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ORIGINAL RESEARCH article

Front. Environ. Sci.

Sec. Environmental Policy and Governance

Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1642985

Multiple Institutional Pressures, Government Attention Allocation, and Regional Environmental Performance: A Fuzzy-Set Qualitative Comparative Analysis Study across (FSQCA) 30 Provinces in China

Provisionally accepted
  • Kunming University of Science and Technology School of Environmental Science and Engineering, Kunming, China

The final, formatted version of the article will be published soon.

Introduction:Environmental performance is a fundamental metric for assessing the efficacy of environmental management systems and a critical determinant of regional sustainable development. Existing research has consistently identified institutional pressures as pivotal exogenous drivers of regional environmental performance, while the strategic allocation of government attention serves as its primary endogenous driver. However, a significant theoretical gap persists in understanding the synergistic mechanisms and coordinated pathways through which these two forces interact. This study, grounded in institutional logic theory and attention allocation theory, constructs an "institutional pressureattention allocation" analytical framework tailored to China's unique institutional context and governmental practices. Method:The Fuzzy-Set Qualitative Comparative Analysis (fsQCA) method can reveal complex causal pathways resulting from multiple conditional combinations. Therefore, this study takes 30 provincial-level regions in China as samples and employs the fsQCA method to systematically investigate how institutional pressures and government attention allocation jointly shape regional environmental performance through synergistic mechanisms and heterogeneous driving paths. Results:Findings reveal that regulatory,(1)Institutional pressure is a critical factor shaping how local governments allocate their attention to environmental governance.(2)No single conditional factor independently qualifies as a necessary determinant for achieving high regional environmental performance.(3)The analysis led to the identification of four distinct high-performance pathways, namely: the Strong Institutional Pressure-Driven path, the Attention-Responsive path, the Central-led Policy-Coordination path, and the Peer Competition-Regulatory Strengthening path.(4)Multiple factors exhibit both complementary and substitutive relationships. This interplay reveals the complexity of regional environmental governance and the presence of equifinality. Discussion: This study identifies four pathways to high environmental governance performance using fsQCA, demonstrating that external institutional pressure and internal attention response together form the core mechanism driving performance improvement. The "institutional pressure-attention allocation" framework developed in this study challenges the single-determinism approach, revealing local governments' proactive strategic choices and path innovation under multiple pressures, and deepening the understanding of the collaborative governance mechanism in multi-level governance.

Keywords: environmental performance, institutional pressures, Government attention allocation, Fuzzy-set Qualitative Comparative Analysis (fsQCA), Regional governance, China

Received: 07 Jun 2025; Accepted: 09 Sep 2025.

Copyright: © 2025 Su and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Yang Su, Kunming University of Science and Technology School of Environmental Science and Engineering, Kunming, China
Manchang Wu, Kunming University of Science and Technology School of Environmental Science and Engineering, Kunming, China

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