• Journal of the Korean Applied Science and Technology
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• v.38 no.4
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• pp.941-950
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• 2021

This study was conducted to identify the factors affecting the health-promoting lifestyle of the school-age obese children. Method: Data Collection for this study was conducted form July 20 to August 2, 2019 using a structured questionnaire. We analyzed the collected data by frequency, percentage, ANOVA, t-test, Pearson's Correlation Coefficient, and Multiple Regression Analysis. Results: The factors affecting the health-promoting lifestyle of the subjects, multiple regression analysis results showed that Dietary Self-Efficacy(𝛽=.406, p=.001), Physical Activity Self-Efficacy(𝛽=.245, p=.038), Furthermore, the F statistics for the fitness of the estimated regression model were 6.34(p<.001), which was significant. The explanatory power was 24.2%. Conclusion: The results of this study showed that Dietary Self-Efficacy and Physical Activity Self-Efficacy of the school-age obese children was the most influential factor on health-promoting lifestyle. Consequently, the results of this study suggest that it is necessary to find ways to improve Dietary Self-Efficacy and Physical Activity Self-Efficacy in order to improve health-promoting lifestyle of nurses, and it is considered to be useful as basic data for developing intervention programs to improve health-promoting lifestyle.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.183-193
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• 2020

This study attempts to interpret the causes of offshoring and reshoring, find out facilitating factors and the areas where these happen mainly. In viewpoint of self-organization phenomena, the theory of prospect, quantitative analysis is performed by utilizing actual data of American Reshoring Association. This study shows that offshoring to the U.S. is positively correlated with market power in the U.S. and innovation of investment countries, while reshoring to U.S. is positively correlated with market power in the U.S. not with technology innovation. The reshoring of U.S. companies is influencing offshoring to U.S, emerging countries such as Asia tends to focus offshoring in short catch up cycle area like IT. This study is expected to contribute to investment support policy and decision for optimal production site. Further study will complete the economic benefit assessment model by reinforcing the impact factors of reshoring and offshoring.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.655-660
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• 2022

This paper analyzes the problem of the economic order quantity (lot size) of a retailer in a two-stage supply chain consisting of a supplier, a retailer(distributor), and a customer. In this two-stage supply chain, the supplier permits the retailer to defer payment for a certain fixed period of time for the purchase cost to be paid by the retailer as a price differentiation strategy with his competitor. In addition, in the case of customer goods such as food and grain, it is common to see that end-customer demand is generally depend on the level of inventory displayed by the retailer. From this perspective, this paper analyzes the inventory problem of retailers under the assumption that the supplier may allow a certain period to suspend payments for the purchase of goods and the end customer demand is a function of the retailer's inventory level increasing with size. In this regard, we need to analyze how much the length of the grace period for product purchase costs affect the retailer's lot-sizing policy. Therefore, we formulate the retailer's annual net profit and analyze the effect of the length of credit period on the retailer's inventory policy numerically.

• Journal of the Korean Applied Science and Technology
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• v.39 no.6
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• pp.727-737
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• 2022

This study was conducted to identify the factors Influencing the burnout of general hospital nurses. Method: The study subjects were 150 nurses in three general hospital. The collected data were analyzed by t-test, ANOVA, Scheffe's test, Pearson's correlation coefficient, and Multiple regression analysis. Results: The factors affecting the burnout of the subjects, multiple regression analysis results showed that emotional intelligence(β=-.441, p<.001), emotional labor(β=.403, p<.001), current position was more than responsible nurse(β=-.111, p<.018), and health status was healthy(β=-.100, p<.029). In addition, the F statistics for the fitness of the estimated regression model were 35.51(p<.001), which was very significant. The explanatory power was 79.7%. Conclusion: The results of this study showed that emotional intelligence of the general hospital nurse was the most influential factor on burnout, and the higher the position, the better the health status, the lower the emotional labor, the lower the burnout. Therefore, the results of this study suggest that it is necessary to find ways to reduce emotional labor and improve health and emotional intelligence in order to reduce burnout of nurses, and it is considered to be useful as basic data for developing intervention programs to lower burnout.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.127-139
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• 2023

Compensation and pay dispersion has been rigorously scrutinized to investigate their impacts on productivity and organizational performance. However, it is difficult to find a systematic study on the systematic dynamics of compensation and pay dispersion effects specifically in the context of Korean venture companies. Venture companies should manage their organizational resources efficiently to maximize their organizational performance through pay structure by efficiently managing the inherent resources. However, we acknowledge that empirical studies on how compensation and pay dispersion affect organizational productivity and performance are rare to find in the Korean context. To overcome this supplement limitation, this study hypothesized that (1) pay and members' productivity are positively related, (2) pay dispersion and organizational productivity have U shaped relationship, and (3) organizational productivity mediates the positive relationship between compensation and organizational performance. Venture companies and professional sports teams share manifold common characteristics such as size, financial circumstances, and operational objectives. We collect 9 seasons (2013~2014 - 2021~2022) of 10 teams' data of Korean Basketball League teams to test our hypotheses. Methodologically, the assessment of our analysis is rendered with PROCESS macro model 58. The statistical results showed that all hypotheses are statistically supported. This study explains how compensation and pay dispersion affect organizational productivity and performance of venture companies in Korea.

