• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.287-295
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• 2019

This study was conducted to analyze firm survival rate and impact factors of survival of Foreign-invested Companies in Korea which is between 2006 and 2017. An empirical analysis of the survival factors of firms used explanatory variables such as characteristics of the and 3 firm dummy and 2 firm factors, financial variables of 3 profitability and 3 stability factors. The Kaplan-Meier method was chosen to perform analyses on the survival rates, Cox Proportional Hazard Model took to conduct on the impact factors. As a result of the impact factors of Foreign-invested Companies survival, Ownership (OS), Labour (NE ) of characteristics of the firm had positive effects. The Gross Sales Profit (GSP), Net Profit (NP ) and Operating Profit (OP ) of the financial characteristics had a positive effect. Additional Asset (LA ) had positive effects and Capital (LC), Debt (LB ) had a negative effect. Other factors did not produce significant results.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.5
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• pp.63-72
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• 2018

The purpose of this study was to analyze the survival rate and survival characteristics of young start-up entrepreneurs supported with public financing, by using non-parametric statistic of Kaplanr-Meier Analysis on non-financial data. Average survival periods of different survival characteristics have been estimated by dividing the age groups into 20s and 30s. After then, the main variables affecting the survival period have been analyzed. 3,825 firms guaranteed by Credit Guarantee Institutions in Korea were used as database for the analysis. 3,242 firms have survived while 583 firms have gone insolvent. The study period was from January 1, 2011 to December 31, 2017. Age-based breakdown of the business founders show that 3 variables in the 20s and 5 variables in the 30s are derived as the significant variables, resulting in the significant differences of each age group. In other words, the start-up support agencies and financial institutions need to develop a credit evaluation system that distinguishes the criteria of age range and find information that reflect the characteristics of entrepreneurs in their 20s as well as developing tailor-made financial products. Also, step-by-step support measures are required for the start-ups of high survival times and make them grow into promising SMEs. Meanwhile, non-financial support plans shall be invigorated along with the financial ones to help the start-ups of low survival times. This study is meaningful in that the survival analysis has been conducted by using the non-financial data of young start-up entrepreneurs. It is expected that the results of this analysis contribute to the enhancement of survival rate of start-ups by providing start-up support agencies and start-up business owners with the unique information of the survival characteristics.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1095-1106
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• 2014

Symbolic data analysis extends the data mining and exploratory data analysis to the knowledge mining, we can suggest the SDA tree model on clinical and genomic data with new knowledge mining SDA approach. Using SDA application for huge genomic SNP data, we can get the correlation the availability of understanding of hidden structure of HCC data could be proved. We can confirm validity of application of SDA to the tree structured progression model and to quantify the clinical lab data and SNP data for early diagnosis of HCC. Our proposed model constructs the representative model for HCC survival time and causal association with their SNP gene data. To fit the simple and easy interpretation tree structured survival model which could reduced from huge clinical and genomic data under the new statistical theory of knowledge mining with SDA.

• Industry Promotion Research
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• v.7 no.1
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• pp.1-8
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• 2022

We investigated various types of machine learning methods that can be applied to censored data. Exploratory data analysis reveals the distribution of each feature, relationships among features. Next, classification problem has been set up where the dependent variable is death_event while the rest of the features are independent variables. After applying various machine learning methods to the data, it has been found that just like many other reports from the artificial intelligence arena random forest performs better than logistic regression. But recently well performed artificial neural network and gradient boost do not perform as expected due to the lack of data. Finally Kaplan-Meier and Cox proportional hazard model have been employed to explore the relationship of the dependent variable (t_i, δ_i) with the independent variables. Also random forest which is used in machine learning has been applied to the survival analysis with censored data.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.27-40
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• 2023

This study analyzes the factors affecting the survival of young start-up companies. A youth start-up company was defined as a company with a founder's age under 39. The study was based on evaluation data from 3,540 companies evaluated by the Technology Guarantee Fund to support youth start-up guarantees during the period from 2012 to 2015. In this study, independent variables were defined as founder characteristics, start-up environment, and start-up strategy, and entrepreneurship, knowledge level, and development capabilities were set as variables for start-up characteristics, competition conditions and comparative advantage with alternatives in the start-up environment, and item novelty, commercialization plan and financing plan were set as variables. For variable measurement, the evaluation index of the youth start-up evaluation model of the Technology Guarantee Fund was used. Management performance was defined as the survival of a company, and the survival of 12, 36, 60, and 84 months was measured based on the occurrence of insolvency registered by the Korea Technology Guarantee Fund. The Cox proportional risk model was used for hypothesis testing. As a result of the analysis, knowledge level and development capability were statistically significant in the characteristics of the founder, and the financing plan in the start-up strategy was statistically significant regardless of the survival period. Among the start-up strategies, the novelty of the item had a positive effect on survival after 36 months. Entrepreneurship was significant only in 12-month survival. The most important order for survival was identified in the order of financing plan, knowledge level, item novelty and development capability, of which the founder's knowledge level in the beginning and the funding plan in the second half had the greatest impact.

