A MULTI-DIMENSIONAL COMPOSITE RESILIENCE INDEX FOR UKRAINIAN PUBLIC ADMINISTRATION UNDER CONFLICT CONDITIONS
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Abstract
This paper constructs, empirically identifies, and longitudinally validates a Multi-Dimensional Composite Resilience Index (MCRI) for Ukrainian public administration institutions using seven internationally recognised governance datasets spanning 2015-2024. The work is conducted within the framework of the LEEPS project, a UK-Ukraine-Latvia research partnership. The MCRI integrates indicators from the World Bank Worldwide Governance Indicators (WGI), Transparency International Corruption Perceptions Index (CPI), Freedom House Nations in Transit, the UN E-Government Development Index (EGDI), SIGMA/OECD monitoring reports, and the INFORM Risk Index into a unified composite score through a mathematically rigorous hybrid weighting scheme. Objective weights are derived via Principal Component Analysis (PCA) applied to the longitudinal indicator matrix; subjective weights are elicited from Ukrainian public administration experts through the Analytic Hierarchy Process (AHP); the two weight sets are combined through a convex mixing procedure with parameter μ* identified by minimising prediction error against European Commission Ukraine Progress Report scores used as an external validation benchmark. Non-linear interactions between governance dimensions are captured through an OLS-identified interaction term. Shapley value decomposition provides fair attribution of MCRI changes to individual governance dimensions across three identified phases: gradual pre-war recovery (2015–2021), acute conflict shock (2022), and partial recovery (2023–2024). The conflict shock reduced the MCRI by approximately 34% from its 2021 pre-war peak. External validation against the Bertelsmann Transformation Index confirms the model’s empirical robustness (r=0,91; p<0,01).
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composite resilience index, Ukrainian governance, multi-criteria aggregation, AHP-PCA hybrid weights, Shapley decomposition, longitudinal resilience analysis, conflict resilience, public administration, socio-technical systems, SIGMA indicators
European Commission. (2024). Ukraine 2024 Report. Neighbourhood and Enlargement, EC.
World Bank. (2024). Ukraine Economic Update. Washington DC: World Bank Group.
Hollnagel, E., Woods, D.D., & Leveson, N. (Eds.). (2006). Resilience Engineering: Concepts and Precepts. Ashgate.
Kaufmann, D., Kraay, A., & Mastruzzi, M. (2011). The worldwide governance indicators: Methodology and analytical issues. Hague Journal on the Rule of Law, 3(2), 220–246.
Christmann, G. (2016). Resilient Cities: Governing Urbanisation and City Regions. Berlin: IRS.
Bertelsmann Stiftung. (2024). Bertelsmann Transformation Index 2024. Gütersloh: Bertelsmann Stiftung.
Mo Ibrahim Foundation. (2023). Ibrahim Index of African Governance. London: MIF.
Hollnagel, E. (2011). Prologue: The scope of resilience engineering. In E. Hollnagel et al. (Eds.), Resilience Engineering in Practice. Ashgate.
Woods, D.D. (2015). Four concepts for resilience and the implications for the future of resilience engineering. Reliability Engineering & System Safety, 141, 5–9.
Leveson, N., Dulac, N., Marais, K., & Carroll, J. (2009). Moving beyond normal accidents and high reliability organizations: A systems approach to safety in complex systems. Organization Studies, 30(2–3), 227–249.
Zio, E. (2016). Challenges in the vulnerability and risk analysis of critical infrastructures. Reliability Engineering & System Safety, 152, 137–150.
Cutter, S.L., et al. (2013). New directions for resilience research. In Measuring Community Resilience (pp. 1–27). UN-ISDR.
Bruneau, M., et al. (2003). A framework to quantitatively assess and enhance the seismic resilience of communities. Earthquake Spectra, 19(4), 733–752.
Cutter, S.L., Burton, C.G., & Emrich, C.T. (2010). Disaster resilience indicators for benchmarking baseline conditions. Journal of Homeland Security and Emergency Management, 7(1).
