• International Area Studies Review
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• v.16 no.3
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• pp.3-25
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• 2012

This study is to look at the relationship of entrepreneurship(innovativeness, risk-taking), the learning competence, environmental factors(the domestic market hostility, the speed of technological change) and export performance in international new ventures(INVs). In addition, the integrated model is constructed for the purpose of analysis of the moderating effects of environmental factors. Through the existing investigation, nine hypotheses are set up. PLS(Partial Least Square) analysis method is used to sample of 115 INVs. Analysis, the two elements of entrepreneurship influenced the positive(+) in the learning competence and export performance. And the relationship of learning competence and export performance is significant. In the moderating effects, only the domestic market hostility has a significant moderating effects between the learning competence and innovativeness. The results of this research shows that innovativeness influence the learning competence playing a positive role in the performance in the domestic market is higher. This point illustrates the practical implications of the importance of innovation in learning empowerment.

• International Area Studies Review
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• v.20 no.2
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• pp.63-83
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• 2016

This paper examines the determinants of efficiency in a KOSDAQ-listed manufacturing firm. We use Data Envelopment Analysis (DEA) to estimate the efficiency of the export manufacturing firm. We employ two inputs (number of employees, equity) and one output (sales) in the DEA. The determinants of export manufacturing firm efficiency are estimated using the panel Tobit model. An analysis of 369 export manufacturing firms from 2013 to 2015 indicates the following results: First, the R&D intensity, the wage and salary intensity, total asset, and equity ratio each had a negative impact on both the CCR and BCC efficiency scores. However, export intensity had a negative impact on CCR efficiency scores in a KOSDAQ-listed total export manufacturing firm. Second, the R&D intensity had a positive impact on both the CCR and BCC efficiency scores, but export intensity, the wage and salary intensity, and equity ratio each had a negative impact on the CCR and BCC efficiency scores in a KOSDAQ-listed large export manufacturing firm. Third, the R&D intensity, the wage and salary intensity, total asset, and equity ratio each had a negative impact on both the CCR and BCC efficiency scores; respectively, in a KOSDAQ-listed small and medium export manufacturing firm.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• International Area Studies Review
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• v.22 no.2
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• pp.61-91
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• 2018

Credit Guarantee scheme is one of the most effective tools for the small business policy. The performance analysis on domestic institution level is relevant in terms of various factors of assisting tools factor. This study measured comparative global efficiency by DEA model and Super-efficiency model among 70 credit guarantee institutions in Japan, Taiwan, and Korea who are operating the schemes. At the result of the analysis, Korean credit guarantee institutions are comparatively efficient than Japanese institutions, and the DMU shows moderate in operation efficiency. The Super-efficiency ranked by Hiroshima, Taiwan SMEG, Pusan, Chiba, Shizuoka, Ulsan, and KOTEC. Most of the Credit Guarantee Institutions showed increasing returns to scale, and it indicates increasing input strategy. The statistical difference of efficiency level in Japan and Korea shows very meaning numbers. This research suggest that (1)Periodical Analysis are needed on Japanese Schemes, (2)The analysis on the impact of credit guarantee scale to the national economy and SME policy, (3) Analysis on the conclusive factors of the efficiency, (4)The policy direction has to be made by inefficient factor analysis, (5) The measurement tools of efficiency of the schemes in various aspects.

• Korean Journal of Labor Studies
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• v.24 no.2
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• pp.247-291
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• 2018

This study investigates the employment structure and the social safety net experience of the subcontracting cleaning workers in Korea, who have been main targets of the labor outsourcing despite the necessity and permanence of their labour. This study specifically focuses on the fact that these subcontracting cleaning workers are mostly female and in their old age, and analyzes how the combination of their age, gender, and employment structure leads to the (mis)match with the Korean social security system. Case study with in-dept interview method has been conducted to the old-aged female subcontracting cleaning workers in Korea. The result of this study is as follows. It was the income insecurity that led them to (re)enter the labour market, and the cleaning work was the almost the only wage work they could do considering their age and gender. Cleaning workers are mostly employed in the subcontracting company, and thus their labour contracts depend on the business contract period between the original and subcontracting company. Consequently, their employment relationship is mostly insecure unless they are guaranteed employment succession through the collective agreement of trade union. Moreover, it has been discovered that the employment insecurity due to the indirect employment relationship led to the poor labour conditions, low wage, and the exclusion from the social safety net.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.231-236
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• 2018

