• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.7
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• pp.106-111
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• 2020

In the era of the fourth industrial revolution, the application of big data analysis technology is crucial in various industries. In this regard, considerable research is necessary to improve aquafarming productivity, particularly in fish culture, which is one of the primary industries in the world. In this study, a sample experiment using a flop was conducted to improve oyster productivity in fish farms, and a flush was installed in an environment similar to aquaculture farms. Thereafter, the temperature data of the water environment where the formation of burrows considerably improved were collected; the growth rate of burrow seeds was also measured. The gathered experimental data were examined by time series data analysis. Finally, a system that visualizes the analysis results based on big data is proposed. In accord with the results of this study, it is expected that more advanced research on the productivity improvement of oyster aquafarming will be performed.

• Journal of Labour Economics
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• v.32 no.2
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• pp.95-124
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• 2009

In this article, I were trying to analyze the listed manufacturing companies' trend of productivity and the corporate education & training effect after the financial crisis. According to the analysis, the listed manufacturing companies have decreased their productivity since financial crisis, and from such declining trend. jobless growth and a growth without physical and human capital investment has been observed. Furthermore, there is no efficient labor force coordination within the manufacturing industry; In order to analyze the effect of education & training investment on productivity more deeply, I have practiced the dynamic panel data analysis from constructing the micro panel data which consists of company level information 1997~2008. According to the consequences, dynamic panel data analysis solved the problem of the overestimating education & training effect fairly well.

• BMB Reports
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• v.29 no.3
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• pp.221-224
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• 1996

To examine the growth-phase dependent control of Escherichia coli rnpB gene we used a combination of Northern analysis for RNA determination and Southern analysis for plasmid DNA determination. The relative amounts of metabolically unstable transcript derived from the internally deleted rnpB gene harbored on a multicopy plasmid as well as the relative plasmid contents were measured by Northern analysis and Southern analysis, respectively, of total nucleic acids from E coli cells containing the plasmid. The relative transcription activity of the rnB was represented by a ratio of the relative amount of the transcript to that of the plasmid DNA during bacterial growth. The rnpB transcription increased rapidly with time during exponential growth, but started to decrease before the transition period of an exponential growing cell culture into the stationary phase. Although the expression pattern was similar to the changes of ${\beta}-galactosidase$ activity expressed from the lysogenic strain carrying the chromosomal rnpB-lacZ fusion which were shown in a previous work, the present data appears to represent a more actual growth-phase control of the rnpB transcription than the previous data by the ${\beta}-galactosidase$ assay. In addition the present method described for a direct analysis of both RNA and plasmid DNA provides a rapid and efficient method that can applied to an examination of transcription control by using a multicopy plasmid.

• Journal of Technology Innovation
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• v.5 no.1
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• pp.15-43
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• 1997

This paper investigates empirically the relationship between various business portfolio properties (particularly technological properties) and chaebol's performance using data on the 50largest chaebols in Korea. In addition to the traditional indexes to measure diversification such as entropy index, we calculated inter-industry technological similarity using R'||'&'||'D expenditure data by industry and 1990 Input-output Table in korea, and obtained chaebol-level technological relatedness and internal transaction proportion from chaebols' business profile, inter-inustry technological similarity and 1990 input-output table. We applied factor analysis on 13 business portfolio property indexes and showed that they could be grouped into 3 dimensions. diversification scope, inter-business relatedness and degree of vertical integration. In this paper, using 50 largest chaebols' financial data (1989-1994), we analyzed empirically the effect of business portfolio properties on ROS(Return On Sales) which is conventional index for firm performance and on TFP(Total Factor Productivity) growth which is a pure measure of firm performance. To utilize the advantage of panel data, FEM(Fixed Effect Model) and REM(Random Effect Model) were used. The empirical result shows that the entropy index as a measurement of inter-business relatedness in not significant but technological relatedness index is significant. OLS estimates on pooled data were considerably different from FEM or REM estimates on panel data. By introducing interaction effect among the three variables for business portfolio properties, we obtained three findings. First, only VI(Vertical integration) has a significant positive correlation with ROS. Second, when using TFP growth as an dependent variable, both TR(Technological Relatedness) and VI are significant and positively related to the dependent variable. Third, the interaction term between TR and VI is significant and negatively affects TFP growth, meaning that TR and VI are substitutes. These results suggest strategic directions on restructuring business portfolio. As VI is increased, chaebols will get more profit. A higher level of either TR or VI will increase TFP growth rate, but increase in both TR and VI will have a negative effect on TFP growth. To summarize, certain business portfolio properties such as VI and TR can be considered "resources" themselves since they can affect profit rate and productivity growth. VI and TR have a synergy effect of change in profit rate and productivity growth. VI increases ROS and productivity growth, while TR increases productivity growth representing a technological synergy effect.t.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.1
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• pp.84-88
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• 1998

The aim of this study was to describe growth patterns of mice using Gompertz model. Two distinct types of mice, laboratory mouse $CF_{\sharp1}$ (Mus musculus domesticus) and Yonakuni wild mouse (Yk, Mus musculus molossinus yonakuni) were used. From all possible crosses, there were two parental types and two reciprocal $F_1$ crosses obtained. Individual body weights were measured weekly from birth to ten weeks of age on 321 mice. Standardization to six mice was conducted and only first litters were used. Growth curve parameters were estimated to fit growth data. The results showed that growth among genetic groups were significantly different (p < 0.05) for both sexes, in which parental type of $CF_{\sharp1}$ and Yk had the highest and the smallest values, respectively. Meanwhile, reciprocal $F_1$ crosses were intermediate between parental types. It was concluded that Gompertz model provided and excellent fit for the growth data with a high coefficient determination $(R^2 = 0.999)$.

