Effective policy mixes in entrepreneurial ecosystems: a configurational analysis in China

Policy-makers are seeking to build vibrant entrepreneurial ecosystems (EEs) to promote innovative entrepreneurship. However, the role of government policy in EEs, especially in the emerging economy context, is poorly understood, lacking a systematic concept of policy and theoretical framework, clear policy classification, and empirical research considering distinctive characteristics of policy mixes in EEs. This paper introduces the concept of EE policy mixes and classifies them into seven policy instruments. Using data from 21 national high-tech zones (NHZs) in China, fuzzy-set qualitative comparative analysis (fsQCA) is applied to identify effective configurations of EE policy mixes that support early-stage and late-stage technology start-ups to produce high entrepreneurial performance. The configurational analysis shows that EE policy mixes present causal complexity and stage differences. Based on interpreting multiple policy interactions, we reveal the differentiated support mechanisms of EE policy mixes in NHZs and draw out their implications for research, policy, and practice. This study contributes to the EE literature by adopting a policy-mix perspective to examine the role of policy, exploring the specific emerging economy context of China, suggesting further extensions of the research to other contexts, and applying a methodology that reveals causal mechanisms. It also supports better-informed EE policy and governance. Plain English Summary How to maximize the potential of policy in entrepreneurial ecosystems (EEs)? Revealing the causal complexity, stage differences, and support mechanisms of policy mixes in China's EEs. This study applies a policy-mix concept and a configurational analysis approach to explore the role of government policy in EEs. Taking China's national high-tech zones-a unique model of EEs in emerging economies-as the empirical context, we identify effective configurations of EE policy mixes supporting high early- and late-stage entrepreneurial performance. The findings show that EE policy mixes present causal complexity, reflected in the "joint effects" of policy instruments and multiple equally effective configurations, and stage differences, reflected in the differentiated support mechanisms for early- and late-stage start-ups in three dimensions. The principal implication is that policy-makers should design, implement, and evaluate EE policy from a holistic, interrelated policy-mix perspective, and consider fully local contextual applicability, entrepreneurial growth characteristics, and ecosystem maturity.