• 지식경영연구
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• 제15권4호
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• pp.57-78
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• 2014

Since team performance has become one of the core factors for companies' success, companies are putting every effort to raise team productivity. In this vein, the purpose of this study was to examine the influence of team learning behavior upon team dynamic capabilities, team effectiveness, and to verify the mediating effect of team dynamic capabilities in corporations. 312 employees were randomly selected to participate in an questionnaire survey. The result has shown that the static correlation exists between team learning behavior, team dynamic capabilities, and team effectiveness. Team dynamic capabilities mediated the relationship between team learning behavior and team effectiveness. Based on the findings, the study implies that learning behaviors among team members should be supported in order to improve its outcome, and HR representatives must help to develop dynamic capabilities.

• 한국경영과학회지
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• 제26권1호
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• pp.61-69
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• 2001

This paper presents a two stage game model which examines the effect of learning-by-doing and spillover. Increases in the firm’s cumulative experience lower its unit cost in future period. However, the firm’s rival also enjoys the experience via spillover. Unlike previous theoretical research model, a cost asymmetric market entry game model is developed between the incumbent firm and new entrant. Mathematical results show that the incumbent firm exploits the learning curve to gain future cost advantage, and that the diffusion of learning to the new entrant induces the incumbent firm to choose decreasing output strategically. As a main result, we show that the relative magnitude between the learning and spillover rate determines the market share ratio of competing firms.

• 대한안전경영과학회지
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• 제16권2호
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• pp.175-184
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• 2014

This paper examines how learning orientation and self-efficacy contributed to explaining innovation behaviors. In order to verify the relationships and mediating effect, data were collected from 368 individuals in employees working in small and medium-sized firms at Gyeongnam region to test theoretical model and its hypotheses. All data collected from the survey were analyzed using with SPSS 18.0. This study reports findings as follows: first, the relationship between the learning orientation and the employee's self-efficacy is positively related. Second, there was also a positive correlation between the employee's self-efficacy and the innovation behaviors. Third, the relationship between the learning orientation and the innovation behaviors is positively related. Finally, the employee's self-efficacy played as a partial mediator on the relationship between learning orientation and innovation behaviors. Based on these findings, the implications and the limitations of the study were presented including some directions for future studies.

• Journal of Information Technology Applications and Management
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• 제28권4호
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• pp.33-43
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• 2021

While youth unemployment has recorded the lowest level since the global COVID-19 pandemic, SMEs(small and medium sized enterprises) are still struggling to fill vacancies. It is difficult for SMEs to find good candidates as well as for job seekers to find appropriate job offers due to information mismatch. To overcome information mismatch, this study proposes the fine-turning model for bidirectional HR matching based on a pre-learning language model called BERT(Bidirectional Encoder Representations from Transformers). The proposed model is capable to recommend job openings suitable for the applicant, or applicants appropriate for the job through sufficient pre-learning of terms including technical jargons. The results of the experiment demonstrate the superior performance of our model in terms of precision, recall, and f1-score compared to the existing content-based metric learning model. This study provides insights for developing practical models for job recommendations and offers suggestions for future research.

• Asia Marketing Journal
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• 제11권2호
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• pp.37-51
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• 2009

Although previous studies have made significant progress in adaptive selling behavior (ASB), few studies have considered salesperson's customer orientation (CO) and learning behavior as determinants of effective sales management (ASB and relationship-making efforts), despite the discussion of important roles of these constructs. The authors test not only the relationships of salesperson's CO and market-based learning behavior to ASB and relationship-making efforts, but also the effects of ASB on relationship-making efforts and performance. The results of the study, which is done with samples of salespeople from Korean companies, indicate that salesperson's CO and market-based learning behavior are identified as significant determinants of ASB. Moreover, both salesperson's ASB and relationship-making efforts have significant effects on sales performance. On the other hand, as per salesperson's relationship-making efforts, salesperson's CO has a positive effect, but salesperson's market-based learning behavior and ASB do not influence his or her relationship-making efforts, which suggest a provocative possibility of conceptualization regarding the relationship between ASB and relationship management efforts.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2005년도 춘계학술대회
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• pp.265-276
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• 2005

