Capital stock and performance of R&D organizations: A dynamic DEA-ANP hybrid approach
Assessing resource allocation in R&D organizations is an important issue that requires a comprehensive measure to characterize it. To provide a greater picture, we first construct a dynamic three-stage network DEA model, which evaluates the R&D efficiency, technology-diffusion efficiency, an...
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my.uniten.dspace-229582023-05-29T14:13:42Z Capital stock and performance of R&D organizations: A dynamic DEA-ANP hybrid approach Wu Y.-C. Kweh Q.L. Lu W.-M. Hung S.-W. Chang C.-F. 57013722100 55661469500 25625212800 7201936131 57190129308 Assessing resource allocation in R&D organizations is an important issue that requires a comprehensive measure to characterize it. To provide a greater picture, we first construct a dynamic three-stage network DEA model, which evaluates the R&D efficiency, technology-diffusion efficiency, and value-creation efficiency of Taiwanese R&D organizations over the period 2005�2009. Before integrating window analysis and network data envelopment analysis (DEA) to estimate dynamic efficiencies, we apply Analytic Network Process (ANP) to determine the relative importance of each stage. Subsequently, we employ panel data regression to examine whether the capital stock of patents, quality of human resources, and capability of service support affect the dynamic efficiencies of the R&D organizations. Our findings show that the mean R&D efficiency score is greater than that of the technology-diffusion efficiency, with the value-creation efficiency score being the lowest, suggesting that R&D organizations have to firstly work on improving the technology-diffusion inefficiency, and finally improving the value-creation inefficiency. Our panel data regression analysis indicates that the capital stock of patents do affect the efficiencies of the R&D organizations, even including the quality of human resources and capability of service support. That is, managers should focus on technological development and innovation to improve their corporate performance. � Springer Science+Business Media New York 2016. Final 2023-05-29T06:13:42Z 2023-05-29T06:13:42Z 2016 Book Chapter 10.1007/978-1-4899-7705-2_7 2-s2.0-84977548226 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84977548226&doi=10.1007%2f978-1-4899-7705-2_7&partnerID=40&md5=4af80f2799fc5c4cbf3bf149349eece4 https://irepository.uniten.edu.my/handle/123456789/22958 239 167 186 Springer New York LLC Scopus |
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Assessing resource allocation in R&D organizations is an important issue that requires a comprehensive measure to characterize it. To provide a greater picture, we first construct a dynamic three-stage network DEA model, which evaluates the R&D efficiency, technology-diffusion efficiency, and value-creation efficiency of Taiwanese R&D organizations over the period 2005�2009. Before integrating window analysis and network data envelopment analysis (DEA) to estimate dynamic efficiencies, we apply Analytic Network Process (ANP) to determine the relative importance of each stage. Subsequently, we employ panel data regression to examine whether the capital stock of patents, quality of human resources, and capability of service support affect the dynamic efficiencies of the R&D organizations. Our findings show that the mean R&D efficiency score is greater than that of the technology-diffusion efficiency, with the value-creation efficiency score being the lowest, suggesting that R&D organizations have to firstly work on improving the technology-diffusion inefficiency, and finally improving the value-creation inefficiency. Our panel data regression analysis indicates that the capital stock of patents do affect the efficiencies of the R&D organizations, even including the quality of human resources and capability of service support. That is, managers should focus on technological development and innovation to improve their corporate performance. � Springer Science+Business Media New York 2016. |
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57013722100 Wu Y.-C. Kweh Q.L. Lu W.-M. Hung S.-W. Chang C.-F. |
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Wu Y.-C. Kweh Q.L. Lu W.-M. Hung S.-W. Chang C.-F. |
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Wu Y.-C. Kweh Q.L. Lu W.-M. Hung S.-W. Chang C.-F. Capital stock and performance of R&D organizations: A dynamic DEA-ANP hybrid approach |
author_sort |
Wu Y.-C. |
title |
Capital stock and performance of R&D organizations: A dynamic DEA-ANP hybrid approach |
title_short |
Capital stock and performance of R&D organizations: A dynamic DEA-ANP hybrid approach |
title_full |
Capital stock and performance of R&D organizations: A dynamic DEA-ANP hybrid approach |
title_fullStr |
Capital stock and performance of R&D organizations: A dynamic DEA-ANP hybrid approach |
title_full_unstemmed |
Capital stock and performance of R&D organizations: A dynamic DEA-ANP hybrid approach |
title_sort |
capital stock and performance of r&d organizations: a dynamic dea-anp hybrid approach |
publisher |
Springer New York LLC |
publishDate |
2023 |
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1806428125124362240 |
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13.18916 |