Significance of the Study
2015 한국경영정보학회 추계통합학술대회
The Determinants of National Biotechnology Innovation Capacity
이상원 (경희대학교 언론정보학과)
(경희대 언론정보학과) 이상원 (경희대 언론정보학과) 김도한 (경희대학교 행정학과)
1
Significance of the Study Innovation in biotechnology has become a key component
of the knowledge economy and national competitiveness. Well-established information and communications
technology (ICT) infrastructure such as broadband and R&D expenditure are necessary to promote national-level innovation in biotechnology. Employing panel data from 33 OECD countries, this study
investigates drivers of national biotechnology innovation capacity (Macro-level approach)
Drivers of technological innovation in Biotech Industry !!!
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2
2015 한국경영정보학회 추계통합학술대회
Purpose of the Study This study examines The effects of macro-level drivers of technological innovation in biotech industry: Broadband Diffusion R& D expenditure R&D expenditure by government Education Income
3
The Status of Biotechnology Innovation, Broadband Infrastructure, R&D expenditure 2.5
80
70 2 60
50
1.5
40 1
30
20 0.5 10
0
0 1999
2000
2001 2002 2003 2004 cumulative biotechnology
2005 2006 2007 2008 2009 cumulative fixed broadband
2010 2011 2012 R&D expenditures
2013
The biotechnology patent statistics show that while there has been a steady growth in worldwide biotechnology innovation capacity, a wide range of biotechnology innovation levels exists across countries.
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4
2015 한국경영정보학회 추계통합학술대회
The Empirical Model A country fixed effect model for the estimation This study employs a fixed effect model, which controls for the unobserved heterogeneity among countries. LnBit = β0it + β1it*lnFixedBroadband + β2it*RD + β3it*RD_GOV + β4it*(RD_GOV)2 + β5it*EDU + β6it*INC + δiZi + εit
LnBit: Biotech Innovation in country i in time t
β0it : Constant Zit : Country-dummies εit : Error Term 5
The Model, Method, and Data Variables Biotechnology innovation Fixed broadband
Measurement Cumulative patents grants in biotechnology per 1,000,000
Data sources OECD
inhabitants between 1999-2013 Fixed-broadband subscribers per 100 inhabitants
ITU
penetration R&D expenditure
Research and development expenditure (percent of GDP)
World Bank
R&D financed by
R&D financed by government (percentage of total R&D financed)
World Bank
Education
School enrollment, secondary (percent of GDP)
World Bank
Income
GDP per capita
World Bank
government
Data Sources: Yearly Data (1999-2013) from OECD, World Bank, ITU, Data for 33 countries 6
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2015 한국경영정보학회 추계통합학술대회
Empirical Results: Fixed effect OLS model (1)
(2)
(3)
(4)
0.190*** (0.051)
0.040** (0.017) 0.160*** (0.051)
0.006*** (0.002) 0.000*** (0.000) -0.958*** (0.322)
0.005*** (0.002) 0.000 (0.000) -0.710** (0.301)
0.005*** (0.002) 0.000** (0.000) -0.944*** (0.318)
0.030* (0.017) 0.118** (0.052) 0.046*** (0.013) -0.001*** (0.000) 0.006*** (0.002) 0.000*** (0.000) -1.853*** (0.424)
473 0.931 33
492 0.933 33
473 0.933 33
473 0.937 33
VARIABLES Fixed broadband penetration
0.034** (0.017)
R&D expenditure R&D government financed (R&D government financed)2 Education Income Constant
Observations R-squared Number of country
* Statistically significant at the 10% level ** Statistically significant at the 5% level ***Statistically significant at the 1% level
Empirical Results: Fixed effect OLS model (Broadband lagged variable) (1) VARIABLES Fixed broadband penetration (lagged variable) R&D expenditure R&D government financed (R&D government financed)2 Education Income Constant Observations R-squared Number of country
(2)
(3)
Two-year lagged
Three-year lagged
0.029*
0.026*
0.039***
(0.015) 0.105** (0.048) 0.033** (0.013) -0.000*** (0.000) 0.005*** (0.002) 0.000*** 0.029* 0.845** (0.421) 441 0.931 33
(0.014) 0.100** (0.045) 0.020 (0.012) -0.000** (0.000) 0.005*** (0.001) 0.000*** (0.000) -0.274 (0.383) 408 0.925 33
(0.014) 0.114** (0.045) 0.012 (0.013) -0.000 (0.000) 0.004*** (0.002) 0.000*** (0.000) 1.427*** (0.432) 375 0.914 33
One-year lagged
* Statistically significant at the 10% level ** Statistically significant at the 5% level ***Statistically significant at the 1% level
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2015 한국경영정보학회 추계통합학술대회
cumulative number of patents in biotechnology 0 50 100 150
Fixed broadband penetrations and cumulative number of patents in biotechnology between 1999 and 2013 scatterplot by countries between 1999-2013 Denmark United States
Israel Switzerland Sweden Canada Belgium Australia New Zealand Austria
Iceland
Netherlands
Finland United Kingdom Japan Germany France Norway
Ireland Italy Slovenia Hungary SpainEstonia Slovak Czech Republic Republic Greece Portugal Chile Poland Mexico Turkey
5
Korea, Rep.
