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1.

Evaluating women’s happiness levels with ARASsort: The case of Türkiye Pages 707-726 Right click to download the paper Download PDF

Authors: Semiha Bal, Gül Tekin Temur, Sait Gül

DOI: 10.5267/j.dsl.2025.3.009

Keywords: ARASsort, Happiness, Life satisfaction, Multiple attribute sorting, Women’s happiness

Abstract:
The happiness levels of women exhibit variations attributable to a myriad of factors, encompassing economic, social, cultural, and demographic variables. Numerous governments incorporate the measurement of happiness levels as part of life-satisfaction analyses; nonetheless, these analyses lack a comprehensive framework for predicting happiness levels over specific periods. Notably, in developing countries, women confront the adverse consequences of economic, social, cultural, and demographic determinants to a greater extent than men. Paradoxically, they remain significantly underrepresented in both academic and industrial domains. In light of this, the primary objective of this study is to conduct an in-depth analysis of happiness levels and their underlying determinants from a gender-oriented perspective. Therefore, the pertinent literature has not dedicated a systematic approach to classify and forecast the happiness of women. The present paper initiates by elucidating the factors influencing women's perceptions of happiness through a comprehensive review of the existing literature. Then, a multiple attribute decision-making algorithm-based sorting methodology, ARASsort, is utilized to evaluate how women’s happiness levels are affected by life satisfaction components in a developing country, Türkiye. The selection of ARASsort is based on its performance over other traditional sorting approaches in terms of time and effort attachment. Various factors affecting the happiness levels of women in different cities in the country sample were discussed and analyzed in detail in accordance with the main findings of the OECD Better Life Index (2020), through representative data selected from TÜİK's life satisfaction dataset.
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Journal: DSL | Year: 2025 | Volume: 14 | Issue: 3 | Views: 333 | Reviews: 0

 

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