Determinants of Low-Carbon Logistics Capability Based on Dynamic fsQCA: Evidence from China’s Provincial Panel Data

Hang Jiang, Taipeng Sun, Beini Zhuang and Jiangqiu Wu ()
Additional contact information
Hang Jiang: School of Business Administration, Jimei University, Xiamen 361021, China
Taipeng Sun: School of Business Administration, Jimei University, Xiamen 361021, China
Beini Zhuang: School of Business Administration, Jimei University, Xiamen 361021, China
Jiangqiu Wu: School of Business Administration, Jimei University, Xiamen 361021, China

Sustainability, 2023, vol. 15, issue 14, 1-19

Abstract: The fast-paced growth of the logistics industry has contributed significantly to China’s high-quality economic development. However, the growth of the logistics industry is frequently accompanied by high levels of pollution, carbon emissions, and energy consumption. How to increase low-carbon logistics capacity has emerged as a research hotspot under the dual carbon goals. This study used entropy weight TOPSIS to evaluate the low-carbon logistics capacity and dynamic fuzzy-set qualitative comparative analysis (fsQCA) to shed light on the antecedent conditions that influenced low-carbon logistics capability by using panel data from 30 Chinese provinces between 2008 and 2021. Based on the empirical results, several conclusions are drawn: (1) The comprehensive score show that while province low-carbon logistics capacity varies, most of them exhibit a general growing tendency in most provinces, where Beijing, Shanghai, Tianjin, Guangdong and Zhejiang rank among the top five. (2) Three configurations, digital empower capital intensive type, digital empower labor intensive type, and green ecology plus technology innovation type that lead to better low-carbon logistics capacity. Related policy recommendations are proposed, including strengthening the synergistic development of the digital economy and the logistics industry, promoting research and development of green and innovative technologies, and reinforcing the constraints of the dual-carbon target.

Keywords: low-carbon logistics capability; entropy weight TOPSIS; dynamic fsQCA; configurations (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/14/11372/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/14/11372/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:14:p:11372-:d:1199600

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().