• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.375-384
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• 2022

The shipping industry is cyclically impacted by complex variables such as various economic indicators, social events, and supply and demand. The purpose of this study was to analyze the operating profit of 13 Korean liner companies over 30 years, including the financial crisis of the late 1990s, the global financial crisis of the late 2000s, and the COVID-19 global pandemic. This study was conducted to also identify factors that impacted the profit ratio of Korea's liner shipping companies according to economic conditions. It was divided into ocean-going and short-sea shipping, reflecting the characteristics of liner shipping companies, and was analyzed by hierarchical multiple regression analysis. The time series data are based on the Korean International Financial Reporting Standards (K-IFRS) and comprise seaborne trade volume, fleet evolution, and macroeconomic indicators. The outliers representing the economic downturn due to social events were separately analyzed. As a result of the analysis, the China Container Freight Index (CCFI) positively impacted ocean-going as well as short-sea liner shipping companies. However, the Korean container shipping volume only impacted ocean-going liners positively. Additionally, world and Korea's GDP, world seaborne trade volume, and fuel price are factored in the operating profit of short sea liner shipping. Also, the GDP growth rate of China, exchange rate, and interest rate did not significantly impact both groups. Notably, the operating profitability of Korea's liner shipping shows an exceptionally high rate during the recessions of 1998 and 2020. It is paradoxical, and not correlated with the classical economic indicators. Unlike other studies, this paper focused on the operating profit before financial expenses, considering the complexity as well as difficulty in forecasting the shipping cycle, and rendered conclusions using relatively long-term empirical analysis, including three economic shocks.

• Journal of Service Research and Studies
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• v.12 no.1
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• pp.25-35
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• 2022

Covid-19, of which the first patient in Korea occurred in January 2020, has affected various fields. Of these, the tourism sector might havebeen hit the hardest. In particular, since tourism-based industrial structure forms the basis of the region, Gangwon-province, and the tourism industry is the main source of income for small businesses and small enterprises, the damage is great. To check the situation and extent of such damage, targeting the Chuncheon region, where public access is the most convenient among the Gangwon regions, one-day tours are possible using public transportation from Seoul and the metropolitan area, with a general image that low expense tourism is recognized as possible, this study conducted empirical analysis through data analysis. For this, the general status of the region was checked based on the visitor data of Chuncheon city provided by the tourist information system, and to check the levels ofinterest in 2019, before Covid-19, and in 2020, after Covid-19, by comparing keywords collected from the web service sometrend of Vibe Company Inc., a company specializing in keyword collection, with SK Telecom's T-map search site data, which in parallel provides in-vehicle navigation service and communication service, this study analyzed the general regional image of Chuncheon-city. In addition, by comparing data from two years by developing a tourism popularity index applying keywords and T-map search site data, this study examined how much the Covid-19 situation affected the level of interest of visitors to the Chuncheon area leading to actual visits using a data analysis approach. According to the results of big data analysis applying the tourism popularity index after designing the data mart, this study confirmed that the effect of the Covid-19 situation on tourism popularity in Chuncheon-city, Gangwon-provincewas not significant, and confirmed the image of tourist destinations based on the regional characteristics of the region. It is hoped that the results of this research and analysis can be used as useful reference data for tourism economic policy making.

• Journal of Korea Technology Innovation Society
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• v.10 no.2
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• pp.284-309
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• 2007

Technology transfer (TT) consortium is an affiliation of two or more public research institutions (PRIs) that participate in a common technology transfer activity or pool their resources together, with the objective of facilitating technology transfer. Based on empirical analysis of five regional TT consortia (2002-2006) operating in Korea, this paper suggests their effectiveness by employing a TT performance index (TTPI) and identifies possible characteristics involved, such as motivations, facilitators, barriers, and challenges. TTPI devised in the paper is a new composite TT performance index to measure how much the TT performance of a PH changed in a designated year compared to a base year. All the performance indicators of TTPI are well-structured based on the unique TT process that is prevalent in Korea. Further, TTPI can bring different size and focus of PRIs to the same scale for comparison by double-normalizing. The paper tests the effectiveness of TT consortium for the escalation of TT performances in member PRIs by highlighting the differences of TTPI's between 2005 and 2001. As a result, the paper found that the escalation of TTPI for member PRIs was greater than that for non-member PRIs. As for the characteristics of TT consortia, their respective factors obtained by TT expert survey were computed with proportion tests of differences (Z tests) to compare two perspectives between intramural and extramural groups. One of key findings is that there is general homogeneity in stakeholder perspectives regarding motivations, facilitators, barriers, and challenges. Some notable responses are as follow; the most probable motivation to join TT consortium is to share or exchange TT competences for enhanced performance. Second, the most probable facilitator is professional capability of consortium-hired personnel. Third, the foremost probable barriers to effective TT consortium are frequent change of consortium director and passive participation of member PRIs. Lastly, both publicizing TT consortia and developing performance metrics are the most important for the improvement of TT consortia. The understanding of the characteristics of TT consortia increases the likelihood of accelerated success, because TT consortia path from formation to termination encompasses many concepts, processes, principles, and factors. Finally, an analysis of the survey data combined with expert interview and observation data led the authors to derive five conditions as being critical to viable TT consortia in Korea at early stage of technology transfer systems. These conditions include policy infrastructure, proactive participation, excellent professionals, personal motivation, and teaming mechanisms. It is expected that the Korean evidence is a starting point to develop and refine the theory of TT consortia and for additional studies in other countries.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.5
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• pp.83-94
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• 2014

