ORIGINAL RESEARCH
Achieving Low-Carbon Goals: Analysis of the Configuration Path for Manufacturing Enterprises to Reduce Carbon Emissions Intensity
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1
School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, China
 
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Roehampton Business School, University of Roehampton, London, SW155SL, UK
 
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College of Economy and Management, Changsha University, Changsha, Hunan, 410022, China
 
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Institute of Quantitative Economics and Statistics, Huaqiao University, Xiamen, Fujian, 361021, China
 
 
Submission date: 2024-09-08
 
 
Final revision date: 2024-11-07
 
 
Acceptance date: 2024-12-02
 
 
Online publication date: 2025-03-25
 
 
Publication date: 2026-01-30
 
 
Corresponding author
Hui Wang   

College of Economy and Management, Changsha University, 410022, Changsha, China
 
 
Pol. J. Environ. Stud. 2026;35(1):853-870
 
KEYWORDS
TOPICS
ABSTRACT
Enterprise carbon emissions intensity (CEI) is an important measure of corporate environmental responsibility management. Existing studies exploring the net effects of single factors are insufficient to fully reveal the complex causal relationships behind them. Taking the top 40 listed manufacturing enterprises in China as examples, this study adopted the technological, organizational, and environmental (TOE) framework and selected green technology innovation, digital transformation, dual carbon leadership, financial redundancy, environmental regulatory pressure, and public environmental concern as the key antecedents influencing CEI. This study employs necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis (fsQCA) methods to identify the configuration path of CEI in manufacturing enterprises and uses machine learning to rank the importance of antecedent variables. The findings reveal that no single factor alone is necessary or sufficient for determining the CEI. This study identified five different configurational pathways associated with a low CEI and three different pathways with a higher CEI. Machine learning shows that green technology innovation is the most important antecedent factor affecting CEI. These insights provide valuable guidance for manufacturing companies that adopt practices that facilitate low-carbon transformations.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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