Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain
Xiafei Chen,
Zhiying Liu and
Qingyuan Zhu
Technovation, 2018, vol. 74-75, 42-53
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.
Keywords: Innovation value chain; Shared resource; High-tech industry innovation; Data envelopment analysis (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166497218301238
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:74-75:y:2018:i::p:42-53
DOI: 10.1016/j.technovation.2018.02.009
Access Statistics for this article
Technovation is currently edited by Jonathan Linton
More articles in Technovation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().