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Exploring the Ranking, Classifications and Evolution Mechanisms of Research Fronts: A Method Based on Multiattribute Decision Making and Clustering

Author

Listed:
  • Kai Xiong

    (Center for Network Big Data and Decision-Making, Business School, Sichuan University, Chengdu 610065, Sichuan, P R China)

  • Yucheng Dong

    (Center for Network Big Data and Decision-Making, Business School, Sichuan University, Chengdu 610065, Sichuan, P R China)

  • Zhaoxia Guo

    (Center for Network Big Data and Decision-Making, Business School, Sichuan University, Chengdu 610065, Sichuan, P R China)

  • Francisco Chiclana

    (��Institute of Artificial Intelligence, School of Computer Science and Informatics, De Montfort University, Leicester, UK)

  • Enrique Herrera-Viedma

    (��Andalusian Research Institute in Data Science and Computational Intelligence, University of Granada, Granada 18071, Spain)

Abstract

This study aims to present a multiattribute decision-making (MADM) and clustering method to explore the ranking, classifications and evolution mechanisms of the research fronts in the Web of Science Essential Science Indicators (ESI) database. First, bibliometrics are used to reveal the characteristics of the 57 ESI research fronts with more than 40 ESI highly cited papers (ESI-HCPs) for each research front. Second, the eight representative indicators are discovered to get answers to the following two questions: (i) Who publishes the ESI-HCPs that form a research front? and (ii) Where citations to these ESI-HCPs come from on a research front? Next, we investigate the ranking and clusters among the 57 ESI research fronts using the MADM and k-means clustering method and uncover the evolution process of the research fronts in different clusters based on the representative indicators. We also compare the performances of different countries in these research fronts and find that the USA and China are the leading countries in most research fronts. However, the two countries behave differently with regard to the rankings, the classifications and the evolution.

Suggested Citation

  • Kai Xiong & Yucheng Dong & Zhaoxia Guo & Francisco Chiclana & Enrique Herrera-Viedma, 2023. "Exploring the Ranking, Classifications and Evolution Mechanisms of Research Fronts: A Method Based on Multiattribute Decision Making and Clustering," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 157-185, January.
    • Handle: RePEc:wsi:ijitdm:v:22:y:2023:i:01:n:s0219622022300038
    DOI: 10.1142/S0219622022300038
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