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

Abstract

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

CLC Number:

F503

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

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