Before economical crisis in 1997, domestic company focused on increasing the size of outward experience which including organization. The result of increasing outward experience without substance was economical crisis, so after that time, many companies have been changing their focus from insourcing to strengthen the core competence to secure global market. This is becoming a cause of following that companies are reducing their outward experience. Especially, to process tasks more effectively and to cope with rapid change of business environment, such as incoming raw material from overseas/high raising of salary/rising property prices, many companies decided outsourcing method. At most of hypothesis, the result was that outsourcing can affect positively to the business. First, introducing of outsourcing during focusing on core competence can be positive effect for company performance such as business management /productivity /procurement /administration /product competitiveness /technology. Second, the result that analyzed based on a point of view of population statics after outsourcing was positive effect at the most of research. Third, result of effectiveness for every outsourcing type classified by 4M was also can be positive at the most of research. Fourth, the characteristic of population statics can be positive effect at the most of category when select outsourcing companies. Research result of outsourcing was various based on the goal of outsourcing. It is revealed by investigation of domestic/overseas treatise that there are opposite two opinions. In this research, there is no consistent result that the outsourcing can give effects on business performance, but most of hypothesis indicates that outsourcing can give positive effect on the business performance.In this research, based on the outsourcing intensity, mutual relation was analyzed. The assumption of the reason of outsourcing is economical and organizational. First, sampling numbers of research was too small so it is too difficult to get significant business performance result. (Sampling : 150, Replied : 106, Rate of Reply : 71%) Second, tried to compare significant differences of outsourcing methods which were divided based on 4M, but the there is gaps between the number of Cell and too difficult to make replier understand. Third, it is tried to find the degrees of effect that the point of view of popular statics can effect on business performances and selection of outsourced companies.

• Journal of dental hygiene science
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• v.11 no.6
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• pp.573-581
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• 2011

The purpose of this study was to examine the professionalism of dental hygienists in dental institutions and the influential factors for their professionalism in an attempt to seek ways of enhancing the professionalism of dental hygienists. The subjects in this study were 172 dental hygienists who worked in dental institutions in Busan and Gimhae. A self-administered survey was conducted to gather data, and an experimental analysis was carried out to analyze the collected data. The major findings of the study were as follows: First, concerning professionalism, self-regulation belief(3.70) ranked highest(3.42), followed by service belief(3.65), autonomy belief(3.31), a sense of vocational calling(3.30) and utilization of the professional organization as a standard(3.12). Second, the professionalism of the dental hygienists was significantly better when their title was higher, when they were older, when they got a larger monthly pay and when they intended to work for a longer time. Third, as for the influential factors for their professionalism, age, marital status, the estimated term of working at the workplace and opinion on reemployment were also identified as the significant variables that were up to the standard level of significance(p=0.05). The findings of the study suggest that in order to boost the professionalism of dental hygienists, it's required to take institutional measures to give them more responsibility, autonomy and authority, and how to improve personnel administration by providing strong motivation for them to look at their workplaces more favorably and keep on working for a long time should discreetly be considered.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.117-137
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• 2019

