• Land and Housing Review
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• v.12 no.2
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• pp.33-45
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• 2021

Due to recent changes in government policy, officetels have received attention as alternative assets, along with the uplift of office and apartment prices in Seoul. However, the current officetel price indexes use small-size samples and, thus, there is a critique on their accuracy. They rely on valuation prices which lag the market trend and do not properly reflect the volatile nature of the property market, resulting in 'smoothing'. Therefore, the purpose of this paper is to create the officetel price index using transaction data. The data, provided by the Ministry of Land, Infrastructure and Transport from 2005 to 2020, includes sales prices and rental prices - Jeonsei and monthly rent (and their combinations). This study employed a repeat sales model for sales, jeonsei, and monthly rent indexes. It also contributes to improving conversion rates (between deposit and monthly rent) as a supplementary indicator. The main findings are as follows. First, the officetel price index and jeonsei index reached 132.5P and 163.9P, respectively, in Q4 2020 (1Q 2011=100.0P). However, the rent index was approximately below 100.0. Sales prices and jeonsei continued to rise due to high demand while monthly rent was largely unchanged due to vacancy risk. Second, the increase in the officetel sales price was lower than other housing types such as apartments and villas. Third, the employed approach has seen a potential to produce more reliable officetel price indexes reflecting high volatility compared to those indexes produced by other institutions, contributing to resolving 'smoothing'. As seen in the application in Seoul, this approach can enhance accuracy and, therefore, better assist market players to understand the market trend, which is much valuable under great uncertainties such as COVID-19 environments.

• Journal of International Area Studies (JIAS)
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• v.15 no.1
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• pp.109-134
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• 2011

Drug-related crime has increased in spite of visible results of Uribe government's hard-line policies on drug eradication and illegally armed organizations which were pursued under U.S. support, without the accompaniment of quantity change in drug cultivation and trade. Military disputes of left-right illegally armed communities surrounding illegal crop cultivation rights were rather intensified, and the number of refugees was increased through enforced displaced people. The 2005 refugee registration committee RUPD reports that 3,316,862 people, 7.3% of total population, were refugees. In particular, the number of refugees presented a large increase rate of 624% when compared to the past year due to enforced displaced people. Main discharge areas of enforced displaced people are connected with drug crime and activities of illegally armed organizations, and are places of increased armed disputes in the process of occupied territory expansion of illegally armed communities and militia. Undiscriminated attacks were executed on farmers in the process of occupation of illegal crop cultivation sites by illegally armed organization and militia to emit enforced displaced people, who moved to border areas by crossing national borders. Enforced displaced people were restricted to certain areas before the appearance of Uribe administration. However, enforced displaced people not only presented quantitative expansion, but also showed tendency of nationwide expansion after national security policy was pursued. With the closing of the Amazon area, previously the main route of drug trade, activity base of illegally armed organizations was moved to the Pacific region, and Panama border area experienced refugee increase due to the new policy of enforced displaced people. This study aims to understand the actual condition and cause for the increase in refugees in Colombia based on border areas of Venezuela, which is the nation of highest dispersion of Columbian refugees, Panama, which has appeared as a new destination for refugees after the 90s, and Ecuador, which has experienced sudden refugee increase in 2000.

• Korea Science and Art Forum
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• v.30
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• pp.151-161
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• 2017

In the fields of science and engineering, multidisciplinary research is common, and researchers with a diverse range of expertise collaborate to achieve common goals. As the 4th industrial revolution gains currency in society, there is growing demand on talented personnel both with technical knowledge and skills and with communicative skills. That is, future engineers are expected to possess competence in social and artistic skills in addition to specialized knowledge and skills in engineering. In this paper we introduce an emerging field of 3D bioprinting as an exemplary case of interdisciplinary research. We have chosen the case to demonstrate the possibility of cultivating engineers with π-shaped expertise. Building on the concept of T-shaped talent, we define π-shaped expertise as having both technical skills in more than one specialized field and interpersonal/communicative skills. Wtih references to such concepts as trading zones and interactional expertise, we suggest that π-shaped expertise can be cultivated via the creation of multi-level trading zones. Trading zones are referred to as the physical, conceptual, or metaphorical spaces in which experts with different world views trade ideas, objects, and the like. Interactional expertise is cultivated, as interactions between researches are under way, with growing understanding of each other's expertise. Under the support of the university and the government, two researchers with expertise in printing technology and life sciences cooperate to develop a 3D bioprinting system. And the primary investigator of the research laboratory under study has aimed to create multiple dimensions of trading zones where researchers with different educational and cultural backgrounds can exchange ideas and interact with each other. As 3D bioprinting has taken shape, we have found that a new form of expertise, namely π-shaped expertise is formed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.31-43
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• 2022

