Modeling the intellectual maturity of industrial ecosystems using data-driven approaches and the modified analytic hierarchy process

The purpose of the study is to develop and empirically validate a data-driven managerial model for assessing the intellectual maturity of industrial ecosystems using the modified Analytic Hierarchy Process. The research hypothesis assumes that the intellectual maturity of industrial ecosystems is formed as a synergistic outcome of the interaction among strategic, process, organizational, data-related, architectural, and operational-innovation dimensions, rather than as the sum of their isolated characteristics.

The research methodological framework integrates the classical Saaty procedure with entropy-based weight objectification and an inter-dimensional interaction matrix, which makes it possible to account for nonlinear relationships and to reduce the subjectivity of expert judgments through the analysis of data variability.

The empirical validation has been conducted on an expert sample representing enterprises from the mechanical engineering, chemical-technological, pharmaceutical, and IT sectors. The average integrated level of intellectual maturity amounted to 3.6 on a 0–5 scale, corresponding to a transition from the Managed to the Established level. The highest levels of intellectual maturity have been observed in the strategic and architectural dimensions (3.9 and 3.8, respectively), forming the core of ecosystem maturity, while the process dimension has also demonstrated values close to the established level (3.7). At the same time, the organizational, data-related, and operational-innovation dimensions have exhibited lower maturity levels (3.4, 3.2, and 3.3, respectively).

The obtained study results confirm the applicability of the mo­ dified Analytic Hierarchy Process for the quantitative assessment and forecasting of the intellectual development of industrial ecosystems. The practical value of the study lies in the possibility of using the proposed model to design maturity-enhancement roadmaps, define priorities for digital and AI transformation, and support the transition from fragmented digitalization to sustai­ nable data-driven governance.

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