• The Korean Journal of Air & Space Law and Policy
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• v.25 no.1
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• pp.97-158
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• 2010

The purpose of this paper is to research on the contents and improvement of national legislations relating to space development in Korea to make the sustainable progress of space development project in Korea. Korea has launched its first satellite KITST-1 in 1992. The National Space Committee has established "The Space Development Promotion Basic Plan" in 2007. The plan addressed the development of total 13 satellites by 2010 and the space launch vehicle by 2020, and the launch of moon exploration spaceship by 2021. Korea has built the space center at Oinarodo, Goheng Province in June 2009. In Korea the first small launch vehicle KSLV-1 was launched at the Naro Space Center in August 2009, and its second launch was made in June 2010. The United Nations has adopted five treaties relating to the development of outer space as follows : The Outer Space Treaty of 1967, the Rescue and Return Agreement of 1968, the Liability Convention of 1972, the Registration Convention of 1974, and the Moon Treaty of 1979. All five treaties has come into force. Korea has ratified the Outer Space Treaty, the Rescue and Return Agreement, the Liability Convention and the Registration Convention excepting the Moon Treaty. Most of development countries have enacted the national legislation relating to the development of our space as follows : The National Aeronautic and Space Act of 1958 and the Commercial Space Act of 1998 in the United States, Outer Space Act of 1986 in England, Establishment Act of National Space Center of 1961 in France, Canadian Space Agency Act of 1990 in Canada, Space Basic Act of 2008 in Japan, and Law on Space Activity of 1993 in Russia. There are currently three national legislations relating to space development in Korea as follows : Aerospace Industry Development Promotion Act of 1987, Outer Space Development Promotion Act of 2005, Outer Space Damage Compensation Act of 2008. The Ministry of Knowledge Economy of Korea has announced the Full Amendment Draft of Aerospace Industry Development Promotion Act in December 2009, and it's main contents are as follows : (1) Changing the title of Act into Aerospace Industry Promotion Act, (2) Newly regulating the definition of air flight test place, etc., (3) Establishment of aerospace industry basic plan, establishment of aerospace industry committee, (4) Project for promoting aerospace industry, (5) Exploration development, international joint development, (6) Cooperative research development, (7) Mutual benefit project, (8) Project for furthering basis of aerospace industry, (9) Activating cluster of aerospace industry, (10) Designation of air flight test place, etc., (11) Abolishing the designation and assistance of specific enterprise, (12) Abolishing the inspection of performance and quality. The Outer Space Development Promotion Act should be revised with regard to the following matters : (1) Overlapping problem in legal system between the Outer Space Development Promotion Act and the Aerospace industry Development promotion Act, (2) Distribution and adjustment problem of the national research development budget for space development between National Space Committee and National Science Technology Committee, (3) Consideration and preservation of environment in space development, (4) Taking the legal action and maintaining the legal system for policy and regulation relating to space development. The Outer Space Damage Compensation Act should be revised with regard to the following matters : (1) Definition of space damage and indirect damage, (2) Currency unit of limit of compensation liability, (3) Joint liability and compensation claim right of launching person of space object, (4) Establishment of Space Damage Compensation Council. In Korea, it will be possible to make a space tourism in 2013, and it is planned to introduce and operate a manned spaceship in 2013. Therefore, it is necessary to develop the policy relating to the promotion of commercial space transportation industry. Also it is necessary to make the proper maintenance of the current Aviation Law and space development-related laws and regulations for the promotion of space transportation industry in Korea.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

• Clinical and Experimental Reproductive Medicine
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• v.35 no.2
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• pp.99-110
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• 2008

