• 한국중재학회지:중재연구
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• 제28권2호
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• pp.179-200
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• 2018

The purpose of this study is to investigate the effects of service training and arbitration support on superstore workers' work performance. The conclusion could be summarized as follows. First, as a result of Hypothesis 1 that service training and arbitration support for superstore workers would significantly affect the factor of workers' emotional labor, when surface acting of emotion and frequency of expressing emotions were the dependent variable, only arbitration support was positively correlated. When emotional diversity was the dependent variable, there was a significantly positive relationship with service training. Second, for Hypothesis 2 that service training and arbitration support for superstore workers would significantly influence the workers' job satisfaction, it was found that only organizational support was significantly positive when wage satisfaction was the dependent variable. When job satisfaction was the dependent variable, service training and arbitration support were significantly correlated positively. Third, for Hypothesis 3 that service training and arbitration support for superstore workers would significantly affect the service delivery level when service responsiveness was the dependent variable, service training and arbitration support were significantly positive. When service expertise was the dependent variable, there was also a significantly positive relationship with service training and arbitration. On the other hand, all the three independent variables-service training, organizational support, and arbitration support-showed a significantly positive relationship when the willingness and effort of service was the dependent variable.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.235-248
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• 2024

The performance of informatization differs depending on its utilization, investment and construction methods. This study analyzed the key factors affecting the performance of informatization based on a public survey on the information system operation of small and medium-sized companies in Korea. Through structural equation modeling and one-way ANOVA, the study identified the pathways leading to performance. As a result of the analysis, it was confirmed that higher levels of top management support are associated with increased information system use and performance. Similarly, higher levels of information system use are correlated with better performance of information systems. This research is significant as it investigates and reveals how top management support and information system usage work in the cases of SMEs in South Korea, which is a leading country in manufacturing. The findings of this study will provide valuable insights for SMEs, whether they have already developed an information system or plan to do so, in their efforts to enhance corporate competitiveness.

• 한국직업건강간호학회지
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• 제32권4호
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• pp.185-194
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• 2023

Purpose: This study aimed to prepare basic data for the development of a nursing intervention program to improve nursing performance by identifying the factors affecting nursing performance in an integrated nursing care service ward. Methods: Participants were 166 nurses who had worked for more than six months in the integrated nursing care service wards of three general hospitals located in B city. Data were collected from July 15 to August 30, 2022 using structured questionnaires and analyzed by T-test, ANOVA, Scheffé test, Pearson's correlation coefficients and multiple linear regression using the IBM SPSS/WIN 25.0 statistical program. Results: Factors affecting the nursing performance of participants were age (β=.58, p<.001), positive psychological capital (β=.41, p<.001), and social support (β=.28, p<.001). The total explanatory power of these variables for nursing performance was 55.8%. Conclusion: The results of this study suggest the need for programs that improve psychological capital and social support while considering nurse's age to enhance their performance in nursing integrated service wards.

• 벤처창업연구
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• 제18권6호
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• pp.105-116
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• 2023

중소벤처기업에 대한 자금지원 등 정책지원이 기업성과에 미치는 영향에 관한 연구는 많이 있으나 정책지원에 대한 기업가의 인식이 기업성과에 미치는 영향에 관한 연구는 별로 없다. 또한, 기업가적 목표를 달성하고 지속하는 데 중요한 영향을 미치는 기업가 끈기(entrepreneurial persistence)와 기업성과에 관한 국내 연구도 거의 없는 실정이다. 따라서 본 연구의 목적은 정책지원에 대한 기업가의 인식이 기업성과에 미치는 영향과 기업가 끈기의 매개효과를 분석함으로써 인식의 중요성을 밝히고, 기업가 끈기에 관한 연구를 심화하는데 있다. 본 연구는 우리나라 중소벤처기업 정책지원에 대한 기업가의 인식 및 기업가정신을 독립변수로 구성하였으며, 기업가 끈기를 매개 변수로, 기업의 비재무적 성과를 종속변수로 사용하였다. 연구자료는 중소벤처기업의 CEO 및 임원들을 대상으로 한 설문지를 통해 수집하였으며, 설문 응답이 누락 되거나 불성실한 설문지를 제외하고 205부의 설문자료를 가설검증에 사용하였다. 본 연구의 결과는 다음과 같다. 첫째, 중소벤처기업 정책지원의 인식 및 기업가정신은 기업성과에 유의한 정(+)의 영향이 있는 것으로 검증되었다. 둘째, 기업가 끈기는 중소벤처기업 정책지원의 인식 및 기업가정신과 기업성과 간의 관계에 있어서 부분 매개 하는 것으로 검증되었다. 본 연구의 이론적 시사점은 다음과 같다. 첫째, 기존 연구는 정책자금지원이 기업성과에 미치는 영향에 관한 연구인 데 비하여, 본 연구는 이에 대한 기업가들의 인식이 기업성과에 정(+)의 영향을 미친다는 것을 검증함으로써 국내에는 선행연구가 거의 없는 인식과 성과와의 관계 그리고, 인식에 대한 중요성을 밝혔다는 점에서 이론적 기여를 한다. 둘째, 국내 선행연구가 별로 없는 기업가 끈기를 매개변수로 활용하여 기업가 끈기가 중소벤처기업 정책지원의 인식 및 기업가정신과 기업성과 간의 관계를 매개한다는 점을 검증함으로써 기업가 끈기의 중요성을 밝히고 그에 관한 연구를 확장했다는 점에서 이론적으로 기여한다. 본 연구의 실무적인 시사점은 중소벤처기업의 성과를 확대하기 위해서는 정책당국은 예산 및 지원제도 등 정책지원의 확대뿐만 아니라 그러한 정책지원을 기업가에게 홍보하고 공지하는 시스템적인 접근 등을 통해서 기업가의 인식을 제고해야 한다는 점이다.

