Results in Control and Optimization (Sep 2023)

Empowerment of women in India as different perspectives based on the AHP-TOPSIS inspired multi-criterion decision making method

  • Doli Adhikari,
  • Kamal Hossain Gazi,
  • Bibhas Chandra Giri,
  • Fariba Azizzadeh,
  • Sankar Prasad Mondal

Journal volume & issue
Vol. 12
p. 100271

Abstract

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The multi-criteria decision-making (MCDM) method often entails a number of steps, such as identifying the decision problem, defining the criteria, calculating the weighting of the criteria, assessing the alternatives against the criteria, and finally choosing the best alternative based on the overall evaluation. In this paper, the essential factor for sports, politics, journalism or media, and technological empowerment of women in India are found by MCDM techniques, which may also be utilized to examine the key factors influencing women’s empowerment. The uses the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) MCDM methodologies are taken to discover the optimal criteria for empowerment. The decision-making for finding the factors is done by taking multi experts’ opinions. First, determined the best criteria among the six criterion’s, such as Family Support (C1), Financial Support (C2), Cultural and Religious Barrier (C3), Child Marriage (C4), Nutrition (C5), and Shame and concealment (C6). The weights are calculated by the AHP method. According to the importance of the criteria, select a significant alternative for empowering women in many fields. Also take six possibilities into consideration, which are Empowerment in Sports (A1), Empowerment in Politics (A2), Empowerment in Administrative Service (A3), Empowerment of Journalism or Media (A4), Empowerment for Social Work (A5)and Empowerment of Technological (A6)and they are ranked by TOPSIS method. To verify the validity and robustness of our result, sensitivity analysis is performed by removing some criteria to make sure the procedure is reliable and a comparative study using a fuzzy environment.

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