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Exploring the knowledge diffusion and research front of OWA operator: a main path analysis

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Abstract

In recent years, more and more attention is paid to the OWA operator in the academy. Growth curve analysis, which is often used in ecosystem studies, also indicates that this growth trend will continue. However, prior literature has not made a big picture to help researchers make clear of the development of this field by identifying the evolution path. The classic main path analysis is an excellent method combining quantitative analysis and qualitative analysis. We conducted the classic main path analysis and its variants on a citation network with 1474 papers to probe the development trajectories and research topics of OWA. We obtained several findings by constructing local and global main path, and multiple main paths. The path results indicate that weight generation and operator generalization run through the overall OWA domain, show that the multiple criteria decision making process assumed in the related research begins to be dynamic and multi-period, and reveal that some theories such as social network theory are introduced into the OWA operator and the applications are also greatly expanded.

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All data included in this study are available upon request by contact with the corresponding author.

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Authors and Affiliations

  1. Business School, Nanjing Audit University, Nanjing, 211815, Jiangsu, China

    Dejian Yu

  2. School of Information Management, Nanjing University, Nanjing, 210023, Jiangsu, China

    Tianxing Pan

  3. Business School, Sichuan University, Chengdu, 610064, China

    Zeshui Xu

  4. The Machine Intelligence Institute, Iona College, New Rochelle, NY, 10805, USA

    Ronald R. Yager

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  1. Dejian Yu
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  2. Tianxing Pan
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  4. Ronald R. Yager
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Appendix

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Table 1 Top cited references
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Yu, D., Pan, T., Xu, Z. et al. Exploring the knowledge diffusion and research front of OWA operator: a main path analysis. Artif Intell Rev 56, 12233–12255 (2023). https://doi.org/10.1007/s10462-023-10462-y

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