Does Chinese forestry eco-efficiency converge? A three-stage DEA-Malmquist approach

Chen, Yufeng; Ma, Lihua; Miao, Jiafeng; Hui, Xiaoxiong

doi:10.1007/s10342-023-01573-w

Eur J Forest Res

2023

DOI: 10.1007/s10342-023-01573-w

|View full text |Cite|

Does Chinese forestry eco-efficiency converge? A three-stage DEA-Malmquist approach

Yufeng Chen

Lihua Ma

Jiafeng Miao

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Forestry Resource Efficiency, Total Factor Productivity Change, and Regional Technological Heterogeneity in China

Shah,

Hao,

Yan

et al. 2024

Forests

View full text Add to dashboard Cite

The efficient and sustainable management of forestry resources is crucial in ensuring economic and societal sustainability. The Chinese government has invested significantly in regulations, afforestation, and technology to enhance the forest resource efficiency, reduce technological disparities, and boost productivity growth. However, the success level of this undertaking is unclear and worth exploring. To this end, this study applied DEA-SBM, meta-frontier analysis, and the Malmquist productivity index to gauge the forest resource efficiency (FRE), regional technology heterogeneity (TGR), and total factor productivity growth (MI) in 31 Chinese provinces for a study period of 2001–2020. Results revealed that the average FRE was 0.5430, with potential growth of 45.70%, to enhance the efficiency level in forestry resource utilization. Anhui, Tibet, Fujian, Shanghai, and Hainan were found to be the top performers in forestry utilization during the study period. The southern forest region was ranked highest, with the highest TGR of 0.915, indicating advanced production technologies. The average MI score was 0.9644, signifying a 3.56% decline in forestry resource productivity. This deterioration is primarily attributed to technological change (TC), which decreased by 5.2%, while efficiency change (EC) witnessed 1.74% growth over the study period. The Southern Chinese forest region, indicating an average 3.06% increase in total factor productivity, ranked highest in all four regions. Guangxi, Tianjin, Shandong, Chongqing, and Jiangxi were the top performers, with prominent growth in MI. Finally, the Kruskal–Wallis test found a significant statistical difference among all four regions for FRE and TGR.

show abstract

Forestry Resource Efficiency, Total Factor Productivity Change, and Regional Technological Heterogeneity in China

Shah,

Hao,

Yan

et al. 2024

Forests

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Does Chinese forestry eco-efficiency converge? A three-stage DEA-Malmquist approach

Cited by 1 publication

References 44 publications

Forestry Resource Efficiency, Total Factor Productivity Change, and Regional Technological Heterogeneity in China

Forestry Resource Efficiency, Total Factor Productivity Change, and Regional Technological Heterogeneity in China

Contact Info

Product

Resources

About