Influencing factors identification of transportation low-carbonization capacity based on the RBF-DEMATEL model

Cui Qiang; Wu Chunyou; Kuang Haibo

PDF(1 KB)

Science Research Management ›› 2013, Vol. 34 ›› Issue (10) : 131-137.

Influencing factors identification of transportation low-carbonization capacity based on the RBF-DEMATEL model

Cui Qiang¹, Wu Chunyou¹, Kuang Haibo²

Author information +

History +

Abstract

It is a hot academic topic to identify the influencing factors of transportation low-carbonization capacity which are numerous and interrelated. This study improves the traditional Decision-making Trial and Evaluation Laboratory (DEMATEL) method according to its boundedness and proposes the RBF-DEMATEL method which is suitable for the influencing factors identification of transportation low-carbonization capacity. It exploits the RBF neural network to calculate the weights between object index and influencing factor index and uses the weights to get the direct-relation matrix, then takes advantage of the traditional DEMATEL method to study the influencing factors of transportation low-carbonization capacity. The empirical analysis shows that this method is feasible and can supply theoretical support in improving the transportation low-carbonization capacity, so the RBF-DEMATEL method enriches the theory and method in studying the influencing factors and provides the possibility of extracting the fundamental influencing factors effectively.

Key words

RBF-DEMATEL / transportation low-carbonization capacity / influencing factors

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Cui Qiang, Wu Chunyou, Kuang Haibo. Influencing factors identification of transportation low-carbonization capacity based on the RBF-DEMATEL model[J]. Science Research Management. 2013, 34(10): 131-137

References

[1] Andress D, Nguyen T D, Das S. Reducing GHG emissions in the United States' transportation sector[J].Energy for Sustainable Development, 2011,15: 117-136. [2] Lakshmanan T R. Factors underlying transportation CO2 emissions in the USA: a decomposition analysis[J].Transportation Research Part D, 1997, 2(1): 1-15. [3] Bristow A L, Tight M, Pridmore A, May A D. Developing pathways to low carbon land-based passenger transport in Great Britain by 2050[J].Energy Policy, 2008, 36: 3427-3435. [4] Hickman R,Ashiru O, Banister D. Briefing: Low-carbon transport in London[J].Proceedings of the ICE-Urban Design and Planning, 2009, 162(4):151-153. [5] Geels F W. A socio-technical analysis of low-carbon transitions: introducing the multi-level perspective into transport studies[J].Journal of Transport Geography, 2012, 24:471-482. [6] 徐建闽. 我国低碳交通分析及推进措施[J].城市观察, 2010(4): 13-20. [7] Summers A, Salter M, Vergereau H. How low can transport go? Assessing transport's contribution to a low carbon economy in the east of England [C].European Transport Conference, 2010. [8] 宿凤鸣. 低碳交通的概念和实现途径[J].综合运输, 2010(5):13-17. [9] Tzeng G H, Chiang C H, Li C W. Evaluating intertwined effects in e-learning programs: a novel hybrid MCDM model based on factor analysis and DEMATEL method[J].Expert Systemwith Applications, 2007, 32:1028-1044. [10] Wu W W. Choosing knowledge management strategies by using a combined ANP and DEMATEL approach[J].Expert Systemwith Applications, 2008, 35: 828-835. [11] Kim Y. Study on impact mechanism for beef cattle farming and importance of evaluating agricultural information inKorea using DEMATEL, PCA and AHP[J].Agricultural Information Research, 2006, 15(3): 267-280. [12] Shieh J I, Wu H H, Huang K K. A DEMATEL method in identifying key success factors of hospital service quality[J].Knowledge-Based Systems, 2010, 23: 277-282. [13] 吴微. 神经网络计算[M].北京:高等教育出版社, 2007. [14] 《节能与环保》杂志社.节能手册2006[M].北京:《节能与环保》杂志社, 2006. [15] 崔强, 武春友, 匡海波. 中国空港可持续发展能力评价研究[J].科研管理, 2012, 33(4):55-61.