Logistics Efficiency under Carbon Constraints Based on a Super SBM Model with Undesirable Output: Empirical Evidence from China’s Logistics Industry

Yongrong Xin, Kengcheng Zheng, Yujiao Zhou, Yangyang Han, P. R. Tadikamalla and Qin Fan
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Yongrong Xin: Business College, Jiangsu Open University, Nanjing 210036, China
Kengcheng Zheng: School of Finance and Taxation, Zhongnan University of Economics and Law, Wuhan 430073, China
Yujiao Zhou: School of Economics, Southwestern University of Finance and Economics, Chengdu 611130, China
Yangyang Han: School of Finance, Shanghai University of Finance and Economics, Shanghai 200433, China
P. R. Tadikamalla: Joseph M. Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA 15260, USA
Qin Fan: Business College, Jiangsu Open University, Nanjing 210036, China

Sustainability, 2022, vol. 14, issue 9, 1-24

Abstract: As world resources and environmental constraints have increased, environmental cost has become a concern that affects the sustainable development of the logistics industry in various countries. Carbon emissions are an important part of any environmental cost assessment. How to scientifically and rationally evaluate the green GDP impact and regional efficiency in the logistics industry, especially when under carbon emission constraints, is of great significance to the realization of green and sustainable development. This study evaluated the logistics efficiency of 30 provinces in China from 2003 to 2016 by constructing a super SBM (Slack Based Model) model with undesirable output to explore provincial efficiency and its regional differences. The input–output ratio of the regional logistics industry was optimized through the calculation of the frontier slack variables. The research results showed that, first, it was more reasonable to adjust efficiency under carbon constraints, and it was consistent with the actual performance of the logistics industry. Second, technological progress and deeper capital investments promoted the development of the logistics industry, but technological barriers and low-scale efficiency between regions often limited technological efficiency. Therefore, decision-makers in the logistics industry should reconsider the challenges presented in each reason, encourage industrial technological innovation between regions, and especially promote energy-saving and emission-reduction technologies, so as to maintain the sustainable growth of the logistics industry.

Keywords: logistics efficiency; technological efficiency; scale efficiency; undesirable output; super SBM model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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