• Management Science and Financial Engineering
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• 제13권2호
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• pp.79-97
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• 2007

This paper investigates the relationship of service quality and user satisfaction in the wired and mobile Internet services based on the integrative framework of both systems. Given a moderate level of reliability and validity, the commonly driven dimensions for measuring service quality include responsiveness, assurance, empathy, convenience, usefulness, and diversity. User satisfaction is measurable by the dimensions of communication/entertainment, finance/economics, location/geography, and information/consulting. We apply the MANOVA tests to evaluate whether each of the service quality dimensions has an overall influence on user satisfaction. Next, multiple regression analyses are conducted to check if unique positive effect exists between each combination of service quality dimensions and user satisfaction dimensions. The results show that service quality must be taken care of with respect to the assurance dimension in order to enhance customer satisfaction in the dimensions of location/geography, which will contribute to increasing the utilization of mobile service. For improving user satisfaction in the dimension of information/consulting, service quality must be supported with respect to assurance and empathy in the mobile Internet market, in addition to diversity, which is the only significant service quality in the wired Internet service.

• International Journal of Contents
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• 제13권1호
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• pp.38-44
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• 2017

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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• pp.287-294
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• 2016

Purpose: Environment test support is urgent for small and medium defense companies in order to improve the reliability of weapons systems. Also, to reduce the burden of test costs, the voucher system must be strengthened. Quality assurance support should be accompanied by budget support. Methods: First of all, it is necessary to expand infrastructure for test equipment that suffers shortages by considering environmental test frequency and waiting periods to reduce the time required for environmental tests. Results: In regard to the environmental test, expansion for test equipment infrastructure, security of budget for the test, establishment of test plan, education and consulting support are required to resolve some limits of small and medium defense companies. Conclusion: Along with the opening of environmental test courses for industry operators, the expansion for consulting support projects of the defense industry support system is needed.

• 디지털융복합연구
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• 제14권3호
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• pp.83-94
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• 2016

본 연구는 중소기업의 기술이전에 영향을 미치는 결정인자가 무엇인지를 분석하여 중소기업의 융복합 경영 전략을 수립하기 위한 기초자료를 제공하기 위한 것이 목적이다. 중소기업을 대상으로 한 2008년부터 2012년까지 기술이전 사례를 지식재산거래정보시스템 등에서 기술거래 데이터를 수집하여 중소기업 기술이전의 결정요인을 로지스틱 회귀분석을 통해 분석하였으며 그 연구결과는 다음과 같다. 첫째, 중소기업 기술이전의 경우 해당 기술 발명자의 수가 많을수록 기술이전의 성공에 긍정적인 영향을 미치는 것으로 나타났고 둘째, 해당 기술의 청구항의 수가 많아질수록 기술이전의 성공률이 제고되었고 셋째, 해당 기술에 대한 피인용문헌의 수가 많을수록 중소기업의 기술이전 성과와 정의 관계가 있는 것으로 나타났다.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.1129-1138
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• 2021

SMEs are constantly demanded of changes in the rapidly-evolving business environment, which involves the fourth industrial revolution and the COVID-19 pandemic. In this period, management consulting service becomes more in demand to provide technical and strategic solutions for management problems. This study aimed to empirically analyze the direct effects of emotional intelligence on job satisfaction and the indirect effects of such parameters as learning agility and self-efficacy on job satisfaction in management consultants. On the basis of a literature review, inter-variable association was designed in the research model. Based on an online survey of those in the Korean SME management consultants, this study collected 221 questionnaires then used structural equation modeling for statistical analysis. The results reveal that emotional intelligence significantly affected job satisfaction and, also significantly positively affected learning agility and self-efficacy. In addition, a significant indirect correlation could be found between learning agility and self-efficacy. Meanwhile, if learning agility and self-efficacy mediated job satisfaction, emotional intelligence had no significant effect on job satisfaction and fully mediated learning agility and self-efficacy. It is necessary to develop an emotional intelligence education program that can help management consultants improve their emotional intelligence with the objective of giving successful management consulting services.

• 산업경영시스템학회지
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• 제45권4호
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• pp.86-98
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• 2022

Recently, many studies have been conducted to improve quality by applying machine learning models to semiconductor manufacturing process data. However, in the semiconductor manufacturing process, the ratio of good products is much higher than that of defective products, so the problem of data imbalance is serious in terms of machine learning. In addition, since the number of features of data used in machine learning is very large, it is very important to perform machine learning by extracting only important features from among them to increase accuracy and utilization. This study proposes an anomaly detection methodology that can learn excellently despite data imbalance and high-dimensional characteristics of semiconductor process data. The anomaly detection methodology applies the LIME algorithm after applying the SMOTE method and the RFECV method. The proposed methodology analyzes the classification result of the anomaly classification model, detects the cause of the anomaly, and derives a semiconductor process requiring action. The proposed methodology confirmed applicability and feasibility through application of cases.

• 한국분말재료학회지
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• 제21권2호
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• pp.147-154
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• 2014

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2008년도 Asian Magnetics Conference
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• pp.241.2-241.2
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• 2008

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2008년도 Asian Magnetics Conference
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• pp.242.1-242.1
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• 2008

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.216-222
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• 2020

This research evaluated the construction market and project environment of nine nations within the ASEAN members. Quantitative data from global consulting firms and international organizations were identified and normalized for evaluation. The result of the analysis was that Indonesia was ranked highest for construction market growth while Singapore was ranked highest for stability of project environment. The research results can be utilized by construction companies that are planning on entering the construction market within the ASEAN members.