In order to survive the competition, companies are developing new knowledge, applying and communicating, and accumulating numerous knowledge management activities. Therefore, it is important to establish and operate an effective knowledge management system to introduce and utilize effective knowledge management. So, the purpose of this study is to confirm the relation between the learning orientation of the organization and the knowledge management which are the main results in the knowledge management. In other words, this study investigated how the knowledge management system of a company affects the learning orientation of the corporate members, so as to be a basis for establishing the direction of knowledge management in the future. This study synthesized theory and previous studies, developed hypotheses and research models, and conducted empirical analysis through questionnaire surveys. This study is analyzed that knowledge management system has a positive effect on learning growth will. In addition, it was confirmed that the knowledge management system has a statistically significant relationship with the intention of internal improvement. Therefore, for the successful operation and management of the support management system, maintenance of the system that can focus on the strategic and appropriate learning model of the organization and the role of the organization member is an important variable. The results of this study are expected to provide meaningful guidance not only in the practical field but also in the study of the organization's knowledge management system.

• Journal of Technology Innovation
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• v.27 no.2
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• pp.99-122
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• 2019

ODA (Official Development Assistance) aims for practicing international humanitarianism in developing countries. However, ODA donors also seek to find convincing evidence meeting the national economic & political interests in the international community. In this regards, precise & unbiased estimation of the policy effects of ODA aid on the donors' exports to the recipient countries has recently become one of the primary concerns of the ODA donors, especially developing countries including Korea of which economy structure heavily relies on exports for economic growth. Based on the basic gravity model, this study empirically analyzes the effects of technical cooperation ODA delivering skills, knowledge and technical know-how on Korea's exports to the ODA recipient countries using 10-year panel data from 2007 to 2016. Specifically, by incorporating major variables affecting trade such as GDP, distance, FDI etc, the effect of technical cooperation ODA on Korea's exports to the ODA recipient countries is estimated with various kinds of panel models. As a result, technical cooperation ODA has a statistically significant impact on Korea's exports to ODA recipient countries, especially in the exports of intermediate goods. And the detail process of this black-boxed mechanism is scrutinized through case studies on Uzbekistan, The Philippines, and Morocco.

• The Journal of Bigdata
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• v.3 no.2
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• pp.19-33
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• 2018

Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.4
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• pp.373-394
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• 2020

The strengthening of multilateral international sanctions against North Korea has raised questions as to how effective they are in exerting pressure on the country's economy. In this paper, we address this question by examining their impact on the country's integration into regional and global apparel production networks. North Korea has in the past decade become an increasingly competitive exporter of apparel on the basis of consignment-based processing arrangements. Official trade data shows a sharp drop in North Korean exports of clothing since the sectoral ban in 2017. There is evidence to suggest, however, that exports have continued on a more informal and clandestine basis. North Korea's integration into apparel production networks has also taken the form of the dispatch of workers to factories in China's northeastern border regions. Yet there is evidence that the recent sanctions imposed on such practices has similarly led to illicit practices such as working on visitors' visas, often with the help of Chinese enterprises and local government. The resilience of North Korea's integration into apparel production networks follows a capitalist logic and is result of the highly profitable nature of apparel production for all actors concerned and a correspondingly strong desire to evade sanctions. As such, the analysis contributes to the literature on sanctions that suggests that the measures may contribute to emergence of growing informal and illicit practices and to the role of the clandestine economy.

• International Area Studies Review
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• v.21 no.4
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• pp.223-245
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• 2017

This study is examined interaction between carbon market with stock market using a multivariate GARCH(DCC) model. Carbon market is EU ETS EUA price, stock market is the iron and cement stock price which has relatively energy intensive and massive carbon emissions sector in the industrial sector. It also analyzed changes in the correlation between the markets through an analysis of correlation coefficients. Moreover, it checked whether there was marketability expansion(or expansion of carbon emissions reduction) through the analysis above. As a result of empirical tests, it showed that the price spillover effect was insignificant. In addition, it represented that there was a weak correlation between the two markets since the volatility spillover effect disappeared in the second phase by an external shock(a financial crisis). Moreover, it was revealed that there were no significant changes although there was a weak upward trend in terms of the correlation between the carbon market and the stock market. This implies that emission rights could not expand marketability to financial market as a commodity(or did not play its natural role of the reduction of carbon emission).