Dynamic capabilities in higher education: how big data analytics fuels digital service innovation in Chinese HEIs

Although extant literature often concentrates on data steered approaches to enhance students’ academic performance, it discusses digital innovation in tertiary education in broad strokes. However, the combined impact of analytical capabilities, big data, and contemporary digital service revolution relating to Chinese higher education institutions (HEIs) remains significantly undiscovered. To mitigate existing research gaps, this study investigates the intersection of big data, analytical insights, and digital services innovation capabilities in Chinese HEIs. The study employed a cluster sampling approach across four provinces—Beijing, Tianjin, Hebei, and Hubei—and collected data from 272 HEIs through multiple sources using a matched-pair design. The data were analyzed using variance-based structural equation modelling. Findings revealed that big data analytics factors, such as data, technology, basic resources, and data-driven culture, have a positive and significant influence on data-driven insights that lead to digital service innovation capabilities. Technical skills, managerial skills and the moderating role of digital leadership were insignificant in establishing the relationship between data-driven insights and digital service innovation capabilities. From a theoretical standpoint, this study aims to extend the dynamic capabilities theory in the landscape of HEIs by demonstrating how HEIs can leverage dynamic capabilities to foster digital service innovation capabilities. From a practical standpoint, this study suggests to HEIs across China that big data analytics factors are critical to drawing data-driven insights in HEIs for digital service innovation capabilities.