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A new approach based on BWM and MULTIMOORA methods for calculating semi-human development index: An application for provinces of Iran

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  • Omrani, Hashem
  • Alizadeh, Arash
  • Amini, Mohaddeseh

Abstract

Human Development Index (HDI) is a useful tool for policy makers to understand the degree of development in their societies and set new policies to improve it. Traditionally, the United Nations Development Program (UNDP) releases HDI scores of countries based on the three key dimensions of healthy life, population education and standards of living annually. However, HDI scores have some deficiencies such as methodology, indexes selection and measures time lag. In this paper, a new approach is proposed to calculate semi-HDI scores. First, in each dimension of health, education and standard of living, new and extra criteria are selected. Then, policy makers' preferences are considered to assign the weights of criteria in each dimension using best worst method (BWM). Then, MULTIMOORA method is applied to rank provinces of Iran in each dimension. Finally, the semi-HDI scores of provinces are calculated based on geometric mean of healthy life, population education and living standards. According to the semi-HDI scores, Kohgiluyeh & Boyer- Ahmad and Sistan & Baluchestan provinces are the most and the least developed provinces of Iran, respectively.

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  • Omrani, Hashem & Alizadeh, Arash & Amini, Mohaddeseh, 2020. "A new approach based on BWM and MULTIMOORA methods for calculating semi-human development index: An application for provinces of Iran," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:soceps:v:70:y:2020:i:c:s0038012118300235
    DOI: 10.1016/j.seps.2019.02.004
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    4. Shih-Ping Shen & Jung-Fa Tsai, 2022. "Evaluating the Sustainable Development of the Semiconductor Industry Using BWM and Fuzzy TOPSIS," Sustainability, MDPI, vol. 14(17), pages 1-17, August.
    5. Zaijun Li & Xiang Zheng & Suleman Sarwar, 2022. "Spatial Measurements and Influencing Factors of Comprehensive Human Development in China," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    6. Yalcin Kavus, Bahar & Gulum Tas, Pelin & Ayyildiz, Ertugrul & Taskin, Alev, 2022. "A three-level framework to evaluate airline service quality based on interval valued neutrosophic AHP considering the new dimensions," Journal of Air Transport Management, Elsevier, vol. 99(C).
    7. Wang, Hanjie & Feil, Jan-Henning & Yu, Xiaohua, 2023. "Let the data speak about the cut-off values for multidimensional index: Classification of human development index with machine learning," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    8. Sisto, Roberta & Fernández-Portillo, Luis A. & Yazdani, Morteza & Estepa-Mohedano, Lorenzo & Torkayesh, Ali Ebadi, 2022. "Strategic planning of rural areas: Integrating participatory backcasting and multiple criteria decision analysis tools," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).

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