• Title/Summary/Keyword: Ratio function

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Stock-Index Invest Model Using News Big Data Opinion Mining (뉴스와 주가 : 빅데이터 감성분석을 통한 지능형 투자의사결정모형)

  • Kim, Yoo-Sin;Kim, Nam-Gyu;Jeong, Seung-Ryul
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.143-156
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    • 2012
  • People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

Automatic gasometer reading system using selective optical character recognition (관심 문자열 인식 기술을 이용한 가스계량기 자동 검침 시스템)

  • Lee, Kyohyuk;Kim, Taeyeon;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.1-25
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    • 2020
  • In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

Results of Bronchial Sleeve Resection for Primary Lung Cancer (원발성 폐암에 대한 기관지 소매 절제술의 성적)

  • Kim, Dae-Hyun;Youn, Hyo-Chul;Kim, Soo-Cheol;Kim, Bum-Shik;Cho, Kyu-Seok;Kwak, Young-Tae;Hwang, En-Gu;Kim, Dong-Won;Park, Joo-Chul
    • Journal of Chest Surgery
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    • v.40 no.1 s.270
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    • pp.37-44
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    • 2007
  • Background: It is known that long-term survival rate in patients underwent bronchial sleeve lobectomy for primary lung cancer is at least equal to that in patients underwent pneumonectomy, and bronchial sleeve lobectomy is performed in patients with suitable tumor location even in patients have adequate pulmonary function. Sleeve pneumonectomy is performed when carina was invaded by tumor or tumor location was near to the carina. We performed this study to know our results of sleeve resection for primary lung cancer. Material and Method: We analyzed retrospectively the medical records of 45 patients who underwent sleeve lobectomy or sleeve pneumonectomy for primary lung cancer by one thoracic surgeon from May 1990 to July 2003 in Department of Thoracic & Cardiovascular Surgery, College of Medicine, Kyung Hee University. Follow-up loss was absent and last follow-up was performed in April 5, 2005. Kaplan-Meyer method and log-lank test were used to know long-term survival rate and p-value. Result: Mean age was 60 years old and male to female ratio 41:1. Histologic types were squamous cell carcinoma were 39, adenocarcinoma were 4, and others were 2 patients. Pathologic stages were I 14, II 14, and III 17 patients. Nodal stages were N0 23, N1 13, and N2 9 patients. Types of operation were sleeve lobectomy 40 and sleeve pneumonectomy 5 patients. Operative mortality was 3 patients and its cause was respiratory complications. Early complications were pneumonia 4, atelectasis 8, air leakage more than 7 days 6, and atrial fibrillation 4 patients. In 19 patients tumor was recurred. Local recurrence was 10 and systemic metastasis was 9 patients. Overall 5, 10-year survival rate were 54.2%, 42.5%. The 5, 10-year survival rates according to the pathologic stage were 83.9%, 67.1% in stage I, 55%, 47.1% in II, 33.3%, 25% in III, and significance difference was present between stage I and III. The 5, 10-year survival rate according to the lymph node involvement were 63.9%, 54.6% in N0, 53,8%, 46.5% in N1, 28.5%, 14.2% in N2, and significance difference was present between N0 and N2. Conclusion: Because bronchial sleeve lobectomy for primary lung cancer could be performed safely and shows acceptable long-term survival rate, it could be considered primary in case of suitable tumor location if complete resection is possible. Although sleeve pneumonectomy for primary lung cancer shows somewhat high operative mortality rate, it could be considered in view of curative treatment.

DEVELOPMENT OF STATEWIDE TRUCK TRAFFIC FORECASTING METHOD BY USING LIMITED O-D SURVEY DATA (한정된 O-D조사자료를 이용한 주 전체의 트럭교통예측방법 개발)

  • 박만배
    • Proceedings of the KOR-KST Conference
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    • 1995.02a
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    • pp.101-113
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    • 1995
  • The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

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The Clinical Characteristics of Lung Cancer in Patients with Idiopathic Pulmonary Fibrosis (특발성 폐섬유화증에 동반된 폐암 환자의 임상적 특정)

