Green Innovation in Regional Logistics

Level Evaluation and Spatial Analysis

Bibliographic Data

ID15469628
AuthorsHao Zhang (0000-0003-0232-5565, Huaiyin Institute of Technology, corresponding author), Xin Sun (0000-0001-6110-5656, Huaiyin Institute of Technology), Kailong Dong (Huaiyin Institute of Technology), Lianghui Sui (Huaiyin Institute of Technology), Min Wang (0000-0001-8567-8125, Huaiyin Institute of Technology), Qiong Hong (Jiangsu Vocational College of Medicine)
Year2022
Volume20
Issue1
Pages735-735
Publication date2022-12-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph20010735
PMID36613056
OpenAlexW4313471886
LanguageEN
References cited46

Green innovation is imperative for the high-quality and sustainable development of the modern logistics industry. It is also key for achieving the goals of peak emissions and carbon neutrality. This study provides a way of thinking about the evaluation of the green innovation level of the logistics industry. The variance inflation factor-variance coefficient method was employed to construct an evaluation index system of the regional logistics green innovation level (RLGIL) from three dimensions. Empirical data were collected from statistical yearbooks covering 30 provinces in China from 2013 to 2017. Thereafter, the combination weighting-based GRA-TOPSIS method was applied to evaluate the RLGIL, and the spatial distribution differences and spatiotemporal evolution characteristics of inter-provincial green innovation levels were analyzed. The RLGILs in the 30 provinces were found to be generally unbalanced, and the differences between the eastern and western regions were significant. Guangdong, Jiangsu, and Zhejiang had stronger RLGILs, whereas most other provinces did not reach the average level. The RLGIL of the 30 provinces had a high positive spatial correlation and spatial aggregating effect. From a national perspective, the values for the RLGIL were generally higher in the eastern and southern regions and lower in the western and northern regions. Although significant differences were found in the RLGIL of these provinces, the overall development trend was stable

Business · China · Distribution (mathematics · Driving factors · Economic geography · Geography · Index (typography · Operations research · Political science · Regional science · Sustainable development · TOPSIS · Variance (accounting · Computer Science · Energy, Environment, Economic Growth · Environmental Sustainability in Business · Mathematics · Sustainable Supply Chain Management

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