• 경영과학
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• 제32권2호
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• pp.15-35
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• 2015

Large business groups typically have central firms through which their controlling families establish (or acquire) new firms and maintain control over other member firms. Research on corporate governance has developed metrics to identify those central firms and investigated an impact of the centrality on ownership structure and firm's financial performance. This paper introduces centrality metrics used in social network analysis (SNA) to measure how crucial a role each firm plays in the ownership structure of its business group. Then, the SNA centrality metrics are compared with the metrics developed in corporate governance field. Also, we test the relationship between the SNA centrality metrics and firm's value. Experimental results show that the SNA centrality metrics are closely correlated with the centrality metrics used in corporate governance and are significantly correlated with firm's value.

• 대한산업공학회지
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• 제33권1호
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• pp.11-25
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• 2007

Despite surging interests in analyzing business processes, there are few scientific approaches to analysis and redesign of organizational structures which can greatly affect the performance of business processes. This paper presents a method for deriving and analyzing organizational relations from process models using social network analysis techniques. Process models contain information on who performs which processes and activities, along with the assignment of organizational units such as departments and roles to related activities. To derive social relations between organizational units from process models, three types of metrics are formally defined: transfer of work metrics, subcontracting metrics, and cooperation metrics. By applying these metrics, various relations among organizational units can be derived and analyzed. To verify the proposed method and metrics, they are applied to standard process models of the semiconductor and electronic, and automotive industry in Korea. This paper presents a taxonomy for diagnosing organization structure based on the presented approach. The paper also discusses how to combine analyses in the taxonomy for redesign of organizational structures.

• Journal of information and communication convergence engineering
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• 제15권3호
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• pp.165-169
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• 2017

Altmetrics is an emergent research area whereby social media is applied as a source of metrics to evaluate scientific impact. Recently, the interest in altmetrics has been growing. Traditional scientific impact evaluation indictors are based on the number of publications, citation counts and peer reviews of a researcher. As research publications were increasingly placed online, usage metrics as well as webometrics appeared. This paper explores the potential benefits of altmetrics and the deep relationship between each metrics. Firstly, we found a weak-to-medium correlation among the 11 altmetrics and visualized such correlation. Secondly, we conducted principal component analysis and exploratory factor analysis on altmetrics of social media, divided the 11 altmetrics into four feature sets, confirming the dispersion and relative concentration of altmetrics groups and developed the altmetrics evaluation model. We can use this model to evaluate the scientific impact of articles on social media.

• Journal of Information Science Theory and Practice
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• 제3권2호
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• pp.16-30
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• 2015

The term megajournal is used to describe publication platforms, like PLOS ONE, that claim to incorporate peer review processes and web technologies that allow fast review and publishing. These platforms also publish without the constraints of periodic issues and instead publish daily. We conducted a yearlong bibliometric profile of a sample of articles published in the first several months after the launch of PeerJ, a peer reviewed, open access publishing platform in the medical and biological sciences. The profile included a study of author characteristics, peer review characteristics, usage and social metrics, and a citation analysis. We found that about 43% of the articles are collaborated on by authors from different nations. Publication delay averaged 68 days, based on the median. Almost 74% of the articles were coauthored by males and females, but less than a third were first authored by females. Usage and social metrics tended to be high after publication but declined sharply over the course of a year. Citations increased as social metrics declined. Google Scholar and Scopus citation counts were highly correlated after the first year of data collection (Spearman rho = 0.86). An analysis of reference lists indicated that articles tended to include unique journal titles. The purpose of the study is not to generalize to other journals but to chart the origin of PeerJ in order to compare to future analyses of other megajournals, which may play increasingly substantial roles in science communication.

• Journal of Preventive Medicine and Public Health
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• 제57권3호
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• pp.298-303
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• 2024

Objectives: The aim of this study was to estimate drug prescription indicators in outpatient services provided at Iran Social Security Organization (SSO) healthcare facilities. Methods: Data on all prescribed drugs for outpatient visits from 2017 to 2018 were extracted from the SSO database. The data were categorized into 4 main subgroups: patient characteristics, provider characteristics, service characteristics, and type of healthcare facility. Logistic regression models were used to detect risk factors for inappropriate drug prescriptions. SPSS and IBM Modeler software were utilized for data analysis. Results: In 2017, approximately 150 981 752 drug items were issued to outpatients referred to SSO healthcare facilities in Iran. The average number of drug items per outpatient prescription was estimated at 3.33. The proportion of prescriptions that included an injection was 17.5%, and the rate of prescriptions that included an antibiotic was 37.5%. Factors such as patient sex and age, provider specialty, type of facility, and time of outpatient visit were associated with the risk of inappropriate prescriptions. Conclusions: In this study, all drug prescription criteria exceeded the recommended limits set by the World Health Organization. To improve the current prescription patterns throughout the country, it would be beneficial to provide providers with monthly and annual reports and to consider implementing some prescription policies for physicians.

