基于RM-DEMATEL的交通运输低碳化能力影响因素分析

›› 2018, Vol. 30 ›› Issue (1): 210-220.

基于RM-DEMATEL的交通运输低碳化能力影响因素分析

崔强^1,2,3, 徐鑫⁴, 匡海波⁴

1. 东南大学经济管理学院, 南京 211189;
2. 北京理工大学能源与环境政策研究中心, 北京 100081;
3. 北京理工大学管理与经济学院, 北京 100081;
4. 大连海事大学交通运输管理学院, 大连 116026

收稿日期:2015-10-19 出版日期:2018-01-28 发布日期:2018-01-24
通讯作者: 崔强(通讯作者),东南大学经济管理学院副教授,硕士生导师,博士。
作者简介:徐鑫,大连海事大学交通运输管理学院硕士研究生;匡海波,大连海事大学交通运输管理学院教授,博士生导师,博士。
基金资助:
国家自然科学基金项目（71403034）；中国博士后基金项目（2016M590050）。

A RM-DEMATEL-based Analysis of the Factors that Influence Low-carbon Transportation

Cui Qiang^1,2,3, Xu Xin⁴, Kuang Haibo⁴

1. School of Economics and Management, Southeast University, Nanjing 211189;
2. Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing 100081;
3. School of Management and Economics, Beijing Institute of Technology, Beijing 100081;
4. School of Transportation Management, Dalian Maritime University, Dalian 116026

Received:2015-10-19 Online:2018-01-28 Published:2018-01-24

摘要/Abstract

摘要：

为了深入推进节能减排，从根本上实现低碳化交通运输，需明确交通运输低碳化能力的影响因素并对其进行分析。提出RM-DEMATEL方法，对传统决策试验与评价实验室（DEMATEL）模型采用专家赋值法确定直接影响矩阵的主观性缺点进行改进，更加客观地对交通运输低碳化能力的影响因素进行识别。综合技术驱动力、管理驱动力、产业实力及运输结构四方面要素，建立多层交通运输低碳化能力影响因素指标体系，并对中国交通运输系统进行实证研究，研究结果表明技术驱动力因素和管理驱动力因素分别为中国交通运输低碳化能力的根本影响因素和主要影响因素，为低碳交通运输的发展策略提供理论依据。

关键词: RM-DEMATEL, 交通运输低碳化能力, 影响因素

Abstract:

In order to further promote energy conservation and emission reduction and fundamentally realize low-carbon transportation, the influencing factors of transportation low-carbonization capacity need to be definitely found out and analyzed. The RM-DEMATEL method is proposed to improve the disadvantage of traditional Decision Making Trial and Evaluation Laboratory (DEMATEL) model by subjectively using expert evaluation method to determine the direct impact matrices. The method could identify the influencing factors of transportation low-carbonization capacity more objectively. The multi-layer influencing factors index system is established, which is integrated by the four aspects of technical driving force, managerial driving force, industrial strength and transport structure. An empirical study of Chinese transportation system is carried out, the results show that the technical driving force factors are fundamental factors and managerial driving force factors are main factors of China's transportation low-carbonization capacity. This paper provides a theoretical basis for the strategy of the development of low-carbon transportation.

Key words: RM-DEMATEL, transportation low-carbonization capacity, influencing factors

崔强, 徐鑫, 匡海波. 基于RM-DEMATEL的交通运输低碳化能力影响因素分析[J]. , 2018, 30(1): 210-220.

Cui Qiang, Xu Xin, Kuang Haibo. A RM-DEMATEL-based Analysis of the Factors that Influence Low-carbon Transportation[J]. , 2018, 30(1): 210-220.

