District-level Study of Uttar Pradesh Based on the MCDM Approach
DOI:
https://doi.org/10.13052/jrss0974-8024.1718Keywords:
MCDM, TOPSIS, MOORA, Wilcoxon signed-rank test, CAW, TFRAbstract
Development and population are two crucial and complex areas of study for the researchers. They depend on many variables such as demography, economic status, nutritional status of the child and women, etc. This research aims to determine the best districts by evaluating them against eight specific criteria that reflect the demographic composition of women and children in Uttar Pradesh (UP).
The identification of the criteria of the variables is determined by various factors such as education, security & threat, gender equality, and health dimensions within the districts of UP, India. To achieve this we attempted to implement the multiple criteria decision-making (MCDM) methods comprehensibly. This study has presented an impartial assessment of the performance of 75 districts in UP. The methodology included a technique for order preference by similarity to ideal solution (TOPSIS) and multi-objective optimization based on ratio analysis (MOORA). Data on demographic and educational parameters were collected from the most recent published report of the national family health survey (NFHS-5) and various online portals & platforms of the government of UP. Also, we made an attempt to validate the techniques using a non-parametric statistical test known as Wilcoxon sign rank test. TOPSIS and MOORA were identified as two most popular MCDM techniques for demography research. Interestingly, we found districts namely, (Agra, Kanpur Nagar, Moradabad), Lucknow and Shrawasti as outliers with respect to variables area(A3)
, CAW(A5) and TFR(A6) respectively that need to be dealt with careful attention and effective measures has to be taken. The study provides useful information on the demographic characteristics of districts in UP and possibly provide the basis to our policymakers for designing the targeted interventions to improve the social and economic indicators of the State.
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