Measuring Logistics Efficiency in China Considering Technology Heterogeneity and Carbon Emission through a Meta-Frontier Model

Hao Zhang, Jianxin You, Xuekelaiti Haiyirete and Tianyu Zhang
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Hao Zhang: School of Economics and Management, Tongji University, Shanghai 200092, China
Jianxin You: School of Economics and Management, Tongji University, Shanghai 200092, China
Xuekelaiti Haiyirete: School of Economics and Management, Tongji University, Shanghai 200092, China
Tianyu Zhang: The York Management School, University of York, York YO10 5GB, UK

Sustainability, 2020, vol. 12, issue 19, 1-18

Abstract: Due to the differences in the economic and social environment, production technology heterogeneity exists in the logistics industry among provinces in China. If this fact is ignored, the evaluation result of logistics efficiency may be biased. To this end, this study developed a new analysis framework for evaluating logistics efficiency with the consideration of technology heterogeneity and carbon emission through a metafrontier data envelopment analysis (DEA) method. Furthermore, the source of logistics inefficiency were identified. The proposed method was employed in the regional logistics industry in China from 2011 to 2017. The following empirical findings could be drawn: (1) The overall logistics efficiency is low in China, and great potential exists in improving logistics efficiency. (2) Significant disparities exist in logistics efficiency and the technology gap among the three areas. The east area has higher logistics efficiency with advanced technology, while the central area and the west area have lower logistics efficiencies. (3) The technology gap and management issues in the utilization of logistics resources are the two primary reasons resulting in the logistics efficiency loss in China. The effect of the management factor is significant in the east area, while the impact of the technology gap is dominant in the central area and the west area. Some policy suggestions for enhancing logistics efficiency are provided.

Keywords: logistics efficiency; technology heterogeneity; carbon emission; slack-based measure (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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