Evaluation of the Global Multidimensional Poverty Index by Fuzzy LMAW Method

Küresel Çok Boyutlu Yoksulluk Endeksinin Bulanık LMAW Yöntemi İle Değerlendirilmesi

Authors

  • Gülay DEMİR Sivas Cumhuriyet University

Keywords:

Global poverty, Fuzzy number, Fuzzy LMAW

Abstract

In order to be successful in combating poverty, poverty must be well defined and poverty measurement criteria must be well defined. Especially in recent studies, poverty is not only defined as an income deficiency, but poverty is defined as a multidimensional problem. In these current studies on poverty indicators, all dimensions are considered with equal importance. However, the effects of the dimensions of poverty on this problem are not equal. In this study, the importance levels of the dimensions that make up the concept of poverty were calculated with expert opinions. The Fuzzy LMAW model was used to improve the scientific calculation of weights. The three dimensions of health, education and living standards of the multidimensional poverty index and the weight of their indicators were calculated based on the interviews with the relevant experts. The research shows that the size of the standard of living and its main indicators, drinking water, make up a large weight. By using these weight levels, dimensions can be weighted in studies on poverty indicators and solution proposals will be more effective.

References

Alkire, S., S. Jahan. 2018. The New Global MPI 2018: Aligning with the Sustainable Development Goals. Human Development Research Paper. UNDPHDRO, New York. http://hdr.undp.org/en/content/new-global-mpi-2018-aligning-sustainable-development goals.

Alkire, S., Kanagaratnam, U. and Suppa, N. (2020). ‘The Global Multidimensional Poverty Index (MPI) 2020’, OPHI MPI Methodological Notes 49, Oxford Poverty and Human Development Initiative, University of Oxford.

Arslan,R. & Bircan, H. (2018). Alternatif Sayısının Çok Kriterli Karar Verme Yöntemlerinin Sonuçlarına Etkisi, Bartın Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt 9, Sayı 18, 239-264.

Bárcena-Martín, E., Pérez-Moreno, S., & Rodríguez-Díaz, B. (2020). Rethinking multidimensional poverty through a multi-criteria analysis. Economic Modelling, 91, 313-325.

Božanić D, Pamučar D, Milić A, Marinković D, Komazec N. 2022. Modification of the Logarithm Methodology of Additive Weights (LMAW) by a Triangular Fuzzy Number and Its Application in Multi-Criteria Decision Making. Axioms. 11(3):89.

Budiman, E., Labulan, P. M., & Hairah, U. (2018). A Model for Poverty Alleviation Strategies: Decision Making Management and Indicators Issues. Advanced Science Letters, 24(11), 8729-8735.

Chen, C.T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1–9.

Cheng, C. H., Cheng, G. W. & Wang, J. W. (2008). Multi-attribute fuzzy time series method based on fuzzy clustering. Expert Systems with Applications, 34(2), 1235-1242.

Ecer, F. (2020). Çok Kriterli Karar Verme Geçmişten Günümüze Kapsamlı Yaklaşım. Seçkin Yayınları, Ankara.

Görçün, Ö. F. & Küçükönder, H. (2022). Evaluation of The Transitions Potential to Cyber-Physical Production System of Heavy Industries in Turkey with A Novel Decision-Making Approach Based on Bonferroni Function. Verimlilik Dergisi, Dijital Dönüşüm ve Verimlilik, 1-16. DOI: 10.51551/verimlilik.983133.

Multidimensional-Poverty-Index-MPI (2020). https://www.tr.undp.org/content/turkey/tr/home/library/human_development/2020-Multidimensional-Poverty-Index-MPI.html (Son Erişim Tarihi: 09.07.2022).

Pamučar, D., Žižović, M., Biswas, S., Božanić, D. (2021). A new Logarithm Methodology of Additive Weights (LMAW) for Multi-Criteria Decision-Making: Application in Logistics. Facta Univ.-Ser. Mech. Eng. 19, 361-380.

Rezaei, J., Ortt, R. (2013). Multi-criteria Supplier Segmentation Using a Fuzzy Preference Relations Based AHP. European Journal of Operational Research, 225(1), 75-84.

Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338–353.

Zhang, Z., Tian, M., Li, J., Yang, Y., Wang, F., Wei, Y. (2019). Weight Analysis of Rural Multidimensional Poverty Index Based on DEMATEL Model: A Case Study of Shanxi Province in China. 2nd International Conference on Global Economy, Finance and Humanities Research. 1-5.

Published

2022-07-31

How to Cite

DEMİR, G. (2022). Evaluation of the Global Multidimensional Poverty Index by Fuzzy LMAW Method: Küresel Çok Boyutlu Yoksulluk Endeksinin Bulanık LMAW Yöntemi İle Değerlendirilmesi. Journal of Quantitative Research in Social Sciences, 2(1), 67–77. Retrieved from https://www.sobinarder.com/index.php/sbd/article/view/27