考虑碳排放的长三角港口群动态效率测度

doi:10.16097/j.cnki.1009-6744.2023.04.004

交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (4): 34-46.DOI: 10.16097/j.cnki.1009-6744.2023.04.004

考虑碳排放的长三角港口群动态效率测度

郑琰^*1，巴文婷¹，肖玉杰²

1. 南京林业大学，汽车与交通工程学院，南京210037；2.南京财经大学，营销与物流管理学院，南京 210023

收稿日期:2023-05-06 修回日期:2023-06-23 接受日期:2023-07-06 出版日期:2023-08-25 发布日期:2023-08-21
作者简介:郑琰(1983- )，女，河北唐山人，副教授，博士
基金资助:
国家自然科学基金(71871111, 71701099)

Dynamic Efficiency Measure in Yangtze River Delta Port Cluster Considering Carbon Emissions

ZHENG Yan^*1, BA Wen-ting¹, XIAO Yu-jie²

1. College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China; 2. School of Marketing and Logistic Management, Nanjing University of Finance and Economics, Nanjing 210023, China

Received:2023-05-06 Revised:2023-06-23 Accepted:2023-07-06 Online:2023-08-25 Published:2023-08-21
Supported by:
National Natural Science Foundation of China (71871111, 71701099)

摘要/Abstract

摘要： 为探究考虑碳排放的港口动静态效率及主要影响因素，探寻兼顾节能减排与港口自身发展的有效途径，本文采用基于松弛变量的三阶段SBM-DEA(Slack-based Measurement Model-Data envelopment Analysis)模型与方向距离函数，构建考虑非期望产出的港口动态效率测度模型；应用面板引力模型，剥离环境因素与随机噪声的影响；结合改进的Malmquist指数，根据港口投入、产出要素距前沿面映射点的相对距离计算考虑非期望产出的全要素生产率及其分解项；最后，选取长三角港口群2008—2020年16个主要港口的面板数据进行实证研究。结果表明：港口之间的效率存在明显差异，第3阶段较第1阶段效率均值提升3.474个百分点；多数港口投入指标增加，但产出指标未按同比例增长，这是因为非期望产出指标港口碳排放量逐年增长；货物运输水平增长1个百分点，港口整体泊位数、码头长度和万吨级泊位数冗余分别对应减少 0.4192、0.0436 和0.3862个百分点；考虑碳排放后港口群第3阶段效率均值下降0.062，效率值低的港口受碳排放的抑制作用较为显著；从动态变化角度来看，长三角港口群全要素生产率整体增长1.400个百分点，技术效率与纯技术效率的提升是促进港口发展的重要因素；碳排放产出会对技术进步指数、纯技术效率变动指数和ML指数产生不利影响，对港口结构加以优化及实施低碳发展战略有助于促进港口综合动态效率的提高。

关键词: 水路运输, 碳排放动态效率, 三阶段SBM-DEA模型, 长三角港口群, 改进的Malmquist全局参比指数, 全要素生产率

Abstract: This paper investigates the port dynamic and static efficiencies considering carbon emissions and major influencing factors. It explores an appropriate way to balance energy conservation and emission reduction with port development. This paper selects the panel data of 16 ports in the Yangtze River Delta port cluster in China from 2008 to 2020, combines the three-stage data envelopment analysis model based on slack variables and the distance disorientation function, and develops a model to measure the dynamic efficiency of ports considering unexpected output. The panel gravity model is applied to strip the effects of environmental factors and random noise. Combined with the improved Malmquist index, the total factor productivity and its decomposition considering unexpected output are calculated based on the relative distances of port input and output factors from the mapping points on the frontier surface. The results show that there are significant differences in efficiency between ports, and the third stage has a 3.474% increase in the mean efficiency over the first stage. The majority of port input indicators have increased but output indicators have not risen in the identical proportion, as the unexpected output indicator of port carbon emissions has increased annually. 1% increase in the level of freight would result in a corresponding reduction of 0.4192% in the overall number of berths, 0.0436% reduction of quay length, and 0.3862% reduction of, 10000-ton berth redundancy in ports. The average value of the third stage efficiency of the port cluster decreases by 0.062 after considering carbon emissions, and the ports with low efficiency values are more significantly inhibited by carbon emissions. From the perspective of dynamic changes, total factor productivity of the Yangtze River Delta port cluster increased by 1.4%, and the improvement of technical efficiency and pure technical efficiency was an important factor in promoting port development. The carbon emission output adversely affects the technological progress index, the pure technical efficiency change index and the Malmquist-Lenberger index, and the optimization of port structure and the implementation of low-carbon development strategy can help to improve the comprehensive dynamic efficiency of the port cluster.

Key words: waterway transportation, dynamic carbon efficiency, three-stage Slacks-Based Measure (SBM-DEA), Yangtze river delta port cluster, improved Malmquist index, total factor productivity

中图分类号:

郑琰, 巴文婷, 肖玉杰. 考虑碳排放的长三角港口群动态效率测度[J]. 交通运输系统工程与信息, 2023, 23(4): 34-46.

ZHENG Yan, BA Wen-ting, XIAO Yu-jie. Dynamic Efficiency Measure in Yangtze River Delta Port Cluster Considering Carbon Emissions[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(4): 34-46.

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http://www.tseit.org.cn/CN/Y2023/V23/I4/34

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考虑碳排放的长三角港口群动态效率测度

Dynamic Efficiency Measure in Yangtze River Delta Port Cluster Considering Carbon Emissions

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