  • Park, Joo-Hun;Lee, Jin-Seong;Song, Koun-Sik;Shim, Tae-Sun;Lim, Chae-Man;Koh, Youn-Suck;Lee, Sang-Do;Kim, Woo-Sung;Kim, Won-Dong;Kim, Dong-Soon
    • Tuberculosis and Respiratory Diseases
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    • v.46 no.5
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    • pp.674-684
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    • 1999
  • Background : It has been generally known that the incidence of lung cancer is higher in the patients with idopathic pumonary fibrosis (IPF) than those in general population. The reported incidence was variable from 4.8 to 43.2%. There were controversies on the most frequent cell type (squamous cell carcinoma vs. adenocarcinoma) and no study was done about the real concordance of cancer and the fibrotic lesion. And the pulmonary fibrosis may influence not only the development of cancer but also the treatment and prognosis of the cancer, but there was no report on that point. Method : Total 63 patients ($66.8{\pm}7.8$ year, M : F=61 : 2) were diagnosed as IPF combined with lung cancer (IFF-CA) at Asan Medical Center. A retrospective analysis was done about the risk factors of the lung cancer, pulmonary function test, the site of cancer(especially the relationship of the cancer with the fibrotic lesion), the histologic types, and the stage of cancer. The histologic types were compared with those of 2,660 patients with lung cancer who were diagnosed at the same institute for the same period. The effect of IPF on the treatment of the cancer was evaluated with the survival time after the detection of lung cancer. Results : The lung cancer was found in 63(22.9%) out of 281 patients with IPF. But in most of them(45 patients), lung cancer was detected at the same time with IPF and only in 18 patients, the cancer was diagnosed during the follow-up($25.2{\pm}17.7$ months) of IPF. So in our study, 6.7% of patients with IPF developed lung cancer during the course of the disease. The age ($66.8{\pm}7.84$ vs. $63.4{\pm}11.1$ years), percentage of smoker (88.9 vs. 67.2%), and the male gender (96.8 vs. 67.6%) were significantly higher in IPF-CA compared with lone IPF (p<0.05). The odds ratio of smoking was 4.7 compared with non smoking IPF controls. The lung cancer was located more frequently in the upper lobe and 55.5% was in the periphery of lung. The cancer was developed in the fibrotic lesion in 23 patients (35.9%), and in the majority of the patients, the cancer was separated from the fibrosis. The cell type of the lung cancer in IPF-CA was squamous cell carcinoma 34.9%, adenocarcinoma 30.2%, small cell carcinoma 19.0%, large cell undifferenciated carcinoma 6.3%, and others 9.5%. No significant difference in the distribution of histologic type of the lung cancer was found between IPF-CA and lone lung cancer. There was no significant difference in demographic features, cell types, location and the stage of the cancer between the group with concurrent IPF-CA and the group with cancer diagnosed during the follow up of IPF. There was a tendency (but statistically not significant : p=0.081) of higher incidence of adenocarcinoma among the cancers developed in the fibrotic area(43.5%) (F-CA) than in the cancers in non-fibrotic area (22.5%) (NF-CA). The prognosis of the patients with F-CA was poor (median survival : 4 months) compared with the patients with NF-CA (7 months, p=0.013), partly because the prevalence of severe IPF (the extent of fibrosis in HRCT 50%) was higher in F-CA group. Conclusion : These data suggest that the lung cancer in the patients with IPF has similar features to the ordinary lung cancer.

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A Study on Medium-Sized Enterprises of Japan (일본의 중견기업에 관한 연구 : 현황과 특징, 정책을 중심으로)

