The developmental level of high-tech industries bears a close connection to a region’s overall competitiveness, and accurately identifying the differences in innovation capabilities during the R&D and transformation phases of these industries plays a vital role in developing targeted policies. Taking into account the features of panel data related to high-tech industries, this paper develops a grey matrix-type relational clustering model based on panel data by applying grey relational analysis. This model is used to assess the technological innovation capacities of high-tech industries across 30 provinces (including municipalities directly under the Central Government and autonomous regions) in China (with the Tibet Autonomous Region excluded) and identify variations from the two perspectives of "technological R&D" and "achievement transformation". The findings show that the general innovation capacity of China’s high-tech industries remains relatively low, and there is a notable regional imbalance; the hierarchy of innovation capacities follows a pattern where eastern provinces/municipalities outperform central provinces/municipalities, which in turn are superior to northwestern provinces/municipalities. Furthermore, the two-phase clustering ultimately results in six provincial/municipal combination categories, laying a precise foundation for policy development.
