ЕКОСИСТЕМНИЙ ПІДХІД ДО ЦИФРОВОЇ ТРАНСФОРМАЦІЇ МОТИВАЦІЙНИХ СИСТЕМ

The accelerated digital transformation of HRM in Ukraine under wartime turbulence and the recovery agenda makes the redesign of motivation systems a strategic priority. Many organizations deploy separate digital HR solutions – performance and goal-setting modules, recognition services, learning platforms, and HR analytics – yet the outcomes remain uneven. The central challenge is fragmented digitalization: when technology is introduced without alignment to values and rules, end-to-end management processes, governance roles, and employee experience, it may amplify perceptions of control, weaken trust and fairness, and ultimately reduce engagement and retention. This article aims to substantiate an ecosystem perspective on the digital transformation of motivation systems and to develop a theory-driven model tailored to Ukrainian organizations. The method combines conceptual synthesis of recent research on HR ecosystems, digital HR strategy, employee experience, motivational climate, and resilience with logical causal modelling. The paper proposes the METM-UA model (Motivation Ecosystem Transformation Model for Ukraine), structured around five interdependent loops: (1) the value-normative loop (purpose, fairness, responsible use of data and AI), (2) the process-governance loop (process redesign, roles, and change management), (3) the technology-data loop (platform integration, data quality, and analytics), (4) the employee experience loop (EX/DEX, autonomy, competence development, feedback and recognition), and (5) the outcomes-resilience loop (engagement, retention, performance, adaptability). The model explains how integrated HR technologies influence motivation outcomes through mediators such as perceived fairness and transparency, satisfaction of basic psychological needs, and the quality of employee experience in digital interactions. The practical contribution is a structured framework for planning digital initiatives in motivation management, assigning governance responsibilities, selecting compact monitoring metrics, and reducing implementation risks while strengthening organizational resilience.