• KSBB Journal
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• v.13 no.3
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• pp.251-258
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• 1998

A structured kinetic model is proposed to describe cell growth and secondary metabolite, flavone glycosides, synthesis in batch suspension culture of Scutellaria baicalensis G. The model has been developed by representing the physiological state of cell described as the activity and viability which can be estimated based on the culture fluorescence. In the model, three type of cells are considered; active-viable, nonactive-viable and dead cells. Viable cell weight could be determined based on the relative fluorescence intensity. The flavone glycosides could be produced by both active-viable and non-active viable cells with a different production rate. And the model includes the cell expansion due to glucose concentration and death phase which accounts for the release of intracellular secondary metabolite into medium. Dependent variables include substrate concentration(glucose), cell mass(dry cell weight and fresh cell weight), product concentration(flavone glycosides), activity and viability. Satisfactory agreement between the model and experimental data is obtained from shake flask culture of Scutellaria baicalensis G. The proposed model can predict the cell growth and flavone glycosides synthesis as well as intermediate materials.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.325-333
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• 1999

경북대학교병원에서 1985년에서 1994년까지 위암 때문에 위 절제수술을 받은 1,192명의 환자에 대한 자료를 이용하여 5년 생존율에 관해 분석하고자 한다. 일반적으로 위암 진단을 받은 환자가 수술을 받으려고 할 때 또는 수술을 직후에, 환자의 임상적 특성들을 이용하여 수술후 생존시간과 수술후 5년 생존 여부는 큰 의미가 있다. 그러나 많은 경우에 있어서 실제 임상자료는 연구가 진행 중에 있으므로 생존시간이 우측 중도절단된 형태로 관측되어 기존의 판별분석과 로짓분석을 적용할 수 없다. 본 논문에서는 Buckley와 James가 제안한 의사확률변수를 이용하여 수술전과 수술직후, 두 시점에서 중도절단된 자료를 보완하고, 판별분석과 로짓분석을 통하여 수술전과 수술직후에 환자들의 각 특성이 5년 생존여부에 미치는 영향을 분석을 한다.

• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.803-806
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• 2010

저고용을 통한 고효율로 기업생산성을 추구하는 결과, 야기되는 고용의 불균형을 타개하기 위해 2007년 정부는 사회적 기업 육성법을 통해 사회적 기업을 장려하고 있다. 뿐 만 아니라 전 세계적 으로도 사회적 기업에 관련된 연구를 미국의 로버츠 재단, 영국의 Social Firms, EMES European Research Network 등이 중심이 되어 사회적 기업의 생존 전략과 사회적 자본 활용을 통한 발전방법을 모색하고 있다. 본 연구는 이러한 세계적인 추세에 발맞추어 사회적 기업 발전에 필요한 기업생존, 고용증대, 매출증대, 권한위임을 종속변수로 Granovetter Mark, Burt Ronald, Coleman James, Peter Witt, Andreas Schroeter, Christin Merz, Helen Haugh 등의 연구를 참고하여 독립변수인 네트워크다양성과 강도가 어떻게 작용하는지를 먼저 실증 분석하고 나아가 네트워크의 효율적인 운영을 통하여 사회적 기업 발전을 극대화시키는데 연구목적이 있다. 그리고 본연구의 대상은 2009년 현재 국내의 295개 사회적 기업 가운데 전문가의 추천을 받은 25개 회사로 이루어졌으며 SPSS 12.0으로 요인분석, 타당성, 신뢰성, 상관관계 등의 분석을 거쳐 다중회귀분석을 통하여 가설을 검증하였다. 검증의 결과 기업생존, 고용증대, 매출증대, 권한위임 전 과정에 네트워크가 필요하며 특히, 기업생존을 위해서는 네트워크강도에 관련된 요인을 매출증대를 위해서는 네트워크다양성에 관련된 요인을 잘 관리하고 유지 발전시켜야 함을 알 수 있었다. 끝으로 본 연구의 결과가 사회적 기업 창업을 준비 중인 국내의 많은 회사나 비영리법인, 사회단체가 계속기업으로 발전해 가기위한 사회적 자본 활용 전략에 많은 도움을 줄 수 있을 것으로 생각한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.11
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• pp.883-890
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• 2013

Aircraft combat survivability analysis is essential process for the development of combat aircraft. M&S methodology is the typical procedure for the aircraft combat survivability analysis, and the last step is the expensive Live Fire Test if it is necessary. This study introduced cost and time effective survivability analysis methodology based on the random variable weighted score algorithm in conceptual design phase. For this study, essential element and event analysis (E3A) is used to define the random variables and Monte-Carlo simulation is implemented to estimate weighted score and the final value of survivability.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.411-425
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• 2021

Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.