Reprint of "Performance evaluation of China's high-tech innovation process :Analysis based on the innovation value chain" |
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| Institution: | 1. Newcastle Business School, Northumbria University, UK;2. Judge Business School, Cambridge University, UK;3. National Institute of Innovation Management, Zhejiang University, China;4. Business School, Coventry University, UK;1. School of Management, University of Chinese Academy of Sciences, Beijing, China;2. School of Management, Fudan University, Shanghai, China;3. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;1. College of Economics and Management, Zhejiang Normal University, Jinhua, China;2. School of Economics and Management, Shandong Jiaotong University, Jinan, China;3. School of Management, Fudan University, Shanhai, China;1. School of Management, University of Science and Technology of China, PR China;2. Business School, University of Western Australia, Australia |
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| Abstract: | The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency. |
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| Keywords: | Innovation value chain Shared resource High-tech industry innovation Data envelopment analysis |
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