Volume 27 , Issue 2 , PP: 474-488, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Samandarboy Sulaymanov 1 * , Gafurov Ubaydullo Vakhabovich 2
Doi: https://doi.org/10.54216/IJNS.270238
We introduce a neutrosophic framework to assess corruption across micro, meso, and macro levels and illustrate it with a public, fully synthetic dataset covering five Central Asian societies (2020–2025). The framework models the proposition “High Corruption” with three independent degrees: Truth (T ), Indeterminacy (I), and Falsity (F), which need not sum to one. We propose a summary index—the Neutrosophic Evidence Risk Index (NERI)—that couples evidence for and against high corruption with indeterminacy. Empirically, we document three stylized patterns in the synthetic data: (i) a moderate decline in country-level NERI over time for most countries; (ii) a negative association between region-year e-service adoption and bribe solicitation; and (iii) a negative association between digital government capacity and T at the country-year level. For example, the average bribe-solicitation rate is 0.047 overall, 0.198 without e-services (95% CI 0.175–0.220) vs. 0.019 with e-services (95% CI 0.015–0.022), implying a risk difference of -0.179 and a relative risk of 0.094.
Neutrosophic Sets , Neutrosophic Logic , Indeterminacy , Uncertainty Quantification , Multilevel Modeling , Corruption Assessment , Governance , Central Asia , Public Sector Integrity , E-Government , Decision Support Systems , Transition Economies , Social Measurement , Institutional Analysis , Neutrosophic Sociology
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