Environmental regulations and eco-innovation as catalysts for green agricultural practices: insights from Pakistan–China agricultural cooperation

Ali Raza (), Lu Hongliang (), Zhu Yue (), Tingyu Yang () and Nian Wei ()
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Ali Raza: Northeast Forestry University
Lu Hongliang: Northeast Forestry University
Zhu Yue: Northeast Forestry University
Tingyu Yang: Northeast Forestry University
Nian Wei: Northeast Forestry University

Agricultural and Food Economics, 2025, vol. 13, issue 1, 1-32

Abstract: Abstract This paper explores the adoption of green production technology within the framework of Pakistan–China agricultural cooperation under the China–Pakistan Economic Corridor. The research focus is on how farmers’ green values (FGVs) and energy use reduction (EUR) affect the adoption of green production technology (AGPT), mediating through green production willingness (GPW), with environmental regulation and eco-innovation as moderators. The study conducts an analysis based on the use of structural equation modelling (SEM) and random forest regressor (RFR), wherein the drivers of sustainable agricultural practice are discussed. For this primary quantitative study, data were gathered via the survey method from 366 rural farmers, and SEM was performed to test hypotheses. SmartPLS software was used for this purpose. The results obtained show that both FGV and EUR have significant impacts on AGPT. However, ER insignificantly influences GPW. The mediation of GPW was significant in the association between FGV and AGPT (p 0.05). The sequential mediation of GPW and AGPT was also found to be insignificant (p > 0.05), whereas AGPT has a significant impact on green supply chain performance (GSP). The moderation of environmental regulation was also insignificant (p > 0.05), while the moderation of eco-innovation was significant (p

Keywords: Farmer green values; Energy use reduction; Supply chain; Green technology; Machine learning; Random forest regress (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1186/s40100-025-00380-8

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