Abstract:    Optimizing urban business environment ecology is crucial for the development of enterprises′ new quality productive forces. This paper constructed an evaluation index system based on the contemporary connotation of enterprises′ new quality productive forces and combined institutional logic framework with the ecosystem coupling perspective. Using the dynamic QCA methodology and a sample of 84 strategic emerging enterprises from 2011 to 2021, the study explored the configuration paths and evolutionary patterns of the development of enterprises′ new quality productive forces driven by urban business environment ecology. The findings are as follows: (1) Individual business environment ecological factors are not necessary conditions for the development of enterprises′ new quality productive forces; (2) Four configuration paths driving enterprises′ new quality productive forces are identified as follows: human resources-oriented tightly coupled under government leadership (H1), government-led-market-regulated loosely coupled with finance (H2), government-market dual-lead tightly coupled with finance (H3), and service-oriented government-led-market-regulated loosely coupled with human resources and innovation (H4), with innovation and financial environments playing a relatively universal role; (3) The inter-group consistency of configurations between H1, H2, and H3 shows a distinct parallel fluctuation trend, with some enterprises not adhering to a single configuration, and significant regional differences in the within coverage of all four configurations. The results of this study will contribute to uncovering the “black box” of the formation mechanism of enterprises′ new quality productive forces within the urban business environment ecology, thus providing theoretical and practical insights for developing new quality productive forces in a context-specific manner.

Key words: enterprises′ new quality productive force, urban business environment ecology, ecosystem coupling perspective, institutional logic, dynamic QCA