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The relevance of this study is determined by the strategic shift in the development of the Russian forest industry complex, moving from an extensive model toward accelerated deep processing and digitalization, as enshrined in the Forestry Development Strategy until 2030 and the launch of the Federal State Information System for Forestry on January 1, 2025. A region's raw material supply is no longer an unconditional indicator of enterprises' technological viability, necessitating a distinction between forest resource and innovation and technological potential at the interregional analytical level. The objective of this study is to develop and empirically test a methodology for comparatively assessing the innovation and technological potential (ITP) of forestry enterprises through the construction of an integrated index. The empirical basis for the study is based on data from scientific papers on forest region strategy, digitalization of the forestry industry, and cluster mechanisms, as well as official statistics from Rosstat, materials from the Federal Forestry Agency, the Innovative Development Ranking of Russian Federation Subjects (ISSEZ HSE), and data from regional investment portals. The innovative and technological status of forestry enterprises in five forest-rich regions of the Russian Federation for the period 2023–2025 is examined through the prism of a five-component integrated model. Three regional trajectories for converting raw material resources into technological advantages are classified. The scientific novelty lies in the development of an original fivecomponent index model specifically adapted to the architecture of the forest bioeconomy. The practical significance lies in the potential use of the developed integrated index by executive authorities of the constituent entities of the Russian Federation and relevant ministries as a tool for the objective selection of priority investment projects, the calibration of state support measures, and the monitoring of the digital transformation of forest enterprises within the FGIS LK architecture.
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Кузнецова et al. (2026) studied this question.
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