• Journal of Preventive Medicine and Public Health
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• 제46권6호
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• pp.319-328
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• 2013

Objectives: This study estimated the association of cardiovascular health behaviors with the risk of all-cause and cardiovascular disease (CVD) mortality in middle-aged men in Korea. Methods: In total, 12 538 men aged 40 to 59 years were enrolled in 1993 and followed up through 2011. Cardiovascular health metrics defined the following lifestyle behaviors proposed by the American Heart Association: smoking, physical activity, body mass index, diet habit score, total cholesterol, blood pressure, and fasting blood glucose. The cardiovascular health metrics score was calculated as a single categorical variable, by assigning 1 point to each ideal healthy behavior. A Cox proportional hazards regression model was used to estimate the hazard ratio of cardiovascular health behavior. Population attributable risks (PARs) were calculated from the significant cardiovascular health metrics. Results: There were 1054 total and 171 CVD deaths over 230 690 person-years of follow-up. The prevalence of meeting all 7 cardiovascular health metrics was 0.67%. Current smoking, elevated blood pressure, and high fasting blood glucose were significantly associated with all-cause and CVD mortality. The adjusted PARs for the 3 significant metrics combined were 35.2% (95% confidence interval [CI], 21.7 to 47.4) and 52.8% (95% CI, 22.0 to 74.0) for all-cause and CVD mortality, respectively. The adjusted hazard ratios of the groups with a 6-7 vs. 0-2 cardiovascular health metrics score were 0.42 (95% CI, 0.31 to 0.59) for all-cause mortality and 0.10 (95% CI, 0.03 to 0.29) for CVD mortality. Conclusions: Among cardiovascular health behaviors, not smoking, normal blood pressure, and recommended fasting blood glucose levels were associated with reduced risks of all-cause and CVD mortality. Meeting a greater number of cardiovascular health metrics was associated with a lower risk of all-cause and CVD mortality.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.302-309
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• 2009

The effectiveness of Building Information Modeling (BIM) tools and processes has been recognized by the industry and owners are beginning to adopt Triple Bottom Line accounting practices, to enhance economic performance and environmental and social performance. However, the widespread and practical application of Green BIM remains largely unrealized. The authors identify that lack of understanding of the applicability of sustainability metrics to BIM design process is a significant barrier to this adoption. Through literature review this paper outlines the various sustainability metrics available to construction and elaborates on the potential of BIM for sustainable design. The paper maps and correlates applicable concepts of sustainability evaluation systems to BIM and describes the constraints in current BIM tools.

• 한국콘텐츠학회논문지
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• 제12권5호
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• pp.470-477
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• 2012

최근 에너지 소비 증가, 화석연료 사용의 증가로 인해 기후관련 정책이 논의 되고 있다. 건설 산업에서도 이산화탄소 배출량 감소와 녹색 건설을 위한 연구가 이루어지고 있다. 따라서 본 논문은 기존 문헌 조사와 전문가 설문조사를 통하여 교통 시설물의 친환경 성과를 비교 분석 할 수 있는 지표를 제시하였다. 지표는 경제적, 사회적, 환경적 성과지표로 구분하였으며, 경제적 지표 14개, 사회적 지표 10개, 환경적 지표 12개를 제시하였다. 도출된 지표의 적용 가능성을 검증하기 위해 건설 산업에 종사하는 실무자를 대상으로 설문조사를 통해 각 지표별로 관련성, 명확성, 적시성, 비교가능성, 자료획득 가능성을 평가하였다. 그리고 제시된 지표의 활용을 위한 방안을 제시하였다.