参考文献

[1] 刘建翠. 中国交通运输部门节能潜力和碳排放预测[J]. 资源科学, 2011,33(4):640-646
[2] 宿凤鸣. 低碳交通的概念和实现途径[J]. 综合运输, 2010,(5):13-17
[3] Great Britain. Department for Transport.Low Carbon Transport:A Greener Future[M]. London:Stationery Office, 2009
[4] 陆化普. 城市绿色交通的实现途径[J]. 城市交通, 2009,7(6):23-27
[5] 李大元,孙妍,杨广. 企业环境效益、能源效率与经济绩效关系研究[J]. 管理评论, 2015,27(5):29-37
[6] 曹春辉,席酉民,曹瑄玮. 企业节能减排的动因探析与策略选择[J]. 管理评论, 2013,25(7):3-10
[7] 孙曦. 我国交通运输业低碳减排研究[J]. 中国流通经济, 2014,28(2):54-58
[8] 欧阳斌,李忠奎,凤振华. 低碳交通运输规划研究现状、问题及展望[J]. 中国流通经济, 2014,(9):13-20
[9] Cheng Y. H., Chang Y. H., Lu I. J. Urban Transportation Energy and Carbon Dioxide Emission Reduction Strategies[J]. Applied Energy, 2015,157:953-973
[10] Shukla P. R., Dhar S. Energy Policies for Low Carbon Sustainable Transport in Asia[J].Energy Policy, 2015,81:170-175
[11] Mccollum D. L. Achieving Long-term Energy,Transport and Climate Objectives:Multidimensional Scenario Analysis and Modeling Within a Systems Level Framework[M]. Davis:Proquest Dissertations Publising, 2011
[12] 朱长征. 基于协整分析的我国交通运输业碳排放影响因素研究[J]. 公路交通科技, 2015,32(1):153-158
[13] 高标,许清涛,李玉波,等. 吉林省交通运输能源消费碳排放测算与驱动因子分析[J]. 经济地理, 2013,33(9):25-30
[14] Cui Q., Li Y. An Empirical Study on the Influencing Factors of Transportation Carbon Efficiency:Evidences from Fifteen Countries[J]. Applied Energy, 2015,141:209-217
[15] Wang W. W., Zhang M., Zhou M. Using LMDI Method to Analyze Transport Sector CO₂,Emissions in China[J]. Fuel & Energy Abstracts, 2011,36(10):5909-5915
[16] 王中原,魏法杰. 基于IFAHP-DEMATEL的军工企业法律风险识别研究[J]. 管理评论, 2015,27(6):68-77
[17] Baykasoglu A., Kaplanoglu V., Durmusoglu Z. D. U., et al. Integrating Fuzzy DEMATEL and Fuzzy Hierarchical TOPSIS Methods for Truck Selection[J]. Expert Systems with Applications, 2013,40(3):899-907
[18] 武春友,陈兴红,匡海波. 基于Rough-DEMATEL的企业绿色增长模式影响因素识别[J]. 管理评论, 2014,26(8):74-81
[19] 李英,朱庆华,夏西强. 基于Grey-DEMATEL方法的绿色食品可持续供应链障碍分析[J]. 当代经济管理, 2013,35(6):21-25
[20] Su C. M., Horng D. J., Tseng M. L., et al. Improving Sustainable Supply Chain Management Using a Novel Hierarchical Grey-DEMATEL Approach[J]. Journal of Cleaner Production, 2015,134:469-481
[21] 崔强,武春友,匡海波. 基于RBF-DEMATEL的交通运输低碳化能力影响因素研究[J]. 科研管理, 2013,34(10):131-137
[22] 崔强,武春友,匡海波. BP-DEMATEL在空港竞争力影响因素识别中的应用[J]. 系统工程理论与实践, 2013,33(6):1471-1478
[23] 秦晓楠,卢小丽. 基于BP-DEMATEL模型的沿海城市生态安全系统影响因素研究[J]. 管理评论, 2015,27(5):48-58
[24] Chen Y., Li J., Li Y., et al. RM-DEMATEL:A New Methodology to Identify The Key Factors in PM 2.5[J]. Environmental Science & Pollution Research, 2015,22(8):6372-6380
[25] 高沛然,卢新元. 基于区间数的拓展DEMATEL方法及其应用研究[J]. 运筹与管理, 2014,23(1):44-50
[26] Li Y., Liu J., Bao Q., et al. A New Method of Mapping Relations from Data Based on Artificial Neural Network[J]. International Journal of System Assurance Engineering & Management, 2014,5(4):544-553
[27] 毛健,赵红东,姚婧婧. 人工神经网络的发展及应用[J]. 电子设计工程, 2011,19(24):62-65
[28] Hecht-Nielsen R. Theory of the Backpropagation Neural Network[J]. Neural Networks, 1988,1(1):65-93
[29] Funahashi K. I. On the Approximate Realization of Continuous Mappings by Neural Networks[J]. Neural Networks, 1989,2(89):183-192
[30] 陆礼. 我国发展低碳交通的技术路线研究[J]. 综合运输, 2012,(6):28-32
[31] 孙焱林,李华磊,王春元. 中国贸易开放对碳排放作用机制的实证研究[J]. 国际贸易问题, 2015,(2):63-71
[32] 何凌云,程怡,范若滢,等. 国内能源相对价格对碳排放的价格杠杆作用[J]. 中国人口·资源与环境, 2015,25(11):1-11