In young entrepreneurs, the individual situation of opportunity discovery is very important. It is very important that the opportunities that are created for a particular individual entrepreneur are also recognized and assessed through the process. The need for the development of entrepreneurial opportunity competencies, which have a low proportion of opportunistic entrepreneurship, is low in the entrepreneurship education. In particular, young entrepreneurs are in desperate need of opportunistic entrepreneurship. The purpose of this study is to examine the effect of entrepreneurship motivation on entrepreneurial opportunity competence, using entrepreneurial orientation and entrepreneurship orientation as mediation variables for preliminary young entrepreneurs (19-39 old). In the case of young entrepreneurs, there is a tendency to study entrepreneurship policies and education through the system of youth entrepreneurship schools, mainly on college students and youths, and on the effects of institutional support on entrepreneurship. There is little research on the effect of a entrepreneurial motivation on the entrepreneurial opportunity competence needed to promote an entrepreneurial venture in a model with multiple mediators. The purpose of this study is to investigate the effect of start - up motivation on the entrepreneurial opportunity competence. To do this we analyzed 374 questionnaires collected from preliminary young entrepreneurs in Seoul and Gyeonggi provinces. The results of the analysis using SPSS v22.0 and Process macro v3.0 showed that the motivation of start - up had a significant effect on both opportunity recognition and opportunity evaluation of entrepreneurial opportunity competence. Second, motivation of entrepreneurs has a significant effect on entrepreneurial efficacy. Third, entrepreneurial efficacy has a significant effect on entrepreneurial orientation. Fourth, entrepreneurial orientation has a significant effect on entrepreneurial opportunity competence. Fifth, there is a significant indirect effect between entrepreneurial motivation and entrepreneurial opportunity recognition when passing through entrepreneurial orientation, entrepreneurial efficacy and entrepreneurial orientation at the same time, But indirect effects was insignificant when only entrepreneurship efficacy is passed. There is a significant indirect effect on all mediators between entrepreneurial motivation and entrepreneurial opportunity valuation. It is suggested that strengthening education on entrepreneurship is necessary to cultivate awareness of entrepreneurship opportunities and strengthening education on both entrepreneurial efficacy and entrepreneurship is necessary to cultivate evaluation of entrepreneurship opportunities by type of entrepreneurial motivation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.139-149
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• 2019

The purpose of this study is to contribute to the minimization of the social cost due to the insolvency by improving the success rate of the startups by providing useful information to the founders and the start-up support institutions through analysis of non-financial information affecting the failure of the startups. This study is aimed at entrepreneurs. The entrepreneurs that are defined by the credit guarantee institutions generally refer to entrepreneurs within 5 years of establishment. The data used in the study are sampled from the companies that were supported by the start-up guarantee from January 2014 to December 2013 as the end of December 2017. The total number of sampled firms is 2,826, 2,267 companies (80.2%), and 559 non-performing companies (19.8%). The non-financial information of the entrepreneur was divided into the entrepreneur characteristics information, the entrepreneur characteristics information, the entrepreneur asset information and the entrepreneur 's credit information, and cross-tabulations and logistic regression analysis were conducted. As a result of cross-tabulations, univariate analysis showed that personal credit rating, presence in the industry, presence of residential housing, presence of employees, and presence of financial statements were selected as significant variables. As a result of the logistic regression analysis, three variables such as personal credit rating, occupation in the industry, and presence of residential house were found to be important factors affecting the failure of founding companies. This result shows the importance of entrepreneur 's personal credibility and experience and entrepreneur' s assets in business management. The start-up support institutions should reflect these results in the entrepreneur 's credit evaluation system, and the entrepreneurs need training on the importance of the personal credit and the management plan in the entrepreneurial education. The results of this analysis will contribute to the minimization of the incapacity of startups by providing useful non-financial information to founders and start-up support organizations.

• Korean Journal of Soil Science and Fertilizer
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• v.20 no.3
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• pp.199-204
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• 1987

This study was conducted to verify the identity and the effects on soil improvements by the application of Barley stone which has been recently named as miraculous mineral on account of being propagandized as health stone because of several special effect of medicine, the supplement of micronutrients for agriculture, prevention against diseases and insects of plant, and the increase of nutrient holding capacity of soil. The results were summarized as follows; 1. Barley stone is considered as Diabase Porphyrite by the analysis of X-ray Diffraction, chemical composition and microspore's observation. This mineral stone called as Barley stone has been deducted because of being seen as if the feature was attatched with cooked barley and appearently scattered about feldspar's phenocryst on the dark-green stone base. 2. In chemical characteristics of barley stone, the pH 8.7 was higher but C.E.C. 9.0 me/100g was lower then those of other clay minerals such as Bentonite and Zeolite, and so barley stone material was not considered suitable for improvement of sandy loam soil. 3. Effects of Bentonite and Zeolite application on yield of paddy rice were 108-109% compare to non-treated plot, but Barley stone has not increased rice yield. Notwithstanding the increase of application of barely stone to 5 ton per 10a, the yield increase was not significantly showing only 102-103% and the effects of Peanut, hot pepper and chinese cabbage were not recognized either.