• Information Systems Review
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• v.21 no.1
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• pp.91-111
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• 2019

Around the end of 2017, the investment fever for cryptocurrencies-especially Bitcoin-has started all over the world. Especially, South Korea has been at the center of this phenomenon. Sinceit was difficult to find the profitable investment opportunities, people have started to see the cryptocurrency markets as an alternative investment objects. However, the cryptocurrency fever inSouth Korea is mostly based on psychological phenomenon due to expectation of short-term profits and social atmosphere rather than intrinsic value of the assets. Therefore, this study aimed to analyze influence of people's social sentiment on price movement of cryptocurrency. The data was collected for 181 days from Nov 1st, 2017 to Apr 30th, 2018, especially focusing on Bitcoin-related post in Twitter along with price of Bitcoin in Bithumb/UPbit. After the collected data was refined into neutral, positive and negative words through sentiment analysis, the refined neutral, positive, and negative words were put into regression model in order to find out the impacts of social sentiments on Bitcoin price. After examining the relationship by the regression analyses and Granger Causality tests, we found that the positive sentiments had a positive relationship with Bitcoin price, while the negative words had a negative relation with it. Also, the causality test results show that there exist two-way causalities between social sentiment and Bitcoin price movement. Therefore, we were able to conclude that the Bitcoin investors'behaviors are affected by the changes of social sentiments.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.360-373
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• 2017

The BTO-a projects is the types, which has a demand risk among the type of PPP projects in Korea. When demand risk is realized, private investor encounters financial difficulties due to lower revenue than its expectation and the government may also have a problem in stable infrastructure operation. In this regards, the government has applied various risk sharing policies in response to demand risk. However, the amount of government's risk sharing is the government's contingent liabilities as a result of demand uncertainty, and it fails to be quantified by the conventional NPV method of expressing in the text of the concession agreement. The purpose of this study is to estimate the value of investment risk sharing by the government considering the demand risk in the profit sharing system (BTO-a) introduced in 2015 as one of the demand risk sharing policy. The investment risk sharing will take the form of options in finance. Private investors have the right to claim subsidies from the government when their revenue declines, while the government has the obligation to pay subsidies under certain conditions. In this study, we have established a methodology for estimating the value of investment risk sharing by using the Black - Scholes option pricing model and examined the appropriateness of the results through case studies. As a result of the analysis, the value of investment risk sharing is estimated to be 12 billion won, which is about 4% of the investment cost of the private investment. In other words, it can be seen that the government will invest 12 billion won in financial support by sharing the investment risk. The option value when assuming the traffic volume risk as a random variable from the case studies is derived as an average of 12.2 billion won and a standard deviation of 3.67 billion won. As a result of the cumulative distribution, the option value of the 90% probability interval will be determined within the range of 6.9 to 18.8 billion won. The method proposed in this study is expected to help government and private investors understand the better risk analysis and economic value of better for investment risk sharing under the uncertainty of future demand.

• Journal of Korea Port Economic Association
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• v.36 no.4
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• pp.17-30
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• 2020

In the shipping industry, it is essential to engage in the preemptive prediction of freight rate volatility through market monitoring. Considering that freight rates have already started to fall, the loss of shipping companies will soon be uncontrollable. Therefore, in this study, factors affecting the freight rates of bulk carriers, which have relatively large freight rate volatility as compared to container freight rates, were quantified and analyzed. In doing so, we intended to contribute to future shipping market monitoring. We performed an analysis using a vector error correction model and estimated the influence of six independent variables on the charter rates of bulk carriers by Handy Size, Supramax, Panamax, and Cape Size. The six independent variables included the bulk carrier fleet volume, iron ore traffic volume, ribo interest rate, bunker oil price, and Euro-Dollar exchange rate. The dependent variables were handy size (32,000 DWT) spot charter rates, Supramax 6 T/C average charter rates, Pana Max (75,000 DWT) spot charter, and Cape Size (170,000 DWT) spot charter. The study examined charter rates by size of bulk carriers, which was different from studies on existing specific types of ships or fares in oil tankers and chemical carriers other than bulk carriers. Findings revealed that influencing factors differed for each ship size. The Libo interest rate had a significant effect on all four ship types, and the iron ore traffic volume had a significant effect on three ship types. The Ribo rate showed a negative (-) relationship with Handy Size, Supramax, Panamax, and Cape Size. Iron ore traffic influenced three types of linearity, except for Panamax. The size of shipping companies differed depending on their characteristics. These findings are expected to contribute to the establishment of a management strategy for shipping companies by analyzing the factors influencing changes in the freight rates of charterers, which have a profound effect on the management performance of shipping companies.

• Journal of Korean Port Research
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• v.6 no.2
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• pp.65-92
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• 1992

The Korean central government has not appreciate the full extent of the impact of seaports on the national economy. As a consequence port investment has not been given sufficient priority and capacity has failed to keep pace with demand. The principal reason for this failure is the fact that the linkages (or relationships) of the port transport industry with other sectors have not been quantified and fully appreciated. To overcome this dificiency this paper developed a port input-output model to determine the economic impact of the port industry on the national economy. This impact study was conducted by analysing the impact of the Korean port industry upon the national economy from the macroeconomic viewpoint, and identifying the spreading effects of port investments upon the nation's economy. The analysis of the economic impact of the port industry suggests that its contribution to the Korean economy is substantial. What the model shows is, in quantifiable terms, there are the strong economic linkages between the port industry and the other sectors of the national economy. The contribution of the port industry to the Korean economy was summarised in the Conclusion section.