• Korean System Dynamics Review
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• v.17 no.2
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• pp.33-56
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• 2016

In this paper, a system dynamics model for explaining the application, grant and maintenance of patents is provided. Existing literatures regarding the patent application system are mostly econometric approaches that consider only economic variables such as GDP and R&D. The model in this paper includes patent variables such as disputes as well as economic variables. Moreover, we show that the model can be used in not only a quantitative prediction but also policy experiment. The results of the policy experiment shows that strengthening protection of patents tend to increase the propensity to patent more than R&D investment.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2001.05a
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• pp.473-492
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• 2001

This paper presents an econometric model for measuring basic research capacity index(BRCI) of each OECD countries and analyses the gap in terms of time lag measured and forecasted in connection with factor analysis and BRCI progress function. Based on the analysis, gross domestic expenditure on R&D(GERD), total R&D personnel, higher education expenditure on R&D(HERD) and number of science and technical papers based on SCI are more effective than other factors to BRCI. Also, BRCI progress function shows that 29 years is needed for Korea to catch up the level of German's BRCI of year 1998. But, it's impossible for Korea to catch up US and Japan. Therefore, with restricted scientific resources, Korea's own strategy for strengthening basic research capacity is going to be more important in 21st century.

• KDI Journal of Economic Policy
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• v.37 no.1
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• pp.44-72
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• 2015

This study evaluates the economic impact of product innovation by using firm-level data from the Community Innovation Survey conducted in Japan. It accounts for possible technological spillover from innovation activities and examines the extent to which new-to-market product innovations contribute to firm performance. Econometric analysis using a simultaneous equation model reveals that new-to-market product innovation is likely to increase a firm's sales without cannibalizing those of existing products and generate more technological spillover to other firms. Moreover, such innovation is more likely to emerge from firms collaborating with academic institutions. The paper concludes by discussing policy implications of these findings as well as points to the importance of cross-country comparison between Korea and Japan.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.307-314
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• 2022

The construction and real estate industries contribute significantly to each country's economic development. Strong construction and real estate firms will contribute more to the country's GDP by contributing to the industry's development. The purpose of this study is to examine the factors that influence the performance of the construction and real estate sectors in Vietnam. A survey of 200 construction and real estate firms in different areas was conducted from 2020 until the end of 2021. Following the removal of errors, the author got 196 replies, 6 of which were invalid, leaving 190 votes for quantitative analysis. The research findings show that elements such as (1) senior executives' commitment to the organization, and (2) the ability to use technology have a positive and significant impact on firm performance when using advanced econometric analysis. Furthermore, in the case of Hanoi, Vietnam, business relationships have a positive impact on firm performance. Training and development, as well as the working environment and incentives, have little effect on the profitability of construction and real estate firms. Finally, the research also has some recommendations and limitations for the construction and real estate sector.

• Asia pacific journal of information systems
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• v.29 no.3
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• pp.414-427
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• 2019

The sharing economy has significantly changed the way of living for years. The emergence and expansion of sharing economy empowered by the mobile information technologies and intellectual algorithms reconfigure how people use transportation means. In this paper, the bike sharing phenomenon is highlighted. Combining a big data set provided by the Seoul government about user logs and air quality data set, the empirical findings reveal that temperature change is tightly associated bike sharing activities. Also, the concentration of particulate matter is weakly related to bike sharing, but the trend should be carefully examined. By considering external environmental factors to bike sharing businesses, this work is differentiated. To further understand empirical data, data mining methods and econometric approaches were adopted.

• Journal of the Korean Academic Society of Industrial Cluster
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• v.4 no.1
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• pp.14-50
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• 2010

This study focused on the competitiveness analysis of industrial cluster using econometric method and competency analysis method to measure the situation of Seocho-gu industrial cluster and Yangjae R&D cluster at Seoul. The econometric method used the data such as the number of firms, the number of employee, GRDP. The competency analysis method measured the level of agglomeration of cluster for years through LQ(Location quotient) index. In addition, the characteristics and structure of each industry in Secho-gu and Yangjae-dong R&D cluster. The circumstance of location and business, the competency of potential ability of industries were analysed by SWOT. In sum, this study has the following conclusion. First, Seocho-gu and Yangjae-dong region has an advantage in the circumstance for R&D related industry and man power. Second, Seocho-gu and Yangjae-dong region has a good potential for development in R&D related industries. These region has a good relationship the four major R&D related industry of Seoul. Third, these region also has a advantage in the potential development of R&D related researchers in the corresponding industries.

• Ocean and Polar Research
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• v.42 no.2
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• pp.157-169
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• 2020

This study aimed to analyze the effect of total allowable catches (TACs) on the target species. First to effects analyse of TACs, the 8 TAC target species and 75 non-target species were selected for which catch data were available before and after the introduction of the TACs. The 8 target species were simply compared to catch changes before and after TACs. Through the comparison, it was confirmed how the catches of target fishes have changed after the implementation of the TACs. Secondly, the Difference In Differences(DID) analysis was conducted to confirm the effects of the TACs on the catches of the target fishes using the catch data of 8 TAC target species and 75 non-TAC species. Finally, to overcome the limitations of the DID analysis, the random effects model was estimated to confirm the effects of the TACs on the catch of the TAC target species. Overall, this study confirmed that the TACs affects catches of target species, not only through simple comparisons of catches before and after the introduction of the TACs but also through econometric analysis.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.207-215
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• 2021

The number of tourists visiting Nepal has shown rapid growth in recent years, and Nepal is expecting more tourist arrivals in the future. This paper, thus, attempts to analyze the tourist arrivals in Nepal and predict the number of visitors until 2025. This paper has examined the international tourist arrival trend in Nepal using the Gompertz and Logistic growth model. The international tourist arrival data from 1991 to 2018 is used to investigate international tourist arrival trends. The result of the analysis found that the Gompertz model performs a better fit than the Logistic model. The study further forecast the expected tourist arrival below one million (844,319) by 2025. Nevertheless, the government of Nepal has the goal of two million tourists in a year. The present study also discusses system dynamics scenarios for the two million potential visitors within a year. Scenario analysis shows that proper advertisement and positive word-of-mouth will be key factors in achieving a higher number of tourists. The current study could fill the gap of theoretical and empirical forecasting of tourist arrivals in the Nepalese tourism industry. Also, the study findings would be beneficial for government officers, planners and investors, and policy-makers in the Nepalese tourism industry.

• Journal of Distribution Science
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• v.21 no.7
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• pp.41-50
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• 2023

Purpose: The purpose of the research is identified factors influencing the competitiveness of the copper industry in Kazakhstan. Research design, data and methodology: A few studies are dedicated to the analysis in developing countries, particularly Kazakhstan. The algorithm was chosen for research provision: statistical and comparative analysis, correlation, and regression analysis. The data of 1999-2021 obtained from the World Bank, Bureau of National Statistics, National Bank of Kazakhstan. Results: The obtained results demonstrate the trends in the development of the industry since 2000. The development of the copper industry is strongly influenced by the distribution and state of the business environment, economic situation, and trends in the global commodity markets. Conclusions: According to econometric modeling, there is a correlation between the profitability of the copper industry, GDP, copper prices, liquidity, and energy resource prices. Trends in global commodity and energy markets have a significant impact on the state of the industry. Further research should be conducted to include an analysis and forecast of internal factors that may affect the development of the industry, such as copper reserves, condition of fixed assets, government programs, etc. It is also important to examine the correlation with the trends in the development of the global green economy and the revival of the Chinese market.

• International Journal of Human Ecology
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• v.4 no.2
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• pp.77-87
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• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.