10 15 20 cumulative number of fixed broadband penetration
25
Government financed R&D and cumulative number of patents in biotechnology between 1999 and 2013 cumulative number of patents in biotechnology 0 50 100 150
scatterplot by countries between 1999-2013 Denmark United States
Israel Switzerland Sweden Canada Belgium Finland Japan
Iceland Netherlands United Kingdom Germany Australia Austria France
New Zealand Norway
Ireland Korea, Rep.
10
20
Slovenia Chile
30 40 government finance
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Italy Estonia Spain Czech Hungary Republic Slovak Republic Greece Portugal MexicoPoland Turkey
50
60
2015 한국경영정보학회 추계통합학술대회
Discussion The results of the data analysis indicate that fixed
broadband diffusion is one of the main drivers of biotechnology innovation. The effect of fixed broadband diffusion on
biotechnology innovation lasted at least three years, controlling for other factors. This finding implies that broadband infrastructure
has a long-term impact on biotechnology innovation in many countries. 11
Discussion This study also found that R&D expenditure has an
impact on biotechnology innovation. R&D for biotechnology also plays a leading role in
building the knowledge-based innovation system in the biotechnology field. This result also suggests that the creation and
management of marketable knowledge capital by R&D investment is necessary for stimulating biotechnology innovation. 12
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2015 한국경영정보학회 추계통합학술대회
Discussion The study found that there is an inverse U-shaped
relationship between R&D government financed and biotechnology innovation.
It appears that diversity of R&D financed ((e.g.) R&D
financed industry and R&D financed by university) is necessary for biotechnology innovation.
13
Discussion The results of the data analysis also indicate that
education is a statistically significant factor in explaining biotechnology innovation.
This finding implies that maintaining higher
education and research is critical to biotechnology innovation in many countries.
14
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2015 한국경영정보학회 추계통합학술대회
Limitations & Future Studies Because of data availability, additional
independent variables could not be included in the fixed-effects regression model. Further studies may include more diverse
independent variables in the empirical model, such as regulatory policy factors in the biotechnology and health sectors. Future research may also address whether
intellectual property rights protection in a country affects biotechnology innovation. 15
Questions
16
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The Determinants of National Biotechnology Innovation Capacity
이상원 (경희대학교 언론정보학과)
(경희대 언론정보학과) 이상원 (경희대 언론정보학과) 김도한 (경희대학교 행정학과)
1
Significance of the Study Innovation in biotechnology has become a key component
of the knowledge economy and national competitiveness. Well-established information and communications
technology (ICT) infrastructure such as broadband and R&D expenditure are necessary to promote national-level innovation in biotechnology. Employing panel data from 33 OECD countries, this study
investigates drivers of national biotechnology innovation capacity (Macro-level approach)
Drivers of technological innovation in Biotech Industry !!!
-533-
2
2015 한국경영정보학회 추계통합학술대회
Purpose of the Study This study examines The effects of macro-level drivers of technological innovation in biotech industry: Broadband Diffusion R& D expenditure R&D expenditure by government Education Income
3
The Status of Biotechnology Innovation, Broadband Infrastructure, R&D expenditure 2.5
80
70 2 60
50
1.5
40 1
30
20 0.5 10
0
0 1999
2000
2001 2002 2003 2004 cumulative biotechnology
2005 2006 2007 2008 2009 cumulative fixed broadband
2010 2011 2012 R&D expenditures
2013
The biotechnology patent statistics show that while there has been a steady growth in worldwide biotechnology innovation capacity, a wide range of biotechnology innovation levels exists across countries.