Objectives: Preimplantation genetic diagnosis (PGD) has become an assisted reproductive technique for couples carrying genetic conditions that may affect their offspring. Osteogenesis imperfecta (OI) is an autosomal dominant disorder of connective tissue characterized by bone fragility and low bone mass. At least 95% of cases are caused by dominant mutations in the COL1A1 or COL1A2. In this study, we report on our experience clinical outcomes with 5 PGD cycles for OI in two couples. Methods: Before clinical PGD, we assessed the amplification rate and allele drop-out (ADO) rate of alkaline lysis and nested PCR protocol using heterozygous patient's single lymphocytes in the pre-clinical diagnostic tests for OI. We performed 5 cycles of PGD for OI by nested PCR for the causative mutation loci, COL1A1 c.2452G>A and c.3226G>A, in case 1 and case 2, respectively. The PCR products were analyzed by agarose gel electrophoresis, restriction fragment length polymorphism (RFLP) analysis with HaeIII restriction enzyme in the case 1 and direct DNA sequencing. Results: We confirmed the causative mutation loci, COL1A1 c.2452G>A in case 1 and c.3226G>A in case 2. In the pre-clinical tests, the amplification rate was 94.2% and ADO rate was 22.5% in case 1, while 98.1% and 1.9% in case 2, respectively. In case 1, a total of 34 embryos were analyzed and 31 embryos (91.2%) were successfully diagnosed in 3 PGD cycles. Eight out of 19 embryos diagnosed as unaffected embryos were transferred in all 3 cycles, and in the third cycle, pregnancy was achieved and a healthy baby was delivered without any complications in July, 2005. In case 2, all 19 embryos (100.0%) were successfully diagnosed and 4 out of 11 unaffected embryos were transferred in 2 cycles. Pregnancy was achieved in the second cycle and the healthy baby was delivered in March, 2008. The causative locus was confirmed as a normal by amniocentesis and postnatal diagnosis. Conclusions: To our knowledge, these two cases are the first successful PGD for OI in Korea. Our experience provides a further demonstration that PGD is a reliable and effective clinical techniques and a useful option for many couples with a high risk of transmitting a genetic disease.

• 한국사회복지학회:학술대회논문집
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• 2003.10a
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• pp.185-216
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• 2003

This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom (($x^2=64.950$, df=61, P=0.341), and the adjusted Goodness of Fit Index (AGFI) were .964, and the Comparative Fit Index (CFI) were .997, and the Root Mean Squared Residual (RMR) was respectively. .038. The model was best fitted and could predict the career success more highly because the goodness of fit index in the whole models was within the allowed range. In conclusion, the following research implications can be suggested. First, the occupational type of research participants was one of the most important variables to predict the career success for both research participant groups. It means that people with disabilities require human development services including education. They need to improve themselves in this knowledge-based society. Furthermore, for maintaining the career success, people with disabilities should be approached by considering the subjective career success aspects including wages and the promotion opportunities than the objective career success aspects.

• Journal of Preventive Medicine and Public Health
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• v.30 no.2 s.57
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• pp.308-326
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• 1997

Many studies have led to the notion that essential hypertension in adults is the result of a process that starts early in life: investigation of blood pressure(BP) in children and adolescents can therefore contribute to knowledge of the etiology of the condition. A unique longitudinal study on BP in Korea, known as Kangwha Children's Blood Pressure(KCBP) Study was initiated in 1986 to investigate changes in BP in children. This study is a part of the KCBP study. The purposes of this study are to show changes in BP and to determine factors affecting to BP level and change in Korean adolescents during age period 12 to 16 years. A total of 710 students(335 males, 375 females) who were in the first grade at junior high school(12 years old) in 1992 in Kangwha County, Korea have been followed to measure BP and related factors(anthropometric, serologic and dietary factors) annually up to 1996. A total of 562 students(242 males, 320 females) completed all five annual examinations. The main results are as follows: 1. For males, mean systolic and diastolic BP at age 12 and 16 years old were 108.7 mmHg and 118.1 mmHg(systolic), and 69.5 mmHg and 73.4 mmHg(diastolic), respectively. BP level was the highest when students were at 15 years old. For females, mean systolic and diastolic BP at age 12 and 16 years were 114.4 mmHg and 113.5 mmHg(systolic) and 75.2 mmHg and 72.1 mmHg(diastolic), respectively. BP level reached the highest point when they were 13-14 years old. 2. Anthropometric variables(height, weight and body mass index, etc) increased constantly during the study period for males. However, the rate of increase was decreased for females after age 15 years. Serum total cholesterol decreased and triglyceride increased according to age for males, but they did not show any significant trend fer females. Total fat intake increased at age 16 years compared with that at age 14 years. Compositions of carbohydrate, protein and fat among total energy intake were 66.2:12.0:19.4, 64.1:12.1:21.8 at age 14 and 16 years, respectively. 3. Most of anthropometric measures, especially, height, body mass index(BMI) and triceps skinfold thickness showed a significant correlation with BP level in both sexes. When BMI was adjusted, serum total cholesterol showed a significant negative correlation with systolic BP at age 12 years in males, but at age 14 years the direction of correlation changed to positive. In females serum total cholesterol was negatively correlated with diastolic BP at age 15 and 16 years. Triglyceride and creatinine showed positive correlation with systolic and diastolic BP in males, but they did not show any correlation in females. There was no consistent findings between nutrient intake and BP level. However, protein intake correlated positively with diastolic BP level in males. 4. Blood pressure change was positively associated with changes in BMI and serum total cholesterol in both sexes. Change in creatinine was associated with BP change positively in males and negatively in females. Students whose sodium intake was high showed higher systolic and diastolic BP in males, and students whose total fat intake was high maintained lower level of BP in females. The major determinants on BP change was BMI in both sexes.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Journal of Korean Institute of Fire Investigation
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• v.9 no.1
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• pp.103-121
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• 2006