  • Kang, Cheol Gu;Kim, Hyun Sung;Kim, Hyun Chul
    • Korean small business review
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    • v.32 no.2
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    • pp.209-223
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    • 2010
  • Korea's business is composed of a few large-sized enterprises (which can be abbreviated as LSE) and a majority of small-sized enterprises (SSE). Although there has been a growing recognition of the need for the development of medium-sized enterprises (MSE) which can serve as a link between SSE and LSE, as yet there has not yet been a consensus on the definition, characteristics and the function of the MSE in Korea. Nowadays, the world is being globalized, and Japan and China are in competition to ne a great economic power. While East Asia is experiencing rapid changes, promoting MSE which can secure flexibility and efficiency through covering up the limitation of LSE and SSE is needed in order to respond the global market which is being specialized. The features of MSE in Japan can be listed as follows. First, the MSE in Japan is developing the company through getting into niche markets which are hard for major companies to enter rather than developing markets in order to compete against major companies directly. While MSEs are endeavoring to build the business firmly in the domestic market, they can possess special and competitive technical skills through trials and errors; so that they can get a chance develop their business through independent business system rather than putting their effort to compete against major companies. Second, from the MSEs with competitive edge in the market, there are many contributions to the national exportation. Those MSEs produce in domestic and maintain the quality of high price products which need cutting-edge technology, while they relocate the low and middle priced goods to the country where manufacturing costs are low, so that they can maintain the price competitiveness. Third, the industrial structure in Japan is formed from dual structure between major companies and small sized companies. In other words, in Japan's industrial structure which are composed of subcontract structure, this dual structure has taken a major role of small sized companies' growth and manufacturing businesses' international competitive power. Forth, MSE in Japan adopt a strategy of putting their value on qualitative scale growth rather than quantitative scale growth. In this paper, the case of Japanese MSE is analyzed. Along with its long history of Industrialization, Japan has a corporate environment where the SSEs can develop as a MSE and later a LSE through a full-support system. Among its SSEs, there are a number of world class corporations equipped with a large domestic market, win-win cooperation with the LSEs and an independent technology development. It can also be observed that these SSEs develop into MSEs with sustainable growth potentials. This study will focus on the condition under which the MSEs of Japan have been developed, and how they have survived the competition between SSEs and LSEs. Through this study, this paper attempts to offer solutions to Korea's polarization between the SSE and LSE, while providing the basis for SSEs revitalization. In general, if both extremities phenomenon deepen between LSE and SSE, there are possible fears of occurring disutility in national economy by the monopolization of LSE. For that reason, enterprise group, which can make SSE or MSE compete LSE in some area and ease the monopoly and oligopoly problem, is needed. This awareness has been shared for ages long. Nevertheless, there is no legal definition for MSE in Japan, and there is no definition about the enterprise size or unified view of MSE between scholars, but it is defined differently by each of academical person or research institution and study meeting. For that reason, this paper will organize the definition of MSE in Japan, and then will propose the characteristics of the background which has made MSE secure competitiveness and sustainable growth in global market. This study focus on that because through this process, the positive change to the awareness of MSE can be proposed in Korea and to seek the policy direction for building institutional framework which can make SSE become MES. Through this way, the fundamentals for SSE to become MSE can be managed and some appropriate suggestions which will be able to make MSE enter the global market in the future can also be proposed. Due to these facts, this study is very important and well timed task. In a sense of this way, this study will examine the definition and role of MSE in Japan. after this examination, this study will deal with the status, special feature, and promotion policy for MSE. Through this analysis of MSE in Japan, the foundation which be able to set the desirable role model for MSE in Korea can be proposed. Also, the political implication which is needed to push ahead to contribute to creating employment and economic growth through sustainable growth of MSEs in economic system of Korea can be offered through this study. It has been found that Japan's MSE functions as an indispensable link among various industrial structures by holding a significant position in employment rate, production and value added. Although the MSEs took up less than 1% of the entire number of businesses with 2700 manufacturing firms and 7000 non-manufacturing firms, its employment ratios are about 15%, while taking about 25% of the manufacturing industry's exports. In industries such as machinery and electronics which is considered Japan's major industry, the MSEs showed a higher than average ratio of manufacturing exports and employment rate. It can be analyzed that behind Japan's advantageous industries, close and deeply knit MSEs exist. Although there are no clearly stated policies geared towards the MSEs by the Japanese government, various political measures exist such as the R&D Project and the inducement of cooperation between enterprises which gives room for MSEs to participate in the SSE policies. In relation to these findings, the following practical measures can be considered in order to revitalize Korea's MSEs: First, there is a need for a legal definition of MSE and the incentives to provide legal support for its growth. Second, if a law to support the MSEs is established, it could provide a powerful inducement for the SSE to grow as a MSE, rather than stay as a SSE. Third, there is a need for a strategy of MSEs to establish a stable base in the domestic market and then advance to the global market with the accumulated trial and error and competitiveness. Fourth, the SSE themselves need the spirit of entrepreneurship in order to make the leap to a MSE. Because if nothing is to be changed about the system on the firms that grew, and the parts of the past custom was left to be managed alone, confusion and absence of management can take place. No matter how much tax favors the government will give and no matter how much incentive there could be through the policies, there are limits for industries to higher the ability to propagate. And because of that it is a period where industries need their own innovative skills to reform their firms.