정보 통신 기술은 비즈니스를 변화시켰고, 이제 교육에도 영향을 미치고 있다. e-Learning으로 대변되는 교육의 변화는 교육의 패러다임을 변화시키고 있다. e-Learning은 현재 정부차원에서 적극적인 지원을 하고 있는 상태이고, 시장 규모 및 성장 가능성이 매우 높다. 그러나 아직 시장이 성숙되어 있지 않고 기업환경이 불확실하기 때문에 e-Learning 시장 참여자들의 본격적인 투자 활동은 미진한 수준으로 보인다. 이에 본 연구는 e-Learning에 대한 특징을 살펴보고 국내외 산업 현황 및 정책 방향을 분석하여 e-Learning에 대한 현안과 문제점을 진단하고 발전 방향을 제시하고자 한다.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2006년도 추계학술대회
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• pp.433-445
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• 2006

본 연구는 e-Learning이 오프라인 교육으로 대변되는 기존의 전통적인 교육 매체를 대체할 가능성 내지는 오프라인 교육과의 상호 보완적인 역할 가능성에 대해 연구함으로써 e-Learning 산업의구체적인 발전 방향을 찾아보고 이에 따른 향후 성장 가능성을 살펴보기 위하여 , 기존의 전통적인교육 매체 수용자의 특성과는 다른 양상을 나타낼 e-Learning 이용자의 특성에 대해 연구해 보고자한다. 이를 위해 e-Learning을 교육 매체로서 선택하는 대학생들을 대상으로 e-Learning을 이용하는 동기와 e-Learning 이용 행태, 그리고 e-Learning 이용에 따른 만족도를 살펴보고자 한다.

• 컴퓨터교육학회논문지
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• 제8권5호
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• pp.73-83
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• 2005

현재 초등학생들의 인터넷 이용률은 급격히 증가하고 있는 반면, 아이디와 비밀번호를 무분별하게 관리하고 있으며, 그에 따른 정보 유출의 심각성을 전혀 인식하지 못하고 있다. 본 논문에서는 초등학생 대상으로 개인정보 관리의 중요성을 인식시키기 위한 교수학습 방법을 설계하였다. 설계한 교수학습 방법은 역할놀이 모형을 기반으로 하였으며 초등학교 3학년을 대상으로 현장 수업에 적용하였다. 수업한 결과를 분석하여 설계한 교수학습 방법이 기존의 강의법보다 더 효과가 있음을 보인다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권1호
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• pp.44-51
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• 2016

Recently, artificial intelligence has reached the level of top information technologies that will have significant influence over many aspects of our future lifestyles. In particular, in the fields of machine learning technologies for classification and decision-making, there have been a lot of research efforts for solving estimation and control problems that appear in the various kinds of portfolio management problems via data-driven approaches. Note that these modern data-driven approaches, which try to find solutions to the problems based on relevant empirical data rather than mathematical analyses, are useful particularly in practical application domains. In this paper, we consider some applications of modern data-driven machine learning methods for portfolio management problems. More precisely, we apply a simplified version of the sparse Gaussian process (GP) classification method for classifying users' sensitivity with respect to financial risk, and then present two portfolio management issues in which the GP application results can be useful. Experimental results show that the GP applications work well in handling simulated data sets.

• 한국수산과학회지
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• 제54권4호
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• pp.489-497
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• 2021

Climate change is affecting the evolutionary trajectories of individual species and ecological communities, partly through the creation of new species groups. As population shift geographically and temporally as a result of climate change, reproductive interactions between previously isolated species are inevitable and it could potentially lead to invasion, speciation, or even extinction. Four species of abalone, genus Haliotis are present along the Korean coastline and these species are important for commercial and fisheries resources management. In this study, genetic markers for fisheries resources management were discovered based on genomic information, as part of the management of endemic species in response to climate change. Two thousand one hundred and sixty one single nucleotide polymorphisms (SNPs) were discovered using genotyping-by-sequencing (GBS) method. Forty-one SNPs were selected based on their features for species classification. Machine learning analysis using these SNPs makes it possible to differentiate four Haliotis species and hybrids. In conclusion, the proposed machine learning method has potentials for species classification of the genus Haliotis. Our results will provide valuable data for biodiversity conservation and management of abalone population in Korea.