-534-
4
2015 한국경영정보학회 추계통합학술대회
The Empirical Model A country fixed effect model for the estimation This study employs a fixed effect model, which controls for the unobserved heterogeneity among countries. LnBit = β0it + β1it*lnFixedBroadband + β2it*RD + β3it*RD_GOV + β4it*(RD_GOV)2 + β5it*EDU + β6it*INC + δiZi + εit
LnBit: Biotech Innovation in country i in time t
β0it : Constant Zit : Country-dummies εit : Error Term 5
The Model, Method, and Data Variables Biotechnology innovation Fixed broadband
Measurement Cumulative patents grants in biotechnology per 1,000,000
Data sources OECD
inhabitants between 1999-2013 Fixed-broadband subscribers per 100 inhabitants
ITU
penetration R&D expenditure
Research and development expenditure (percent of GDP)
World Bank
R&D financed by
R&D financed by government (percentage of total R&D financed)
World Bank
Education
School enrollment, secondary (percent of GDP)
World Bank
Income
GDP per capita
World Bank
government
Data Sources: Yearly Data (1999-2013) from OECD, World Bank, ITU, Data for 33 countries 6
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2015 한국경영정보학회 추계통합학술대회
Empirical Results: Fixed effect OLS model (1)
(2)
(3)
(4)
0.190*** (0.051)
0.040** (0.017) 0.160*** (0.051)
0.006*** (0.002) 0.000*** (0.000) -0.958*** (0.322)
0.005*** (0.002) 0.000 (0.000) -0.710** (0.301)
0.005*** (0.002) 0.000** (0.000) -0.944*** (0.318)
0.030* (0.017) 0.118** (0.052) 0.046*** (0.013) -0.001*** (0.000) 0.006*** (0.002) 0.000*** (0.000) -1.853*** (0.424)
473 0.931 33
492 0.933 33
473 0.933 33
473 0.937 33
VARIABLES Fixed broadband penetration
0.034** (0.017)
R&D expenditure R&D government financed (R&D government financed)2 Education Income Constant
Observations R-squared Number of country
* Statistically significant at the 10% level ** Statistically significant at the 5% level ***Statistically significant at the 1% level
Empirical Results: Fixed effect OLS model (Broadband lagged variable) (1) VARIABLES Fixed broadband penetration (lagged variable) R&D expenditure R&D government financed (R&D government financed)2 Education Income Constant Observations R-squared Number of country
(2)
(3)
Two-year lagged
Three-year lagged
0.029*
0.026*
0.039***
(0.015) 0.105** (0.048) 0.033** (0.013) -0.000*** (0.000) 0.005*** (0.002) 0.000*** 0.029* 0.845** (0.421) 441 0.931 33
(0.014) 0.100** (0.045) 0.020 (0.012) -0.000** (0.000) 0.005*** (0.001) 0.000*** (0.000) -0.274 (0.383) 408 0.925 33
(0.014) 0.114** (0.045) 0.012 (0.013) -0.000 (0.000) 0.004*** (0.002) 0.000*** (0.000) 1.427*** (0.432) 375 0.914 33
One-year lagged
* Statistically significant at the 10% level ** Statistically significant at the 5% level ***Statistically significant at the 1% level
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2015 한국경영정보학회 추계통합학술대회
cumulative number of patents in biotechnology 0 50 100 150
Fixed broadband penetrations and cumulative number of patents in biotechnology between 1999 and 2013 scatterplot by countries between 1999-2013 Denmark United States
Israel Switzerland Sweden Canada Belgium Australia New Zealand Austria
Iceland
Netherlands
Finland United Kingdom Japan Germany France Norway
Ireland Italy Slovenia Hungary SpainEstonia Slovak Czech Republic Republic Greece Portugal Chile Poland Mexico Turkey
5
Korea, Rep.
10 15 20 cumulative number of fixed broadband penetration
25
Government financed R&D and cumulative number of patents in biotechnology between 1999 and 2013 cumulative number of patents in biotechnology 0 50 100 150
scatterplot by countries between 1999-2013 Denmark United States
Israel Switzerland Sweden Canada Belgium Finland Japan
Iceland Netherlands United Kingdom Germany Australia Austria France
New Zealand Norway
Ireland Korea, Rep.
10
20
Slovenia Chile
30 40 government finance
-537-
Italy Estonia Spain Czech Hungary Republic Slovak Republic Greece Portugal MexicoPoland Turkey
50
60
2015 한국경영정보학회 추계통합학술대회
Discussion The results of the data analysis indicate that fixed
broadband diffusion is one of the main drivers of biotechnology innovation. The effect of fixed broadband diffusion on
biotechnology innovation lasted at least three years, controlling for other factors. This finding implies that broadband infrastructure
has a long-term impact on biotechnology innovation in many countries. 11
Discussion This study also found that R&D expenditure has an
impact on biotechnology innovation. R&D for biotechnology also plays a leading role in
building the knowledge-based innovation system in the biotechnology field. This result also suggests that the creation and
management of marketable knowledge capital by R&D investment is necessary for stimulating biotechnology innovation. 12
-538-
2015 한국경영정보학회 추계통합학술대회
Discussion The study found that there is an inverse U-shaped
relationship between R&D government financed and biotechnology innovation.
It appears that diversity of R&D financed ((e.g.) R&D
financed industry and R&D financed by university) is necessary for biotechnology innovation.
13
Discussion The results of the data analysis also indicate that
education is a statistically significant factor in explaining biotechnology innovation.
This finding implies that maintaining higher
education and research is critical to biotechnology innovation in many countries.
14
-539-
2015 한국경영정보학회 추계통합학술대회
Limitations & Future Studies Because of data availability, additional
independent variables could not be included in the fixed-effects regression model. Further studies may include more diverse
independent variables in the empirical model, such as regulatory policy factors in the biotechnology and health sectors. Future research may also address whether
intellectual property rights protection in a country affects biotechnology innovation. 15
Questions
16
-540-
