• Journal of vocational education research
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• v.37 no.1
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• pp.101-118
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• 2018

The purpose of this study was to investigate the effect size of the difference of job satisfaction by type of employment by combining data from previous studies. For this purpose, the total of 95 articles analyzed. For the analysis of data, CMA(Comprehensive Meta-Analysis) 2.0 program was used and statistical significance was set at 5%(${\alpha}=0.05$). The main conclusions of this study are as follows. First, regular workers have higher job satisfaction than non-regular workers and the effect size of employment type is medium. Second, among five constituents of job satisfaction, the difference of wage and promotion satisfaction is greater than the difference of satisfaction in human relations, work and working environment satisfaction. Third, the job satisfaction of regular and non-regular workers differs according to the occupation areas. Fourth, there is a big difference in job satisfaction in financial, insurance, food and service occupation areas, and regular workers have higher job satisfaction than non - regular workers. On the other hand, non-regular workers have higher job satisfaction than regular workers in health, medical, social occupation areas.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.9-16
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• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• Korean small business review
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• v.40 no.3
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• pp.1-24
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• 2018

The purpose of this study is verifying with corporate financial data that the required investment amount flow shows a similar pattern as times passed, in new product development by start-up company. In the previous paper, the same authors proposed the required investment amount flow as a 'New Product Investment Curve (NPIC)'. In this study, we have studied further in various types of companies. The samples used are accounting data of 462 companies selected from 5,873 Korean companies which were finished external audit in 2015. The results of this study are as follows; The average investment period was 3 years for the listed companies, while 6 years for the unlisted companies. The investment payback period was 6 years for listed companies, while 17 years for unlisted companies. The investment payback period of the company supported by big affiliate company (We call 'greenhouse company') was 14~15 years, while 17 years for real venture companies. When we divide all companies into 4 groups in terms of R&D cost and variable cost ratio, NPIC explanatory power of 'high R&D and high variable cost ratio group (Automobile Assembly Business) is best. Among the eight investment cost indexes proposed to estimate the investment amount, the 'cash 1' (operating cash flow+fixed asset excluding land & building+intangible asset, deferred asset change)/year-end total assets) turned out to be the most effective index to estimate the investment flow patterns. The conclusion is that NPIC explanatory power is somewhat reduced when we estimate all companies together. However, if we estimate the sample companies by characteristics such as listed, unlisted, greenhouse, and venture company, the proposed NPIC was verified to be effective by showing the required investment amount pattern.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Korean Journal of Agricultural Science
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• v.31 no.2
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• pp.135-148
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• 2004

Rice is not only main food but also key farm income source of Korean farmers. In spite of the above facts, rice productivity was decreased on account of drought in every 2 or 3 years interval owing to the vulnerability of irrigation facilities throughout Korea in the past decades. As an context of the first five year economic development plan, all weather farming programme including 4 big river basin comprehensive development projects and large and medium sized irrigation water development projects were carried out successfully. Therefore the area of irrigated paddy were increased from 58% in 1970 to 76.2% in 1999. In the past decades, the Government had invested heavy financial funds to develop irrigation water but as an factor share analysis, the contribution rates of irrigation water and investment for farmland base development project have not been identified yet in national agricultural economic level. It is very scarce to find out the papers concerned to macro-economic factor share analysis or contribution rates of water and investment cost to rice production value in Korea considering the production function of the quantity of irrigation water and investment cost as independent variables. Accordingly this paper covered and aimed at identifying (1) derivation of rice production function with the time serial data from 1965 to 1999 and the contribution rates of irrigation water and total investment cost for farmland base development project. The analytical model of the contribution rates was adapted the famous Cobb-Douglass production function. According to the model analysis, the contribution rate of irrigation water to rice production in Korea was shown 37.8% which was equivalent to 0.28 of the production elasticity of water. The contribution rate of farmland base development project cost was revealed 22% and direct production cost of rice was contributed 60% in the growth of rice production and farm mechanization costs contributed to 18% of it respectively. The two contribution rates comparing with the direct production cost were small but without irrigation water and farmland base development, application of high-pay off inputs and farm mechanization might be impossible. Considering the food security and to cope with the frequent drought, rice farming and investment for the irrigation water development should be continued even in WTO system.

• Journal of Distribution Science
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• v.13 no.2
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• pp.105-112
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• 2015

Purpose - There is a recent social trend that is focused on the revitalization of business-founding. Business-founding now has an important impact on the progress of the national economy because of youth unemployment and an increase in baby-boom generation retirees. However, the support and infrastructure required for business-founding of the disabled are very insufficient. Since most supporting policies are on youth or middle-aged business-founding, business-founding by the disabled and the socially weak is losing competitiveness. Accordingly, this study diagnosed the issues by analyzing the current status of business-founding by the disabled and suggested a fostering direction for the advance of business-founding by the disabled. An idea for the founding of various business items is required for the competitiveness of business-founding by the disabled and the establishment of a growth-model based on marketing is required so that business-founding by the disabled would advance toward commercialization with growth potential. Research design, data, and methodology - Regarding the study method, the existing study literature on the status and issues in business-founding was mainly explored. In addition, the existing literature on the status and issues in business-founding by the disabled was also studied. The support on business-founding by the disabled by policy enforced by the 'Welfare Service Agency for the Disabled'and the support of related agencies including financial support on the commercialization of business-founding by the disabled were also examined. Results - Existing studies on business-founding by the disabled are very insufficient. It is very difficult to study a viable business-founding by the disabled fostering policy without thorough learning on the difficulties of business-founding by the disabled. Therefore, this study suggested a direction for the resolution of various issues such as market, funds, item, operational matters, and service by analyzing the difficulties in business-founding by the disabled until now. Particularly, this study suggested that building a commercialization model from the aspect of marketing strategy and the effort to change the growth aspect of the disabled into competitiveness are essential. Conclusions - This study examined the aspect of developing an item-development process for the growth and founding of disabled-owned businesses and the requirement of a government support system by multiple policies. Since the number of studies on business-founding by the disabled is very small, it is expected that this study would become an important study in the field of business-founding by the disabled. The revitalization of business-founding by the disabled substantially contributes to the progress of the state of the economy and continuous interest is required from the viewpoint of equal advance in the society. Success models in business-founding by the disabled should be created continuously and active publicizing of them to the disabled business-founders by analyzing the success cases would also be required. In addition, it is believed that a market entry strategy by way of a win-win strategy and cooperative relation with big companies should be also developed in the future.

