ORIGINAL RESEARCH article
Front. For. Glob. Change
Sec. Forest Management
Study on the Path of Green Total Factor Productivity Improvement in Forestry in China under Spatio-Temporal Heterogeneity: Based on Dynamic QCA Analysis
Provisionally accepted
- 1Beijing Forestry University, Beijing, China
- 2Dalian Jiaotong University, Dalian, China
- 3Dalian University of Technology, Dalian, China
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Under the common agenda of addressing global climate change and promoting sustainable development, forestry has become a key area for achieving carbon neutrality and ecological product value. Forestry Green Total Factor Productivity (GTFP) is a core indicator for measuring the low-carbon transformation and green growth capacity of forestry. Based on panel data from 30 provinces (regions) in China from 2005 to 2022, this paper uses the global reference super efficiency SBM model to measure forestry GTFP. Based on the center of gravity model and spatial autocorrelation, the spatiotemporal evolution trend is revealed. The Dagum Gini coefficient is used to analyze the regional differences and their sources. This study applies dynamic QCA to identify multidimensional configurational paths for forestry GTFP improvement at the provincial level. It further clarifies spatiotemporal evolution patterns, sources of regional disparities, and multiple driving mechanisms, thereby systematically revealing the dynamics of forestry green development and providing a basis for exploring sustainable forestry growth models. The results showed that: (1) The overall trend of forestry GTFP showed a fluctuating upward trend, with the mean increasing from 0.75 to 1.27. The spatial pattern evolved from local point aggregation to multipolar diffusion, and high-value areas exhibited significant spatial spillover effects; (2) The overall differences in forestry GTFP show a fluctuating convergence trend, with the overall Gini coefficient decreasing from 0.275 to 0.198. Regional differences are the main source of overall imbalance, and some low-value areas exhibit catch-up effects; (3) The seven conditional variables are not necessary conditions, and six configuration modes are identified for four paths: resource capital driven, capital driven, resource industry driven, and management industry driven. Based on these findings, this study proposes a new development paradigm for forestry new-quality productive forces, emphasizing strengthened foundational capacity, quality-and efficiency-oriented upgrading, institutional innovation, and whole-process regulation and management.
Keywords: Configuration perspective, dynamic QCA, Forestry green total factor productivity, IMO model, Upgrading pathways
Received: 10 Feb 2026; Accepted: 16 Feb 2026.
Copyright: © 2026 Xu, zhang, cao, wang and lin. 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: when lin
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