Study on the path of green total factor productivity improvement in forestry in China under spatio-temporal heterogeneity: based on dynamic QCA analysis

Introduction 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. Methods Based on panel data from 30 provinces (regions) in China from 2005 to 2022, this study uses the global super efficiency SBM model to measure forestry GTFP in each province, combines the center of gravity model and spatial autocorrelation analysis to reveal the spatiotemporal distribution characteristics and evolutionary trends of forestry GTFP, applies the Dagum Gini coefficient to decompose regional differences and their sources, and identifies multidimensional configurational paths for enhancing provincial forestry GTFP through the dynamic qualitative comparative analysis (QCA) method, revealing the forestry green growth patterns and their driving mechanisms under different combinations of conditions. Results (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. Discussion Based on these findings, this study proposes to build a new pattern of new quality productivity of forestry that is oriented toward consolidating foundational capacity, centered on improving quality and efficiency, with institutional innovation as the guiding thread, and ensured through full-process regulation and management.

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Journal
Frontiers in Forests and Global Change
Published
2026-03-16
DOI
https://doi.org/10.3389/ffgc.2026.1763211
Primary Topic
Qualitative Comparative Analysis Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Study on the path of green total factor productivity improvement in forestry in China under spatio-temporal heterogeneity: based on dynamic QCA analysis

Deya Xu, Yuxuan Wang, Zhen Lin, Yunfan Zhang et al.
Frontiers in Forests and Global Change
Qualitative Comparative Analysis Research
article

Study on the path of green total factor productivity improvement in forestry in China under spatio-temporal heterogeneity: based on dynamic QCA analysis

Deya Xu, Yuxuan Wang, Zhen Lin, Yunfan Zhang, Congcong Cao
article en

Abstract

Introduction 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. Methods Based on panel data from 30 provinces (regions) in China from 2005 to 2022, this study uses the global super efficiency SBM model to measure forestry GTFP in each province, combines the center of gravity model and spatial autocorrelation analysis to reveal the spatiotemporal distribution characteristics and evolutionary trends of forestry GTFP, applies the Dagum Gini coefficient to decompose regional differences and their sources, and identifies multidimensional configurational paths for enhancing provincial forestry GTFP through the dynamic qualitative comparative analysis (QCA) method, revealing the forestry green growth patterns and their driving mechanisms under different combinations of conditions. Results (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. Discussion Based on these findings, this study proposes to build a new pattern of new quality productivity of forestry that is oriented toward consolidating foundational capacity, centered on improving quality and efficiency, with institutional innovation as the guiding thread, and ensured through full-process regulation and management.

Frontiers in Forests and Global ChangeVol. 9
Dalian University of Technology (CN), Lanzhou Jiaotong University (CN), Beijing Forestry University (CN)
Ministry of Education, India
Openalex Percentile: Top 24%
Qualitative Comparative Analysis Research
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