Management system for the logistical potential of agricultural cooperatives in the context of post-war recovery in ukraine

This article investigates an adaptive management system for the logistical potential of agricultural cooperatives in Ukraine’s post-war recovery, grounded in systemic, institutional, and stochastic approaches. Russia’s full-scale invasion caused catastrophic losses to the agricultural sector: direct damages>11 billion USD(as of early 2025),total indirect losses 80–83 billion USD by end-2025(per KSE, Reuters).The sector suffered>14% reduction in sown areas, widespread infrastructure destruction, logistics costs rising to 20–30% of production costs, and restricted resource access in frontline regions. Agricultural cooperatives–vulnerable segment generating<1% value added due to historical trust deficits–face intensified challenges but possess high recovery potential via short supply chains, regional clustering, and digital transformation. Despite adaptation (2025 grain harvest~60 million tonnes per USDA/FAO), persistent bottlenecks make logistical potential management critical. The study proposes a four-module model: risk-oriented planning with Monte Carlo simulation, clustering and institutional integration, digital control integrating IoT and AI-driven analytics, regional supply chain optimization with blockchain traceability ensuring EU Green Deal/Farm to Fork compliance. Empirical validation relies on panel data from 50 cooperatives(2022–2025).Multiple linear regression with robust standard errors explains 54.5% of variance in product losses(Adj.R²=0.538,p<0.001),with infrastructure damage dominant(β=26.21,p<0.001)and digitalization mitigating(β=-11.80,p<0.001).After endogeneity correction via fixed effects and instrumental variables models, digitalization effect remains significant(β≈-9.70 to – 11.20,p<0.05).Monte Carlo simulations(1000 iterations, nonlinear beta distributions for digitalization, sensitivity analysis)predict average loss reduction of 23.6% in optimized scenarios(high digitalization>0.7).Control group(digitalization≤0.55)shows 20.97% losses; treatment group(>0.55)–13.95%,difference 7.02%.These findings underscore the transformative capacity of AI,IoT, and stochastic modeling for supply chain resilience under post-conflict uncertainty, and provide implications for post-war recovery policies, European integration, and sustainable rural development. Keywords: logistical potential, agricultural cooperatives, post-war recovery, supply chain resilience, digital transformation, stochastic modeling.