Journal article
Evaluation of multi-period regional R&D; efficiency: An application of dynamic DEA to China's regional R&D; systems
- Abstract:
- The existing studies about regional R&D; efficiency measurement in a specific period have not considered the dynamic interdependence between regional R&D; activities over different periods. This paper offers a solution to this problem in multi-period regional R&D; efficiency measurement with a novel application to China's regional R&D; systems. This solution can present a systemic measurement for the overall efficiency score of multi-period regional R&D; investment activities, and deduce a weighted decomposition of the overall efficiency score into period efficiency scores. This paper develops a dynamic analytical framework with a new estimation technique from a long-term and systemic perspective associated with data envelopment analysis technique. Our efficiency model with endogenous weights on period efficiencies effectively accounts for the linking function and double role of R&D; capital stock in the operation of connected regional R&D; systems and the intertemporal dependence of R&D; investment on R&D; outputs. The R&D; capital stock as the carry-over estimated using the perpetual inventory method helps this efficiency model to account for the time lag and multi-period influence of R&D; inputs on R&D; outputs. This approach is applied to a new database of R&D; input-output systems in China's provinces during the first five-year period (2006–2010) after China's National Plan for Medium- and Long-term Scientific and Technological Development (NPMLSTD).
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 985.9KB, Terms of use)
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- Publisher copy:
- 10.1016/j.omega.2017.01.010
Authors
- Publisher:
- Elsevier
- Journal:
- Omega More from this journal
- Volume:
- 74
- Pages:
- 103-114
- Publication date:
- 2017-03-06
- Acceptance date:
- 2017-01-18
- DOI:
- ISSN:
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0305-0483
- Language:
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English
- Keywords:
- Pubs id:
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pubs:687551
- UUID:
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uuid:cc005b2f-eb2d-41af-b240-36c74ba2c129
- Local pid:
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pubs:687551
- Source identifiers:
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687551
- Deposit date:
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2019-02-01
- ARK identifier:
Terms of use
- Copyright holder:
- Crown Copyright
- Copyright date:
- 2017
- Notes:
- Crown Copyright © 2017 Published by Elsevier Ltd. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.omega.2017.01.010
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