1. Forecasting a Country-Dependent Technology Growth
2016 AEA
Forecasting a Country-Dependent Technology Growth
by using a Dynamic Technology Level Evaluation Model
Korea Institute S & T Evaluation and Planning
Jiyeon Ryu, Sooncheon Byeon
Ⅰ. Research Question

2. Definition of Technology level evaluation
'accumulation degree of technical knowledge’(Schmookler, 1966)
'ability of efficiently utilizing technical knowledge for innovation, investment and production(Solow, 1957)
Technology level evaluation
- The world-leading technology takes 100% be calculated at the specific time. (relative evaluation)
- Survey to compute technology level and technological gap (time gap/year)
- Between Korea and other world leading countries
- Evaluated by technology experts

3. Objectives of this article
Problems & Limitations
The ambiguity of technological level value
World Top tech level (100%) vs. Korea tech level
Meaning of the technology time gap
technology time gap 1 years ??
To difficult to find out current state of technology
the state of Korea and World Top country on tech life cycle spectrum (Technology is always changing)
Impossible of analyzing Time-based
Difficult to get strategy for catch up
Objectives
Suggest theoretical concept and methodology for evaluation of technology level in dynamic
to get the relative state of Korea and competitor on the technology life cycle and velocity
the application of data, to verify the appropriateness of methodologies  and application possibility 

4. Ⅱ. Framework and Research Methodology

5. Theoretical background
Growth curve
first used in biology and it has known as Pearl curve or Logistics curve by US biologist and demographer R. Pearl(Pearl. R, 1925)
Biological organisms grow gradually at first but as time goes by, they grow drastically, and when they reach a status of saturation, the pace of growth slows down again
The shape that represents such pattern of growth looks like the letter S so, called s-curve
with an s-curve, it is possible to determine the current status of the technology and to predict how much time it will take for the technology to reach the upper limit based on its theoretical upper limit (Park Martino Giovanni, 1982)

6. Conceptual framework

7. Survey process Targets technology Data Scoring model (Gordon model)
90 Critical Technologies and 364 detail technologies in the 2nd S&T Basic Plan('08~'12)
Data
2008 technology level evaluation in KISTEP
Delphi survey : 1st round survey (2,816 person), 2nd round survey (1,943 person)
in-depth interview after Delphi (90 person)
※ Research on the S&T Trends, Analysis on the publications
2010 technology level evaluation in KISTEP
Delphi survey (2,130) : 1ST round survey(47%), 2nd round survey(59.3% of 1st round)
Scoring model (Gordon model)

8. Ⅲ. Data analysis and Result

9. Hypothesis 1 Research Hypothesis
A technology will develop based on its own growth curve.
Each technology will evolve according to the growth curve and the low-technology countries will evolve by following the patterns of the high-technology countries.
Thus, the technological growth curve will be useful to predict the path for future technology as it indicates the patterns of technology development.

10. Sample of curve fitting results
Technology level(%)
Time(year)

11. Survey value of Expert vs. Expectations value after 5 yrs
Analysis of the technology growth model in field of 15 ICTs -Comparison of results from the technology growth model and a survey of experts-
Technology level (5 years later)
Technology level after 5 years: the results of the technology growth model is approximately 10% higher than that of Delphi survey
Pearson correlation coefficient 0.889
Significance probability 0.000, significance level p=0.01
High correlation

12. Technology Life cycle
Technology Life Cycle
Velocity of technology development
Correlation of results of velocity of technology development between technology growth model and a survey of expert
Pearson correlation coefficient
- Model : the higher the technology level, the slower the velocity
- Survey : the higher the technology level, the faster the velocity
Correlation of results of technology life cycle between technology growth model and a survey of experts :
Pearson correlation coefficient
Significance probability 0.000, significance level p=0.01
High correlation

13. Technology development curve in country
The reason why there exists a difference between the results of the technology growth model and experts response :
Analyzed each country's technology growth curve in parallel with similar cases <3-dimensional display technology>.
Made again curve fitting by using past data
Technology growth curve of world-leading Japan and Korea are different :
Japan holds a dominant position in the velocity of technology development as well as current technology level
It is estimated that the technological gap with Japan will keep widening for the next 5 years.
All countries have differently shaped technology growth curves.
It need to modify the first assumption
Technology Development Curve
<3-dimensional display technology>

14. Ⅳ. Data analysis and Result

15. Technology growth curve – 2008& 2010 data

16. 2008 vs. 2010 technology growth curve
Three patterm of technology growth curve in 2008 & 2010
Concurrency of the 2008 and 2010 technology growth curve
Movement of technology growth curve (2010 curve moves to the right from2008)
2008 and 2010 curves cross each other

17. Tech level : 2010 estimation value in 2008 curve vs
Tech level : 2010 estimation value in 2008 curve vs value of survey result

18. Tech level : 2015 estimation value in 2010 curve vs
Tech level : 2015 estimation value in 2010 curve vs value of survey result

19. Hypothesis 2 New hypothesis
There exists a country-specific technology growth curve that reflects the characteristics of the country (system, infrastructure, human resources, investment, etc.)

20. Country specific technology growth curves

21. U. S. A 2015 estimation value in country specific curve vs
U.S.A 2015 estimation value in country specific curve vs value of survey result

22. KOREA 2015 estimation value in country specific curve vs
KOREA 2015 estimation value in country specific curve vs value of survey result

23. CHAINA 2015 estimation value in country specific curve vs
CHAINA 2015 estimation value in country specific curve vs value of survey result

24. Ⅵ. Conclusion and Discussion

25. Conclusion & Limitation
Conclusion and implication
It can and is possible to forecast the future technology level from country technology growth curve.
It can be forecast the velocity and amount of technology development of country to catch up.
It can be analyze possibility of technology catching up.
Limitation
First, we did not provide the upper limit of technology to the survey respondents. It is difficult to determine the theoretical upper limit for each technology
it still provides insufficient explanation about initial phase of technology development. this model can be applicable to the results with over 50% of technology level.
It can be overcome by securing time series data in the future, or producing country-specific technology growth curve for the countries with lower level of technology.

26. Limitation and Further study
It is difficult to make estimation on new growth curve and alternate curve in the case of countries with higher level of technology.
In the future, we can interpret the difference of growth curve models and the pace of development among countries by utilizing quantitative data such as investment, equipment, infrastructure and specifications of technology to structure the technology level, and conducting technology level evaluation for such criteria.
if we identify the correlations between the factors structuring technology level, we can develop the comprehensive index measuring the science and technology competitiveness
In 2012, technology level evaluation will be conducted. Furthermore, it is considered that we are able to suggest a tool for establishing more concrete technology .