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This paper aims to explore the impact of business environment on high-quality economic development (HQED) and clarify the role of technological innovation and government intervention in this relationship.

Based on China’s provincial panel data from 2010 to 2019, this paper adopts the system generalized method of moments to empirically analyze the influential mechanism and heterogeneity of the business environment on HQED. Furthermore, the authors construct a dynamic panel threshold model to test the threshold effect of government intervention.

The results indicate that optimizing the business environment can significantly promote HQED, technological innovation plays a partial mediating role in the impact of business environment on HQED, mainly by enhancing the intensity of innovation input and increasing innovation output to facilitate HQED. Government intervention can regulate the impact of business environment on HQED, and there is a double threshold effect, and it possesses an inverted U-shaped feature of first promoting and then inhibiting.

This paper examines the influence path of business environment on HQED from the perspective of technological innovation and government intervention, filling the gap in the study of provincial business environment. Moreover, the conclusions furnish a theoretical basis for optimizing the business environment and facilitating the HQED in China.

This study analyzes in-depth how knowledge-intensive small and medium-sized enterprises (SMEs) can achieve higher new product development (NPD) process performance in the epidemic era and examine the internal development mechanism of knowledge-intensive SMEs in the process of continuous digital transformation.

This issue is tested with partial least squares on data collected via a survey conducted from November 2021 to February 2022. The sample comprises 487 knowledge-intensive SMEs operating in China.

The results indicate that one form of cross-functional ambidexterity, market development strategy (MDS), plays an important role in process performance from an inside-out financial perspective and an outside-in customer perspective. Simultaneously, product innovation efficiency (PIE) mediates the relationship between MDS and the above results. Big data analytics capabilities (BDACs) positively regulate the relationship between MDS and PIE.

The authors do not consider other contingency factors. Future research should introduce influential factors such as leadership and competitive intensity to further distinguish the effects of MDS on NPD process performance.

The study findings offer suggestions to help knowledge-intensive SME managers better manage their NPD process by making better use of their limited resources in developing countries such as China.

This study is one of only a few to adopt a process-oriented perspective to specifically examine how one form of cross-functional ambidexterity, MDS, impacts knowledge-intensive SME process performance in the epidemic era. This study also extends the theoretical framework of cross-functional ambidexterity to BDAC research.