European Commission. (2023). Critical Entities Resilience Directive (CER). Directive (EU) 2022/2557.
Norris, F.H., Stevens, S.P., Pfefferbaum, B., Wyche, K.F., & Pfefferbaum, R.L. (2008). Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. American Journal of Community Psychology, 41(1–2), 127–150.
Comfort, L.K., Boin, A., & Demchak, C.C. (Eds.). (2010). Designing Resilience: Preparing for Extreme Events. Pittsburgh: University of Pittsburgh Press.
OECD/JRC. (2008). Handbook on Constructing Composite Indicators: Methodology and User Guide. OECD Publishing.
Nardo, M., et al. (2005). Tools for Composite Indicators Building. EUR 21682 EN. Ispra: JRC.
Saisana, M., & Tarantola, S. (2002). State-of-the-art Report on Current Methodologies and Practices for Composite Indicator Development. EUR 20408 EN. Ispra: JRC.
Saaty, T.L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill.
Joliffe, I.T. (2002). Principal Component Analysis (2nd ed.). New York: Springer.
Greco, S., Ishizaka, A., Tasiou, M., & Torrisi, G. (2019). On the methodological framework of composite indices. Social Indicators Research, 141(2), 637–676.
Wang, T.C., & Lee, H.D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980–8985.
Ma, J., Fan, Z.P., & Huang, L.H. (1999). A subjective and objective integrated approach to determine attribute weights. European Journal of Operational Research, 112(2), 397–404.
Grabisch, M., & Labreuche, C. (2010). A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid. Annals of Operations Research, 175(1), 247–286.
Call, C.T. (2008). The fallacy of the ‘failed state’. Third World Quarterly, 29(8), 1491–1507.
Rotberg, R.I. (Ed.). (2003). State Failure and State Weakness in a Time of Terror. Washington DC: Brookings.
Zmerli, S., & Newton, K. (2008). Social trust and attitudes toward democracy. Public Opinion Quarterly, 72(4), 706–724.
Rose-Ackerman, S., & Palifka, B.J. (2016). Corruption and Government: Causes, Consequences, and Reform (2nd ed.). Cambridge University Press.
Margetts, H., & Naumann, A. (2017). Government as a platform: What can Estonia show the world? Research Paper. Oxford Internet Institute.
Brinkerhoff, D.W., & Brinkerhoff, J.M. (2015). Public sector management reform in developing countries: Perspectives beyond NPM orthodoxy. Public Administration and Development, 35(4), 222–237.
Mintsifry Ukraine. (2023). Diia: Digital Transformation of Ukraine. Ministry of Digital Transformation of Ukraine Annual Report.
OECD. (2023). OECD Digital Government Review: Ukraine. Paris: OECD Publishing.
Shapley, L.S. (1953). A value for n-person games. In H. Kuhn & A. Tucker (Eds.), Contributions to the Theory of Games II (pp. 307–317). Princeton University Press.
Moretti, S., & Patrone, F. (2008). Transversality of the Shapley value. TOP, 16(1), 1–41.
Charnes, A., Cooper, W.W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.
Young, H.P. (1985). Monotonic solutions of cooperative games. International Journal of Game Theory, 14(2), 65–72.
Pinar, M., Stengos, T., & Topaloglou, N. (2013). Measuring human development: A stochastic dominance approach. Journal of Economic Growth, 18(1), 69–108.
Decancq, K., & Lugo, M.A. (2013). Weights in multidimensional indices of wellbeing: An overview. Econometric Reviews, 32(1), 7–34.
Saaty, T.L. (1994). How to make a decision: The Analytic Hierarchy Process. Interfaces, 24(6), 19–43.
SIGMA. (2023). Baseline Measurement Report: Principles of Public Administration – Ukraine. Paris: OECD/SIGMA.
Verheijen, T. (Ed.). (1999). Civil Service Systems in Central and Eastern Europe. Cheltenham: Edward Elgar.
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