• 한국IT서비스학회지
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• 제10권2호
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• pp.235-245
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• 2011

Early criticality prediction models that determine whether a design entity is fault-prone or not are becoming more and more important as software development projects are getting larger. Effective predictions can reduce the system development cost and improve software quality by identifying trouble-spots at early phases and proper allocation of effort and resources. Many prediction models have been proposed using statistical and machine learning methods. This paper builds a prediction model using Support Vector Machine(SVM) which is one of the most popular modern classification methods and compares its prediction performance with a well-known prediction model, BackPropagation neural network Model(BPM). SVM is known to generalize well even in high dimensional spaces under small training data conditions. In prediction performance evaluation experiments, dimensionality reduction techniques for data set are not used because the dimension of input data is too small. Experimental results show that the prediction performance of SVM model is slightly better than that of BPM and polynomial kernel function achieves better performance than other SVM kernel functions.

• 유통과학연구
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• 제13권10호
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• pp.5-13
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• 2015

Purpose - This study aims to suggest appropriate policies and performance indicators for financial aid recipients. It analyzes the existing regular government policy funds support project, especially its propriety and reasonability. Research design, data, and methodology - When financial aid is effective, it should be able to predict small enterprise business results. Additionally, there should be an evaluation, checking before and after performance rates so that the rate of achievement and outcome can be measured. This study's contribution for small enterprises is in researching the best way to improve this support system. Results - The Small Enterprise and Market Service (SEMAS), currently designated as a support organization for implementing the government financial aid project, has assessment indicators. However, these focus mainly on quantitative indicators and survey results. Conclusions - In the future, there is some need to draw up measures, setting the right direction for developing policies for the small enterprise fund loans and improving the management of the plans. Eventually, this effort will dispel concerns about the present support policy, which is considered to be weakening small enterprises.

• East Asian mathematical journal
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• 제37권3호
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• pp.333-354
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• 2021

A support vector machine (SVM) is a state-of-the-art machine learning model rooted in structural risk minimization. SVM is underestimated with regards to its application to real world problems because of the difficulties associated with its use. We aim at showing that the performance of SVM highly depends on which kernel function to use. To achieve these, after providing a summary of support vector machines and kernel function, we constructed experiments with various benchmark datasets to compare the performance of various kernel functions. For evaluating the performance of SVM, the F1-score and its Standard Deviation with 10-cross validation was used. Furthermore, we used taylor diagrams to reveal the difference between kernels. Finally, we provided Python codes for all our experiments to enable re-implementation of the experiments.

• Journal of the Korean Data and Information Science Society
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• 제25권2호
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• pp.455-464
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• 2014

Unlabeled examples are easier and less expensive to obtain than labeled examples. Semisupervised approaches are used to utilize such examples in an eort to boost the predictive performance. This paper proposes a novel semisupervised classication method named transductive least squares support vector machine (TLS-SVM), which is based on the least squares support vector machine. The proposed method utilizes the dierence convex algorithm to derive nonconvex minimization solutions for the TLS-SVM. A generalized cross validation method is also developed to choose the hyperparameters that aect the performance of the TLS-SVM. The experimental results conrm the successful performance of the proposed TLS-SVM.

• 재활간호학회지
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• 제3권1호
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• pp.5-14
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• 2000

Stroke patients have increased with the overall aging of our population, 60 years and older. Recently the number of stroke patients has been on the increase even among younger people in their thirties. The family support is frequently mentioned as a major variable which plays an important role in helping the patients adapt themselves to their hemiplegic situations. The purpose of the study was to examine between family support and activities of daily living(ADLs)abilities for the hemiplegic patients, and to provide the basic data to help the patients carry out their ADLs on their own. The sample for the study included 106 hemiplegic patients and their family members. The data were collected using a focused, structured interviews. The major findings of the study were as follows: 1. The hemiplegic patients perceived that their family supports were very high(Mean, 49.00). 2. The degree of family support was significantly higher in female. high economic status, and non-use of brace patients than in male, poor economic status, use of brace patients. 3. The ADL abilities of the hemiplegic patients were significantly higher in ambulatory, younger, and longer-period-of-illness patients and patients who used a cane as a assistive device. 4. The family support for the hemiplegic patients showed a statistically significant Cor relationship with their performance of ADL(r=.30809. p=0.0013). 5. The performance of ADL for the ambulatory patients were mainly affected by the degree of family support, the period of the hemiplegic illness, the use of brace, informal care giving, and the age. These variables explained 50% of variance. 6. The length of illness was a statistically significant affecting variable for ADL performance in OPD and assistive device in IPD. In conclusion, the higher the hemiplegic patients perceived the degree of family support, the better they performed ADL. We should develop nursing methods which enhance the family support for the hemiplegic patients in order to increase their performance of ADL.

• Communications for Statistical Applications and Methods
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• 제19권4호
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• pp.517-526
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• 2012

In this paper a support vector method is proposed for use when the sample observations are contaminated by a normally distributed measurement error. The performance of deconvolution density estimators based on the support vector method is explored and compared with kernel density estimators by means of a simulation study. An interesting result was that for the estimation of kurtotic density, the support vector deconvolution estimator with a Gaussian kernel showed a better performance than the classical deconvolution kernel estimator.