We are living in more comfortable circumstances with the social developments and the improvement of the standard of living, but, on the other hand, we are exposed to an increase of the occurrences of tires on account of large-sized, higher stories, deeper underground building and the use of various energy resources. The materials of the floor in a residence modern society have been going through various alterations in accordance with the uses of a residence and are now used as final goods in interioring the bottom of apartments, houses and shops. There are so many kinds of materials you usually come in contact with, but in the first place, we need to make an experiment on the spread of the fire with the hypocaust used as the floors of apartments, etc. and the floor covers you usually can get easily. We, scientific investigators, can get in contact with the accidents caused by incendiarism or an accidental fire closely connected with petroleum stuffs on the floor materials that give rise to lots of problems. on this account, I'd like to propose that we conduct an experiment on fire shapes by each petroleum stuff and that discriminate an accidental tire from incendiarism. In an investigation, it seems that finding a live coal could be an essential part of clearing up the cause of a tire but it could not be the cause of a fire itself. And besides, all sorts of tire cases or fire accidents have some kind of legislation and standard to minimize and at an early stage cope with the damage by tires. That is to say, we are supposed to install each kind of electric apparatus, automatic alarm equipment, automatic fire extinguisher in order to protect ourselves from the danger of fires and check them at any time and also escape urgently in case of fire-outbreaking or build a tire-proof construction to prevent flames from proliferating to the neighboring areas. Namely, you should take several factors into consideration to investigate a cause of a case or an accident related to fire. That means it's not in reason for one investigator or one investigative team to make clear of the starting part and the cause of a tire. accordingly, in this thesis, explanations would be given set limits to the judgement and verification on the cause of a fire and the concrete tire-spreading part through investigation on the very spot that a fire broke out. The fire-discernment would also be focused on the early stage fire-spreading part fire-outbreaking resources, and I think the realities of police tire investigations and the problems are still a matter of debate. The cause of a fire must be examined into by logical judgement on the basis of abundant scientific knowledge and experience covering the whole of fire phenomena. The judgement of the cause should be made with fire-spreading situation at the spot as the central figure and in case of verifying, you are supposed to prove by the situational proof from the traces of the tire-spreading to the fire-outbreaking sources. The causal relation on a fire-outbreak should not be proved by arbitrary opinion far from concrete facts, and also there is much chance of making mistakes if you draw deduction from a coincidence. It is absolutely necessary you observe in an objective attitude and grasp the situation of a tire in the investigation of the cause. Having a look at the spot with a prejudice is not allowed. The source of tire-outbreak itself is likely to be considered as the cause of a tire and that makes us doubt about the results according to interests of the independent investigators. So to speak, they set about investigations, the police investigation in the hope of it not being incendiarism, the fire department in the hope of it not being problems in installments or equipments, insurance companies in the hope of it being any incendiarism, electric fields in the hope of it not being electric defects, the gas-related in the hope of it not being gas problems. You could not look forward to more fair investigation and break off their misgivings. It is because the firing source itself is known as the cause of a fire and civil or criminal responsibilities are respected to the firing source itself. On this occasion, investigating the cause of a fire should be conducted with research, investigation, emotion independent, and finally you should clear up the cause with the results put together.