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Modified fuzzy TOPSIS + TFNs ranking model for candidate selection using the qualifying criteria

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Abstract

Currently, globalization process significantly impacts not only technological, economical, but also social, political and cultural fields. Ongoing social, economic and political processes demonstrate their impacts, and countries are governed by different regimes and government forms. From this standpoint, there is a need for qualified, competent staff for operation of the regimes and governments. In the article researches, which criteria or factors must be taken into account for selection of competent candidates that are suitable for relevant positions during the election process in contrast to traditional voting. Criteria for candidates’ selection include adoption of democratic principles, age, education, government agency experience, professional competence, global culture and value acknowledgement, influence in voting area, leadership skills, activity in social media, etc. In the article implemented multi-criteria evaluation approach for candidate selection. Candidates are ranked based on criteria selected using modified fuzzy TOPSIS and triangular fuzzy numbers ranking methods and different aggregation operators. Candidates are ranked by applying both methods in a numeral experiment, and obtained results are compared. Proposed fuzzy multi-criteria decision-making model allows determining a compromise solution in candidate selection.

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The authors received no specific funding for this work.

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Correspondence to Farhad Yusifov.

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Alguliyev, R., Aliguliyev, R. & Yusifov, F. Modified fuzzy TOPSIS + TFNs ranking model for candidate selection using the qualifying criteria. Soft Comput 24, 681–695 (2020). https://doi.org/10.1007/s00500-019-04521-2

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Keywords

  • Election systems
  • Voting
  • Candidate selection
  • Fuzzy MCDM
  • Ranking triangular fuzzy numbers
  • Positional ranking