Abstract
The definition of “rural areas” varies significantly across regions, making the determination of rurality levels crucial for sustainable development and effective policy design. This study introduces a comprehensive rurality index to rank and categorize villages within the Belsar Development Block of Gonda District, India. Utilizing Multiple-criteria Decision-making Methods (MCDMs) such as Fuzzy Analytic Hierarchy Process (F-AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Weighted Product Model (WPM), and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), we developed a robust methodology for this assessment. A thorough sensitivity analysis was also conducted to ensure the reliability of the results. The study identified fourteen critical factors, grouped into five domains: (1) socioeconomic status, (2) education, (3) land use, (4) employment, and (5) healthcare. Based on these factors, villages were ranked and classified into four categories according to their rurality levels, and a detailed rurality map was created with QGIS. The study revealed that the modified F-AHP emerged as the most effective MCDM method for this rurality assessment. Given the systematic execution of this assessment, it can serve as a model for comparative studies in other regions of India and globally, promoting sustainable rural development through informed decision-making.
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