• Asia Marketing Journal
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• 제11권1호
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• pp.39-72
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• 2009

최근 들어 마케팅지출의 수익책임성이 쟁점으로 떠오르고 있다. 재무제표에서 마케팅비가 차지하는 비중이 높아지고 있기 때문일 것이다. 본 연구는 이러한 쟁점을 연구하는 기초 작업으로서 마케팅지출과 마케팅성과를 분류하는 체계를 마련하는데 목적이 있다. 이를 위해 마케팅지출과 마케팅성과의 관계를 다섯 가지 가설로 검증하였으며 검증결과에 근거하여 다음과 같은 분류체계를 제안한다. 첫째는 투자성업무비가 마케팅성과에 미치는 영향이 비교적 많이 검증되었다. 따라서 마케팅지출을 투자성업무비로 정의하는 것이 타당함을 제안한다. 재무제표상의 계정과목으로 시장조사비, 경상개발비, 광고선전비, 판촉비, 해외시장개척비 등이 여기에 속한다. 둘째는 마케팅지출은 여러 시기에 걸쳐서 마케팅성과에 영향을 미치는 것을 확인할 수 있었다. 따라서 마케팅지출은 투자라고 할 수 있다. 장기간에 걸쳐서 효과가 나타나는 것을 일반적으로 투자라고 하기 때문이다. 셋째는 마케팅지출은 매출액에서 차지하는 비율도 중요하지만 업계의 비율과 비교한 초과개념이 중요하다. 끝으로 마케팅성과는 과정모델보다는 균형모델로 분류하는 것이 타당하다. 그 이유는 마케팅성과인 고객성과, 시장성과, 재무성과 간의 영향을 확인하기 어렵기 때문이다. 향후 연구에서는 연구의 목적에 맞추어 과정모델과 균형모델을 선택할 것을 제안한다.

• 지능정보연구
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• 제27권1호
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• pp.23-46
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• 2021

개인화 추천에서 많이 사용되는 협업 필터링은 고객들의 구매이력을 기반으로 유사고객을 찾아 상품을 추천할 수 있는 매우 유용한 기법으로 인식되고 있다. 그러나, 전통적인 협업 필터링 기법은 사용자 간에 직접적인 연결과 공통적인 특징을 기반으로 유사도를 계산하는 방식으로 인해 신규 고객 혹은 상품에 대해 유사도를 계산하기 힘들다는 문제가 제기되어 왔다. 이를 극복하기 위하여, 다른 기법을 함께 사용하는 하이브리드 기법이 고안되기도 하였다. 이런 노력의 하나로서, 사회연결망의 구조적 특성을 적용하여 이런 문제를 해결하려는 시도가 있었다. 이는, 직접적으로 유사성을 찾기 힘든 사용자 간에도 둘 사이에 놓인 유사한 사용자 또는 사용자들을 통해 유추해내는 방식으로 상호 간의 유사성을 계산하는 방식을 적용한 것이다. 즉, 구매 데이터를 기반으로 사용자의 네트워크를 생성하고 이 네트워크 내에서 두 사용자를 간접적으로 이어주는 네트워크의 특성을 기반으로 둘 사이의 유사도를 계산하는 것이다. 이렇게 얻은 유사도는 추천대상 고객이 상품의 추천에 대한 수락여부를 결정하는 척도로 활용될 수 있다. 서로 다른 중심성 척도는 추천성과에 미치는 영향이 서로 다를 수 있다는 점에서 중요한 의미를 갖는다 할 수 있다. 이런 유사도의 계산을 위해서 네트워크의 중심성을 활용할 수 있다. 본 연구에서는 여기서 더 나아가 이런 중심성이 추천성과에 미치는 영향이 추천 알고리즘에 따라서도 다를 수 있다는 데에서 주목하여 수행되었다. 또한, 이런 네트워크 분석을 활용한 추천기법은 신규 고객 혹은 상품뿐만 아니라 전체 고객 혹은 상품으로 그 대상을 넓히더라도 추천 성능을 높이는 데 기여할 것을 기대할 수 있을 것이다. 이런 관점에서 본 연구는 네트워크 모형에서 연결선이 생성되는 것을 이진 분류의 문제로 보고, 추천 모형에 적용할 분류 기법으로 의사결정나무, K-최근접이웃법, 로지스틱 회귀분석, 인공신경망, 서포트 벡터 머신을 선택하고, 온라인 쇼핑몰에서 4년2개월간 수집된 구매 데이터로 실험을 진행하였다. 사회연결망에서 측정된 중심성 척도를 각 분류 기법에 적용하여 생성한 모형을 비교 실험한 결과, 각 모형 별로 중심성 척도의 추천성공률이 서로 다르게 나타남을 확인할 수 있었다.