Development efficiency of green logistics in Guangdong province based on Super-SBM and GML index

Under China's national sustainability strategy, the logistics industry is confronted with the imperative of high-quality green development. Given its status as the leading economic province and a national logistics hub, investigating green logistics development in Guangdong province holds paramount strategic importance. To comprehensively evaluate green logistics development efficiency of 21 cities in Guangdong from 2016 to 2022, this study employed the super-efficiency slacks-based measure model (Super-SBM) with undesirable outputs, the Global Malmquist-Luenberger (GML) productivity index and a four-quadrant analysis based on static and dynamic efficiency. With its integrated framework, this study dynamically assesses and meticulously classify green logistics efficiency in Guangdong, thereby offering unique perspectives and deep insights for regional policy formulation. The results reveal three key aspects. First, Guangdong's overall green logistics efficiency remains relatively low with a slight downward trend, exhibiting significant regional and inter-city disparities. The Pearl River Delta(PRD) region, particularly Shenzhen and Guangzhou, consistently shows the highest and increasing efficiency, contrasting sharply with other regions. Second, technological progress is identified as the primary driver of changes in green logistics efficiency. Third, the four-quadrant analysis reveals distinct patterns among the 21 cities, classifying them into four categories: "high-efficiency-growth" (e.g., Shenzhen and Guangzhou), "high-efficiency-regression" (e.g., Dongguan), "low-efficiency-growth" (e.g., Zhuhai and Zhaoqing), and "low-efficiency-regression" (e.g., Meizhou and Shantou). Finally, this study puts forward key policy recommendations to promote green logistics development in Guangdong, including driving green transformation through the realignment of industrial and economic foundations, strengthening core cities' green logistics leadership and regional collaboration, enhancing technological innovation capacity, and implementing precise and targeted support for cities across all four quadrants.

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Journal
PLoS ONE
Published
2025-09-09
DOI
https://doi.org/10.1371/journal.pone.0331893
Primary Topic
Efficiency Analysis Using DEA
Type
article
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article

Development efficiency of green logistics in Guangdong province based on Super-SBM and GML index

Y. Wang
PLoS ONE
Efficiency Analysis Using DEA
article

Development efficiency of green logistics in Guangdong province based on Super-SBM and GML index

Y. Wang
article en

Abstract

Under China's national sustainability strategy, the logistics industry is confronted with the imperative of high-quality green development. Given its status as the leading economic province and a national logistics hub, investigating green logistics development in Guangdong province holds paramount strategic importance. To comprehensively evaluate green logistics development efficiency of 21 cities in Guangdong from 2016 to 2022, this study employed the super-efficiency slacks-based measure model (Super-SBM) with undesirable outputs, the Global Malmquist-Luenberger (GML) productivity index and a four-quadrant analysis based on static and dynamic efficiency. With its integrated framework, this study dynamically assesses and meticulously classify green logistics efficiency in Guangdong, thereby offering unique perspectives and deep insights for regional policy formulation. The results reveal three key aspects. First, Guangdong's overall green logistics efficiency remains relatively low with a slight downward trend, exhibiting significant regional and inter-city disparities. The Pearl River Delta(PRD) region, particularly Shenzhen and Guangzhou, consistently shows the highest and increasing efficiency, contrasting sharply with other regions. Second, technological progress is identified as the primary driver of changes in green logistics efficiency. Third, the four-quadrant analysis reveals distinct patterns among the 21 cities, classifying them into four categories: "high-efficiency-growth" (e.g., Shenzhen and Guangzhou), "high-efficiency-regression" (e.g., Dongguan), "low-efficiency-growth" (e.g., Zhuhai and Zhaoqing), and "low-efficiency-regression" (e.g., Meizhou and Shantou). Finally, this study puts forward key policy recommendations to promote green logistics development in Guangdong, including driving green transformation through the realignment of industrial and economic foundations, strengthening core cities' green logistics leadership and regional collaboration, enhancing technological innovation capacity, and implementing precise and targeted support for cities across all four quadrants.

PLoS ONEVol. 20(9)
Guangzhou Vocational College of Science and Technology (CN)
Openalex Percentile: Top 71%
Efficiency Analysis Using DEA
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