Startups are recognized as the vitality of the economy, and countries are competing to attract competitive overseas entrepreneurs and startups to their own startup ecosystem. In this global trend, entrepreneurs cross the border without hesitation, expecting abundant available resources and a startup friendly environment. Despite the increasing frequency of start-up migration between countries, studies related to this are very rare. Therefore, this study has chosen the cross-border migration of startups between countries as a research topic, and those who have been involved in the cross-border entrepreneurial migration to South Korea as a research sample. This study consists of two stages. The first research stage hires a Delphi method to collect expert opinions and find major factors related to the global startup migration. Drawing on the prior literature on the regional startup ecosystem at the national level, this stage is to conduct expert interviews in order to discover underlying factors and subfactors important for global migration of startups. The second stage measures the importance of the factors and subfactors using the AHP model. The priorities of factors and factors were identified hiring the overseas entrepreneurs who moved to Korea as the AHP survey samples. The results of this study suggest some interesting implications. First, a group of entrepreneurs with nomadic tendencies was found in the trend of global migration of entrepreneurs. They had already started their own businesses with the same business ideas in multiple countries before settling down in Korea. Second, important unique factors and subfactors in the context of global start-up migration were identified. A good example is the government's support package, including start-up visas. Third, it was possible to know the priority of the factors and subfactors that influence the global migration of startups This study is meaningful in that it preemptively conducted exploratory research focusing on a relatively new phenomenon of global startup migration, which recently catches attention in the global startup ecosystem. At the same time, it has a limitation in that it is difficult to generalize the meanings found in this study because the research was conducted based on the case of South Korea

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.203-223
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• 2023

Recently, the platform industry is rapidly growing in the global market, and competition is intensifying at the same time. Therefore, in order for domestic platform companies to have global competitiveness in the platform market, it is necessary to study the platform business ecosystem and success factors. However, most of the recent platform-related studies have been theoretical studies on the characteristics of platform business status analysis, platform economy, and indirect network externalities of platforms. Therefore, this study comprehensively analyzed the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzed the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. And based on these factors, an IPA analysis was conducted as a way to propose a success plan to stakeholders in the platform business ecosystem. As a result of the analysis, among the success factors collected through previous studies, manpower, capital, and challenge culture were identified as factors that are relatively well maintained in both importance and satisfaction in Silicon Valley. In the end, it can be seen that the creation of an environment and culture in which Silicon Valley can use it to challenge itself based on excellent human resources and abundant capital contributes the most to the success of Silicon Valley's platform business. On the other hand, although it is of high importance to Silicon Valley's platform corporate ecosystem, the factors that show relatively low satisfaction among stakeholders are 'learning and benchmarking among active companies' and 'strong ties and cooperation between members', and it is analyzed that interest and effort are needed to strengthen these factors in the future. Finally, the systems and policies necessary for market autonomous competition, 'business support service industry', 'name value', and 'spin-off start-up' were important factors in literature research, but the importance and satisfaction of these factors were lowered due to changes in the times and environment. This study has academic implications in that it comprehensively analyzes the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzes the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. In addition, there is another academic implications that importance and satisfaction were simultaneously examined through IPA analysis based on these various extracted factors. As for academic implications, it is meaningful in that it contributed to the formation of the domestic platform ecosystem by providing the government and companies with concrete information on the success factors of the platform business ecosystem and the theoretical grounds for the growth of domestic platform businesses.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.49-65
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• 2022

This study conducted an exploratory study based on in-depth interviews to understand the characteristics and capabilities of female entrepreneurs to promote women entrepreneurship. Therefore, in this study, through in-depth interviews with eight female entrepreneurs, the main contents of entrepreneurial attitudes (need for independence, development desire, favorable conditions), start-up entry rate, start-up motivation, start-up activities and constraints were analyzed. As a result, first, it was found that the entrepreneurial attitude of female entrepreneurs has a strong motivation for successful management based on a feeling of self-satisfaction, has characteristics that prioritize independence and self-actualization, and favorable conditions for starting a business are important. Second, it was found that women's individual differences from men and social structural factors had no significant effect on the entry rate of women. Third, it was found that the most important entrepreneurship motivation for women is the spirit of challenge, self-satisfaction, and the desire to balance work and family. Fourth, female entrepreneurs showed little difference in perception between male and female entrepreneurs in terms of resource access, but there was some discrimination in the network. Fifth, the main industries of female entrepreneurs are small businesses, and there is a tendency to be concentrated in industries with low profit margins and low growth and sales. Finally, it was found that barriers to women's entrepreneurship still exist. Based on the results of this study, the following implications are suggested. First, this study is differentiated in that it mainly identified the characteristics of women's experiences and social environments while starting a business and running a business. Second, in the case of female entrepreneurs, there is a need to spread a positive awareness of women entrepreneurship by arguing that the barriers to entrepreneurship unique to women are not high and can be sufficiently overcome. Lastly, although opportunistic start-ups based on women's social experience or management ability in work life are important for women's entrepreneurship, government support policies are needed to promote professional technology start-ups.

