• Title/Summary/Keyword: binomial data

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Quality of Life and Its Related Factors Among Metropolitan-dwelling Older Adults (도시지역 재택 고령자의 삶의 질(Quality of Life) 및 관련요인)

  • Ham, Seok-Pil;Kim, Beom-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.411-422
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    • 2021
  • The purpose of this study is to examine the relationships between quality of life and demographic characteristics and health-related behavioral characteristics, and their relevance to variables that represent health conditions among metropolitan-dwelling older adults. The study subjects were 380 senior citizens aged 65 or older living in the D metropolitan area, and data collection was conducted by visiting them for interviews in June 2019. A binomial logistic regression analysis was performed to examine the relationship between independent variables (demographic characteristics, health-related behavioral characteristics, health condition variables) and the dependent variable (quality of life) while controlling for gender and age. As a result, the factors related to quality of life for those surveyed were education level, spousal status, living status, bear for living expenses, average monthly allowance, satisfaction with daily life, evaluation of sleep quality, smoking and eating habits, amount of regular exercise, hobbies, subjective health status, physical disability (if any), hearing ability, visual acuity, mastication ability, urinary incontinence (present or not), and amnesia. The above results suggest that quality of life for the elderly living in urban areas is significantly related to variables that indicate demographic characteristics, health-related behavioral characteristics, and health condition.

A Study of Film Crews' Needs to Participate in Overseas Production : On the Basis of Binary Logistics Analysis and Marginal Effect Method (영화제작인력들의 해외활동 참여욕구에 관한 연구 : 이분형 로지스틱 분석 및 한계효과분석을 중심으로)

  • Lee, Hee-Jin
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.4
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    • pp.27-37
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    • 2019
  • This study empirically identified and sought implications for the degree of desire by film crews to participate in overseas production and the factors affecting them, based on the recognition that the active participation of skilled film crews in overseas production and joint ventures can be an alternative to the poor treatment of domestic film industry sites and the reduction of job losses due to problems with career barriers. In order for respondents to verify research questions, binomial logistic and marginal effects analysis using SPSS and STATA, the data obtained by surveying 402 film crews operating in various areas. The notable findings are as follow: First, about 65%(263 people) of the respondents expressed their desire to participate in overseas activity, indicating that a considerable number of film crews are looking forward to opportunities with overseas productions. Second, major factors that have a positive effect on film crews' need to participate in overseas activities have been found to be professionality, artistic identity, Korean Wave persistence, and career barriers. In other words, the higher the professionality, the more clearly the identity of the artist, the more positive expectations of the possibility of the Korean Wave continuing, and the more serious the problem of career disability, the clearer was the desire to participate in overseas production and joint-work activities.

Patent Production and Technological Performance of Korean Firms: The Role of Corporate Innovation Strategies (특허생산과 기술성과: 기업 혁신전략의 역할)

  • Lee, Jukwan;Jung, Jin Hwa
    • Journal of Technology Innovation
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    • v.22 no.1
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    • pp.149-175
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    • 2014
  • This study analyzed the effect of corporate innovation strategies on patent production and ultimately on technological change and new product development of firms in South Korea. The intent was to derive efficient strategies for enhancing technological performance of the firms. For the empirical analysis, three sources of data were combined: four waves of the Human Capital Corporate Panel Survey (HCCP) data collected by the Korea Research Institute for Vocational Education and Training (KRIVET), corporate financial data obtained from the Korea Information Service (KIS), and corporate patent data provided by the Korean Intellectual Property Office (KIPO). The patent production function was estimated by zero-inflated negative binomial (ZINB) regression. The technological performance function was estimated by two-stage regression, taking into account the endogeneity of patent production. An ordered logit model was applied for the second stage regression. Empirical results confirmed the critical role of corporate innovation strategies in patent production and in facilitating technological change and new product development of the firms. In patent production, the firms' R&D investment and human resources were key determinants. Higher R&D intensity led to more patents, yet with decreasing marginal productivity. A larger stock of registered patents also led to a larger flow of new patent production. Firms were more prolific in patent production when they had high-quality personnel, intensely investing in human resource development, and adopting market-leading or fast-follower strategy as compared to stability strategy. In technological performance, the firms' human resources played a key role in accelerating technological change and new product development. R&D intensity expedited new product development of the firm. Firms adopting market-leading or fast-follower strategy were at an advantage than those with stability strategy in technological performance. Firms prolific in patent production were also advanced in terms of technological change and new product development. However, the nexus between patent production and technological performance measures was substantially reduced when controlling for the endogeneity of patent production. These results suggest that firms need to strengthen the linkage between patent production and technological performance, and take strategies that address each firm's capacities and needs.

Development of a Failure Probability Model based on Operation Data of Thermal Piping Network in District Heating System (지역난방 열배관망 운영데이터 기반의 파손확률 모델 개발)

  • Kim, Hyoung Seok;Kim, Gye Beom;Kim, Lae Hyun
    • Korean Chemical Engineering Research
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    • v.55 no.3
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    • pp.322-331
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    • 2017
  • District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

A study on the prediction of korean NPL market return (한국 NPL시장 수익률 예측에 관한 연구)

  • Lee, Hyeon Su;Jeong, Seung Hwan;Oh, Kyong Joo
    • Journal of Intelligence and Information Systems
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    • v.25 no.2
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    • pp.123-139
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    • 2019
  • The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

A Study on the Impact of SNS Usage Characteristics, Characteristics of Loan Products, and Personal Characteristics on Credit Loan Repayment (SNS 사용특성, 대출특성, 개인특성이 신용대출 상환에 미치는 영향에 관한 연구)

