Industrial ecosystem digitalization: from product to service model

The article an empirical validation of an integrated methodology for evaluating the digitalization effectiveness of an industrial enterprise and links it with the diagnostic assessment of business ecosystem evolutionary stages. The study employs an integrated index (IIE) aggregating economic, operational, technical, social, and market performance indicators across five key domains.

The methodology incorporates data normalization procedures with a significance threshold parameter and the Analytic Hierarchy Process (AHP) for component weighting. The empirical base comprises data from a large electrical machinery plant covering the 2022–2024 period. Qualitative assessment of the ecosystem’s evolutionary stage is conducted through a diagnostic gates rubric that identifies structural conditions for transitions between product, service, and platform models. The analysis reveals steady growth in integrated digitalization effectiveness accompanied by a natural deceleration during the high-maturity phase; at advanced stages, market and social outcomes contribute more significantly to overall dynamics than direct economic indicators. Based on the diagnostic results, the enterprise is positioned as a developed digital product ecosystem, and high internal technological maturity does not guarantee a transition to a service model without establishing external data loops and regular service orchestration mechanisms.

The scientific originality lies in developing an approach that utilizes quantitative effectiveness indicators as objective evidence of an enterprise’s readiness for structural evolutionary shifts. The practical value of the study derives from the applicability of the proposed tools to identify bottlenecks in digital transformation programs and to justify development priorities for business ecosystems.

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