model evaluation method. Then a multi-objective joint decision model of supplier selection and order allocation is established, and the multi-objective evolutionary algorithm combined with actual examples is applied to verify the effectiveness and feasibility of the algorithm and model. Finally, the decision makers’ preferences are integrated into the intelligent decision-making, and the cloud model evaluation method is adopted. The rough set and gray relational analysis mathematical tools are used to construct the procurement supply evaluation system. The research results show that the comparison of the three general indicators of the procurement supply chain can be obtained through the cloud model evaluation calculation, which indirectly reflects the preference decision weights of the three objective functions of the cross-border e-commerce supplier selection and order allocation multi-objective optimization model. This indicates that the procurement supply evaluation system constructed in this paper has achieved the purpose of scientific evaluation and selection of suppliers, and has played a theoretical reference role for supplier management of cross-border e-commerce platform.

Suggested Citation

  • Ying Yang, 2020. "RETRACTED ARTICLE: Research on the optimization of the supplier intelligent management system for cross-border e-commerce platforms based on machine learning," Information Systems and e-Business Management, Springer, vol. 18(4), pages 851-870, December.
    • Handle: RePEc:spr:infsem:v:18:y:2020:i:4:d:10.1007_s10257-019-00402-1
    DOI: 10.1007/s10257-019-00402-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10257-019-00402-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10257-019-00402-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ilias O. Pappas & Patrick Mikalef & Michail N. Giannakos & John Krogstie & George Lekakos, 2018. "Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies," Information Systems and e-Business Management, Springer, vol. 16(3), pages 479-491, August.
    2. Kishor Vaidya & John Campbell, 2016. "Multidisciplinary approach to defining public e-procurement and evaluating its impact on procurement efficiency," Information Systems Frontiers, Springer, vol. 18(2), pages 333-348, April.
    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. Venugopal Gopalakrishna-Remani & Robert Paul Jones & Kerri M. Camp, 2019. "Levels of EMR Adoption in U.S. Hospitals: An Empirical Examination of Absorptive Capacity, Institutional Pressures, Top Management Beliefs, and Participation," Information Systems Frontiers, Springer, vol. 21(6), pages 1325-1344, December.
    2. Hajiheydari, Nastaran & Delgosha, Mohammad Soltani & Olya, Hossein, 2021. "Scepticism and resistance to IoMT in healthcare: Application of behavioural reasoning theory with configurational perspective," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    3. Mendez-Picazo, María-Teresa & Galindo-Martin, Miguel-Angel & Perez-Pujol, Rafael-Sergio, 2024. "Direct and indirect effects of digital transformation on sustainable development in pre- and post-pandemic periods," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    4. Mohammad Soltani Delgosha & Tahereh Saheb & Nastaran Hajiheydari, 0. "Modelling the Asymmetrical Relationships between Digitalisation and Sustainable Competitiveness: A Cross-Country Configurational Analysis," Information Systems Frontiers, Springer, vol. 0, pages 1-21.
    5. Raed A.I. Abueed & Mehmet Aga, 2019. "Sustainable Knowledge Creation and Corporate Outcomes: Does Corporate Data Governance Matter?," Sustainability, MDPI, vol. 11(20), pages 1-15, October.
    6. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. Yang, Xiaoping & Cao, Dongmei & Andrikopoulos, Panagiotis & Yang, Zonghan & Bass, Tina, 2020. "Online social networks, media supervision and investment efficiency: An empirical examination of Chinese listed firms," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    8. Belhadi, Amine & Venkatesh, Mani & Kamble, Sachin & Abedin, Mohammad Zoynul, 2024. "Data-driven digital transformation for supply chain carbon neutrality: Insights from cross-sector supply chain," International Journal of Production Economics, Elsevier, vol. 270(C).
    9. Marija Jović & Edvard Tijan & Doroteja Vidmar & Andreja Pucihar, 2022. "Factors of Digital Transformation in the Maritime Transport Sector," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    10. Francis Aboagye‐Otchere & Cletus Agyenim‐Boateng & Abdulai Enusah & Theodora Ekua Aryee, 2021. "A Review of Big Data Research in Accounting," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(4), pages 268-283, October.
    11. Damminda Alahakoon & Rashmika Nawaratne & Yan Xu & Daswin Silva & Uthayasankar Sivarajah & Bhumika Gupta, 2023. "Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities," Information Systems Frontiers, Springer, vol. 25(1), pages 221-240, February.
    12. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    13. Neukam, Marion & Bollinger, Sophie, 2022. "Encouraging creative teams to integrate a sustainable approach to technology," Journal of Business Research, Elsevier, vol. 150(C), pages 354-364.
    14. Yogesh K. Dwivedi & Elvira Ismagilova & Nripendra P. Rana & Ramakrishnan Raman, 2023. "Social Media Adoption, Usage And Impact In Business-To-Business (B2B) Context: A State-Of-The-Art Literature Review," Information Systems Frontiers, Springer, vol. 25(3), pages 971-993, June.
    15. Mina Nasiri & Minna Saunila & Juhani Ukko & Tero Rantala & Hannu Rantanen, 2023. "Shaping Digital Innovation Via Digital-related Capabilities," Information Systems Frontiers, Springer, vol. 25(3), pages 1063-1080, June.
    16. Aristotelis Mavidis & Dimitris Folinas, 2022. "From Public E-Procurement 3.0 to E-Procurement 4.0; A Critical Literature Review," Sustainability, MDPI, vol. 14(18), pages 1-23, September.
    17. Di Vaio, Assunta & Palladino, Rosa & Pezzi, Alberto & Kalisz, David E., 2021. "The role of digital innovation in knowledge management systems: A systematic literature review," Journal of Business Research, Elsevier, vol. 123(C), pages 220-231.
    18. Anastasia Griva & Cleopatra Bardaki & Katerina Pramatari & Georgios Doukidis, 2022. "Factors Affecting Customer Analytics: Evidence from Three Retail Cases," Information Systems Frontiers, Springer, vol. 24(2), pages 493-516, April.
    19. Jun Zhang & Shuyang Li & Yichuan Wang, 2023. "Shaping a Smart Transportation System for Sustainable Value Co-Creation," Information Systems Frontiers, Springer, vol. 25(1), pages 365-380, February.
    20. Shuai Li & Hao Yu, 2020. "RETRACTED ARTICLE: Big data and financial information analytics ecosystem: strengthening personal information under legal regulation," Information Systems and e-Business Management, Springer, vol. 18(4), pages 891-909, December.

    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:spr:infsem:v:18:y:2020:i:4:d:10.1007_s10257-019-00402-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.