  • Jeong, Wonhoon;Lee, Jaesoon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.5
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    • pp.77-90
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    • 2023
  • This study aims to investigate the potential of alternative credit assessment through Social Networking Sites (SNS) as a complementary tool to conventional loan review processes. It seeks to discern the impact of SNS usage characteristics and loan product attributes on credit loan repayment. To achieve this objective, we conducted a binomial logistic regression analysis examining the influence of SNS usage patterns, loan characteristics, and personal attributes on credit loan conditions, utilizing data from Company A's credit loan program, which integrates SNS data into its actual loan review processes. Our findings reveal several noteworthy insights. Firstly, with respect to profile photos that reflect users' personalities and individual characteristics, individuals who choose to upload photos directly connected to their personal lives, such as images of themselves, their private circles (e.g., family and friends), and photos depicting social activities like hobbies, which tend to be favored by individuals with extroverted tendencies, as well as character and humor-themed photos, which are typically favored by individuals with conscientious traits, demonstrate a higher propensity for diligently repaying credit loans. Conversely, the utilization of photos like landscapes or images concealing one's identity did not exhibit a statistically significant causal relationship with loan repayment. Furthermore, a positive correlation was observed between the extent of SNS usage and the likelihood of loan repayment. However, the level of SNS interaction did not exert a significant effect on the probability of loan repayment. This observation may be attributed to the passive nature of the interaction variable, which primarily involves expressing sympathy for other users' comments rather than generating original content. The study also unveiled the statistical significance of loan duration and the number of loans, representing key characteristics of loan portfolios, in influencing credit loan repayment. This underscores the importance of considering loan duration and the quantity of loans as crucial determinants in the design of microcredit products. Among the personal characteristic variables examined, only gender emerged as a significant factor. This implies that the loan program scrutinized in this analysis does not exhibit substantial discrimination based on age and credit scores, as its customer base predominantly consists of individuals in their twenties and thirties with low credit scores, who encounter challenges in securing loans from traditional financial institutions. This research stands out from prior studies by empirically exploring the relationship between SNS usage and credit loan repayment while incorporating variables not typically addressed in existing credit rating research, such as profile pictures. It underscores the significance of harnessing subjective, unstructured information from SNS for loan screening, offering the potential to mitigate the financial disadvantages faced by borrowers with low credit scores or those ensnared in short-term liquidity constraints due to limited credit history a group often referred to as "thin filers." By utilizing such information, these individuals can potentially reduce their credit costs, whereas they are supposed to accrue a more substantial financial history through credit transactions under conventional credit assessment system.

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Pulmonary Resection in the Treatment of Multidrug-Resistant Tuberculosis (다제 내성 폐결핵환자의 폐절제술에 관한 연구)

  • Kwon, Eun-Soo;Ha, Hyun-Cheol;Hwang, Su-Hee;Lee, Hung-Yol;Park, Seung-Kyu;Song, Sun-Dae
    • Tuberculosis and Respiratory Diseases
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    • v.45 no.6
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    • pp.1143-1153
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    • 1998
  • Background : Recent outbreaks of pulmonary disease due to drug-resistant strains of Mycobacterium Tuberculosis have resulted in significant morbidity and mortality in patients worldwide. We reviewed our experience to evaluate the effects of pulmonary resection on the management of multidrug-resistant tuberculosis. Method : A retrospective review was performed of 41 patients undergoing pulmonary resection for multidrug-resistant tuberculosis between January 1993 and December 1997. We divided these into 3 groups according to the radiologic findings : (1) patients who have reasonably localized lesion (Localized Lesion Group ; LLG) (2) patients who have cavitary lesions after pulmonary resection on chest roentgenogram (Remained Cavity Group : RCG) (3) patients who have Remained infiltrative lesions postoperatively (Remained infiltrative group : RIG). We evaluated the negative conversion rate after resection and overall response rate of the groups. Then they were compared with the results of the chemotherapy on the multi drug-resistant tuberculosis which has been outcome by Goble et al. Goble et al reported that negative conversion rate was 65% and overall response rate, 56% over a mean period of 5.1 months. Results : Seventy five point six percent were men and 24.4% women with a median age of 31 years (range, 16 to 60 years). Although the patients were treated preoperatively with multidrug regimens in an effort to reduce the mycobacterial burden, 22 of 41 were still sputum culture positive at the time of surgery. 20 of 22 patients(90.9%, p<0.01) responded which is defined as negative sputum cultures within 2 months postoperative. Of 26 patients with the sufficient follow up data, 19 have Remained sputum culture negative for a mean duration of 25.7 months (73.1%, p<0.05). The bulk of the disease was manifest in one lung, but lesser amounts of contralateral disease were demonstrated in 15, consisted of 8 in RIG and 7 in RCG, of 41. 12 of 12 patients (100%, p<0.01) who were sputum positive at the time of surgery in LLG converted successfully. 14 of 15 patients (93.3%, p<0.05) with the follow up have completed treatment and not relapsed for a mean period of 25. 7 months. The mean length of postoperative drug therapy of LLG was 12.2 months. In RIG, postoperative negative conversion rate was 83.3% which was not significant statistically. There was a statistical significance in overall response rate (100%, p<0.05) of RIG for a mean period of 24.4 months with a mean length of postoperative chemotherapy, 11.8 months. In RCG a statistically lower overall response rate (14.3%, p<0.01) has been revealed for a mean duration of follow up, 24.2 months. A negative conversion rate of RCG was 75% which was not significant statistically. Conclusion : Surgery plays an important role in the management of patients with multidrug-resistant Mycobacterium tuberculosis infection. Aggressive pulmonary resection should be performed for resistant Mycobacterium tuberculosis infection to avoid treatment failure or relapse. Especially all cavitary lesions on preoperative chest roentgenogram should be resected completely. If all of them could not be resected perfectly, you should not open the thorax.

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