• Journal of the Korean Regional Science Association
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• v.38 no.1
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• pp.3-20
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• 2022

The purpose of this study is to exploratory analyze the transition pattern of establishments and workers in new growth industries in the metropolitan area from 2010 to 2019 and to identify regional factors affecting the inflow and outflow of new growth industry start-ups. As for the analysis, the original data of the Census on Establishments were used, and spatial data at the sigungu level were constructed based on the inflow and outflow data of the number of new growth industry businesses and workers. For the analysis, the degree centrality of connection to outflow inflow by region was calculated, and an empirical analysis was conducted on regional-level factors affecting the inflow and outflow of new growth industries by applying a negative binomial regression model. According to the results, the new growth industry manufacturing sector was actively relocated in southern Gyeonggi Province, and the new growth industry service sector in Gangnam and Guro-Geumcheon-gu, and the impact of regional-level factors on the inflow and outflow of new growth industry start-ups varies depending on the industry. This study presented implications for regional industrial policies to improve the competitiveness of the local economy by attracting new industries by identifying spatial transition patterns for new growth industries and conducting empirical analysis to identify influencing factors.

• Journal of Distribution Science
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• v.21 no.2
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• pp.1-6
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• 2023

Purpose: Research on attracting foreign direct investment plays an important role in ASEAN countries. ASEAN has needed FDI capital for development and integration with many developing countries. Research design, data and methodology: This study is conducted to assess the impact of factors: inflation (INF), economic growth (GDP), population (POP), and trade (TRADE) on attracting foreign direct investment (FDI) of ASEAN countries. The study will find out how factors distribution contributes to FDI attraction. The study collects data from 10 ASEAN countries from 2010 to 2020. With data collected for ten countries from 2010 to 2020, data analysis with panel data will be used in this study. The Regression with Driscoll-Kraay standard errors correction model will be used in the study. Results: Panel data analysis shows that economic growth and population positively impact FDI attraction in ASEAN countries. However, two factors: INF and TRADE, do not affect FDI. Conclusions: Countries need to focus on economic development, create many good conditions for people and domestic enterprises and create opportunities for foreign investors to pay more attention. improving the quality of domestic human resources will help to better improve the working quality factor when the demand for high-quality human resources increases.

• Journal of the Korean Regional Science Association
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• v.10 no.1
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• pp.39-52
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• 1994

This paper primarily aims to analyze the growth rate differentials of the economic activities in chung-Nam area. The research has been undertaken to find out the potentials of the economic activities and economic bases in the area. To analyze the economic potentials of the industries, the study employed the economic Growth Rate Differential Analysis by Henderson which is revised form of Shift-Share Analysis Methods. The research employed the employment data according to the standardized two-digit-classification-system during the period of 10 years from 1981 through 1991. The Growth Rate Differential Analysis calculates Total Growth Differentials which are dicomposed into two parts: Weight Part and Rate Part. Total Growth Differential can be calculated as the difference between national growth rate and regional growth rate by industry. The foundings are as follows: First, the economic bases of Chung-Nam area were found to be very weak, largely depending on primary industries such as agriculture and fisheries. Second, there was a great decline in urban industries in Tae Joeon, Cheon An and other cities over period of 1971-1981. It is strongly recommended that the planned items and products of each industrial complex must be reorgnized in a fashion to match those with high competitive power found in this research.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.349-371
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• 2022

Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

• Korean Journal of Organic Agriculture
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• v.19 no.spc
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• pp.87-91
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• 2011

Eco-efficiency which is calculated by dividing economic productivity by the environmental load was made by synthesizing eco and efficiency from ecology and economy, proposed by World Business Council for Sustainable Development in 2000. Eco-efficiency by connection of resource efficiency with resource intensity is used as an indicator for evaluating green growth for minimizing the impact on the environment and achieving economic development as well by means of efficient use of resources. This research analyzes eco-efficiency with the case of organic agriculture promoted as a key green growth policy. Thirty questionnaires for farmers producing organic rice in Hongseong-gun, Choongcheongnam-do were used for the analysis. Eco-efficiency was measured by means of the amount of used nitrogen with respect to the amount of income, and was represented that organic agriculture was 32.0 higher than conventional agriculture. The analytical result of technical efficiency, using the (Data Envelopment Analysis (DEA) model showed that it is 0.765 which has a possibility of 21% in management improvement, and higher eco-efficiency was with higher technical efficiency. The analytical results showed that an organic agriculture contributes to green growth more than conventional agriculture. In addition, higher technical efficiency groups exhibited higher eco-efficiency indices.