More than regulation: How policy mixes shape innovation ecosystems in digital transformation

The era of digital transformation drives the continuous restructuring of innovation ecosystems, challenging regulators to move beyond conventional regulations to address market and system failures. Although policy mixes are essential to address these challenges and promote innovation ecosystems, the efficacy of specific policy mix characteristics remains underexplored. This study develops a conceptual model to explore the mechanisms through which policy mix characteristics affect firm innovation in the digital transformation era. Specifically, we conceptualize policy mix coordination across three dimensions: temporal (policy stability over time), horizontal (policy similarity across regions), and vertical (policy coherence and complementarity between central and local governments). Firm innovation is examined through firms' technological and business positions within the innovation ecosystem. We conduct an empirical study of Chinese listed companies (2001-2021), employing machine learning techniques to identify policy themes, multi-source heterogeneous network analysis to measure firm innovation, and panel regression to test hypotheses. Results show that temporal and horizontal coordination stimulate firms' technological positions but inhibit business positions, whereas vertical coordination significantly enhances firms' technological positions within innovation ecosystems. These findings contribute to policy mix theory by incorporating a thematic lens and offer insights into recasting regulators' role as strategic coordinators in cultivating innovation ecosystems during digital transformation.