• Information Systems Review
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• v.22 no.2
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• pp.137-166
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• 2020

While South Koreans overseas travelling rate has been increased every year, domestic travelling rate has been at a standstill for several years. The purpose of this study is to analyze domestic traveling styles of Koreans according to their generations in order to provide generation-specific traveling services. For this purpose, we categorized the survey respondents into four different generations, which are Millennium (age 19~34), X generation (35~54), Baby Boomer (55~64) and senior by following the criterions of the Korea National Tourism Organization. After then, we analyze factors related to travel preparation process, the actual traveling activities and satisfaction after the travel. In this study, 16,713 data collected by the Ministry of Culture, Sports and Tourism are used. The results of this study show that Korean people tends to acquire domestic traveling information from their own or acquaintances past experiences. Also, they do not prefer the organized trip for domestic travels, thus do not buy package products a lot. In addition, natural scenery, rich in cultural heritage, and convenient accommodation are the most important determinant factors affecting the overall travel satisfaction of level for all generations. The traveling characteristics for each generation are as follows. Millennium get traveling information from the internet a lot, and more specifically, they refer portal sites and social network services (SNS) in many cases. Also, they tend to travel in summer peak season to popular destinations and pursues active traveling experiences. Generation X has similar traveling patterns with Millennium, however they major transportation method is using their own car. Also, transportation convenience and satisfactory leisure activity are important factors affecting the overall satisfaction level to Generation X. On the other hand, Baby boomer generation has a greater emphasis on appreciation of nature, visiting famous restaurants, and relaxation, rather than actively participating experiencing programs. They travel evenly in summer and spring/fall season to many different areas instead of focusing on popular tourist spots. In addition, shopping and eating delicious food are the important factors affecting the overall satisfaction level for them. Lastly, Senior generation has similar characteristics with Baby boomer in many ways, however, they travel a lot on the same day using public transportations or car rental service. They prefer spring and autumn trips rather than summer peak season, and tend to buy packaged travel products a lot compared with other generations. If these different traveling characteristics of each generation are considered for organizing and customizing tourism services, it is expected that domestic tourism satisfaction level will be ultimately increased.

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.1
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• pp.327-353
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• 2017

The issue submitted to the Court of Justice on the merits of case C---573/13 originated from a claim brought in the context of a dispute between Air Berlin and the German Federal Union of Consumer Organisations and Associations. The challenge concerned the way in which air fares were displayed in Air Berlin's computerised booking system. The system was organised in such a way that, after selecting a date and a departure airport, one would find all possible flight connections in a summary table. However, the final price of the ticket was displayed only for the clicked connection, and not for all connections, thus preventing customers from being able to compare such price with the prices of other connections. The German Federal Union took the view that this practice did not meet the requirements laid down by Article 23 of Regulation (EC) No. 1008/2008, which requires transparency in the prices set for air services. This led the German State to bring an injunctive action to cause Air Berlin to discontinue said practice. The claim was upheld at both the application and appeal stage of the relevant proceedings. Subsequently, Air Berlin submitted the matter to the German Federal High Court, which decided to stay the proceedings and ask for a preliminary ruling from the Court of Justice as to 1. whether Article 23 of Regulation (EC) No. 1008/2008 must be interpreted as meaning that, during the computerised booking process, the final price to be paid must be indicated at all times when prices of air services are shown, including when they are shown for the first time; and 2. whether, during the computerised booking process, the final price must be indicated only for the air service specifically selected by the customer or for each air service shown. In a nutshell, the Court, by the here---discussed judgment determined that Article 23 of Regulation (EC) No. 1008/2008 must be interpreted as meaning that, in the context of a computerised air ticket booking system, the final price to be paid must be indicated not only for the air service specifically selected by the customer, but also for each air service in respect of which the fare is shown. Clearly the above judgment will place air companies under an obligation to update and adjust (when needed) their computerised ticket booking and payment systems, in consideration of the primary need for consumers to be aware at all times of the actual price payable for a ticket and be able to compare the price of the service selected with the prices for other air services in respect of which the fare is shown.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.