• Journal of Distribution Science
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• v.12 no.6
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• pp.59-65
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• 2014

Purpose - The competitiveness of logistics in the 21st century rests on ensuring the efficiency and effectiveness of its local hub. While considering entry into a niche market in local logistics, it is pertinent to note that Budapest is emerging as a hub in EU enlargement in Eastern Europe. Big, small, and medium-sized businesses in Korea entered Hungary in the early 1990s since then, there has been a significant increase in Korean presence, of approximately 130 times. This study aimed to identify the key distribution issues that have emerged in relation to Eastern Europe. Research design, data, and methodology - This study indicates that 33 major Korean companies were located in Hungary, which serves as an out post to enter the European marketplace. However, Korea's exports to Hungary have declined (-32.0% in 2012) because of a loss of competitiveness against multinational corporations, due to factors such as the rise in current local distribution costs and wages. Hungary, on the other hand, through diversification and expansion of foreign trade with the non-EU markets, including Korea, is increasing its exports. Strategies of emerging countries are compared and reviewed in this study, by examining the vicissitudes of Hungary's distribution methods. Results - There are issues regarding Hungary's innovative ability. Hungary has a history of low wages and high skilled labor. However, the outflow of high-quality human resources for high-wages has become more extensive, and this underlines concerns that the CEE's trade hub is moving to neighboring countries. After the European financial crisis in 2010, the Hungarian economy is now developing, because of the IMF's measures, and it is being transformed into a trade surplus nation, while regaining distribution volumes rapidly. However, if there is continued lack of investment, the supply chain is weakened and exports decline amidst competition with TNCs or with China's distribution networks. Conclusions - It is necessary to create a new logistics approach for increasing trade between Korea and Hungary. First, Korean small and medium enterprises (SMEs) should build trust by working with advanced Hungarian talent, and they should expand into state-of-the-art fields instead of being confined to traditional sectors. Second, this study focuses on limiting and lowering their high expectations for success according to foreign direct investment (FDI) inflows and the role in the CEE distribution hub Korea should try to strengthen the distribution hub with its centralized population, using better, more highly educated human resources, thereby sustaining more innovative ability. Further, the positive effects of these measures are manifested in enhanced business on both sides of Hungary, namely, the EU and non-EU nations such as Turkey and emerging markets around Europe, and a better engagement in the core placement of culture and industry. For this, Korea can contribute to, and benefit from, a Hungarian logistics center, for adopting the high-tech cluster systems and commercializing distribution technology such as RFID·USN.

• The korean journal of orthodontics
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• v.50 no.3
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• pp.157-169
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• 2020

Objective: The aim of this retrospective study was to evaluate the pre- and postsurgical bone densities at alveolar and extra-alveolar sites following two-jaw orthognathic surgery. Methods: The sample consisted of 10 patients (mean age, 23.2 years; range, 18.0-27.8 years; 8 males, 2 females) who underwent two-jaw orthognathic surgery. A three-dimensional imaging program (Invivo 5) was used with multidetector computed tomography images taken pre- and postoperatively (obtained 32.3 ± 6.0 days before surgery and 5.8 ± 2.6 days after surgery, respectively) for the measurement of bone densities at the following sites: (1) alveolar bone in the maxilla and mandible, (2) extra-alveolar sites, such as the top of the head, menton (Me), condyle, and the fourth cervical vertebrae (C4). Results: When pre- and postsurgical bone densities were compared, an overall tendency of decrease in bone density was noted. Statistically significant reductions were observed in the densities of cancellous bone at several areas of the maxillary alveolar bone; cortical and cancellous bone in most areas of the mandibular alveolar bone; cortical bone in Me; and cancellous bone in C4. There was no statistically significant difference in bone density in relation to the depth of the alveolar bone. In a comparison of the bone densities between groups with and without genioplasty, there was almost no statistically significant difference. Conclusions: Accelerated tooth movement following orthognathic surgery may be confirmed with reduced bone density. In addition, this study could offer insights into bone metabolism changes following orthognathic surgery, providing direction for further investigations in this field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1118-1125
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• 2014

The past IMF foreign exchange crisis and subprime financial crisis had a big influence on variability of macroeconomics, even if the origin of its occurrence might be different. This not only had a significant infrequence on the overall industries, but also produced many insolvent companies by being closely linked with a management environment of an individual construction company leading the construction industry. The purpose of this research is to investigate characteristics of management condition of construction company according to the size of construction company using KMV model developed on the basis of the Black & Scholes option pricing theory. This research has set 28 construction companies listed to KOSPI/KOSDAQ for applying the KMV model and measuring the level of the default risk of construction companies. The data was retrieved from TS2000 established by Korea Listed Companies Association (KLCA), Statistics Korea. The analysis period is between first quarter of 2004 and fourth quarter of 2010. This research examine characteristics of the level and fluctuation process of the management condition of construction company according to the size of construction company.