Improving a data-driven model of adaptive management for service enterprises in the Aral Sea region

Abstract

The article examines a data-driven model of adaptive management for service enterprises in the Aral Sea region of Uzbekistan. Water scarcity, soil salinization and labour market constraints caused by the shrinking of the Aral Sea directly affect the stability of local service businesses. Drawing on adaptive management theory, service management and data analytics, the study proposes a five-stage management cycle comprising monitoring, analysis, adaptive decision-making, implementation and evaluation. The model links a set of performance indicators to concrete adaptive decisions, allowing enterprises to adjust their operations as external conditions change. The approach may serve as a practical basis for the regional service sector.