Econometric analysis of the R&D performance in the national hydrogen energy technology development for measuring relative efficiency: The fuzzy AHP/DEA integrated model approach |
| |
Authors: | Seong Kon Lee Gento Mogi Sang Kon Lee KS Hui Jong Wook Kim |
| |
Affiliation: | 1. Energy Policy Research Center, Korea Institute of Energy Research, 71-2, Jang-dong, Yuseong-gu, Daejeon 305-343, Republic of Korea;2. Department of Technology management for innovation, Graduate School of Engineering, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656, Japan;3. PNU-IFAM Joint Research Center, Pusan National University, 30 Jangjeon-Dong, Kumjeong-Gu, Busan 609-735, Republic of Korea;4. Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong |
| |
Abstract: | Hydrogen energy technology can be one of the best key players related to the sector of the United Nations Framework Convention on Climate Change (UNFCCC) and the hydrogen economy. Comparing to other technologies, hydrogen energy technology is more environmentally sound and friendly energy technology and has great potential as a future dominant energy carrier. Advanced nations including Korea have been focusing on the development of hydrogen energy technology R&D for the sustainable development and low carbon green society. In this paper, we applied the integrated fuzzy analytic hierarchy process (Fuzzy AHP) and the data envelopment analysis (DEA) for measuring the relative efficiency of the R&D performance in the national hydrogen energy technology development. On the first stage, the fuzzy AHP effectively reflects the vagueness of human thought. On the second stage, the DEA approach measures the relative efficiency of the national R&D performance in the sector of hydrogen energy technology development with economic viewpoints. The efficiency score can be the fundamental data for policymakers for the well focused R&D planning. |
| |
Keywords: | Hydrogen energy competitiveness Fuzzy AHP DEA MCDM |
本文献已被 ScienceDirect 等数据库收录! |
|