• 제목/요약/키워드: explanation model

검색결과 568건 처리시간 0.034초

지식이전 선행요인에 관한 다차원 분석: 사회적 자본 이론과 사회연결망 이론의 결합 (Multi-level Analysis of the Antecedents of Knowledge Transfer: Integration of Social Capital Theory and Social Network Theory)

  • 강민형;허용석
    • Asia pacific journal of information systems
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    • 제22권3호
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    • pp.75-97
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    • 2012
  • Knowledge residing in the heads of employees has always been regarded as one of the most critical resources within a firm. However, many tries to facilitate knowledge transfer among employees has been unsuccessful because of the motivational and cognitive problems between the knowledge source and the recipient. Social capital, which is defined as "the sum of the actual and potential resources embedded within, available through, derived from the network of relationships possessed by an individual or social unit [Nahapiet and Ghoshal, 1998]," is suggested to resolve these motivational and cognitive problems of knowledge transfer. In Social capital theory, there are two research streams. One insists that social capital strengthens group solidarity and brings up cooperative behaviors among group members, such as voluntary help to colleagues. Therefore, social capital can motivate an expert to transfer his/her knowledge to a colleague in need without any direct reward. The other stream insists that social capital provides an access to various resources that the owner of social capital doesn't possess directly. In knowledge transfer context, an employee with social capital can access and learn much knowledge from his/her colleagues. Therefore, social capital provides benefits to both the knowledge source and the recipient in different ways. However, prior research on knowledge transfer and social capital is mostly limited to either of the research stream of social capital and covered only the knowledge source's or the knowledge recipient's perspective. Social network theory which focuses on the structural dimension of social capital provides clear explanation about the in-depth mechanisms of social capital's two different benefits. 'Strong tie' builds up identification, trust, and emotional attachment between the knowledge source and the recipient; therefore, it motivates the knowledge source to transfer his/her knowledge to the recipient. On the other hand, 'weak tie' easily expands to 'diverse' knowledge sources because it does not take much effort to manage. Therefore, the real value of 'weak tie' comes from the 'diverse network structure,' not the 'weak tie' itself. It implies that the two different perspectives on strength of ties can co-exist. For example, an extroverted employee can manage many 'strong' ties with 'various' colleagues. In this regards, the individual-level structure of one's relationships as well as the dyadic-level relationship should be considered together to provide a holistic view of social capital. In addition, interaction effect between individual-level characteristics and dyadic-level characteristics can be examined, too. Based on these arguments, this study has following research questions. (1) How does the social capital of the knowledge source and the recipient influence knowledge transfer respectively? (2) How does the strength of ties between the knowledge source and the recipient influence knowledge transfer? (3) How does the social capital of the knowledge source and the recipient influence the effect of the strength of ties between the knowledge source and the recipient on knowledge transfer? Based on Social capital theory and Social network theory, a multi-level research model is developed to consider both the individual-level social capital of the knowledge source and the recipient and the dyadic-level strength of relationship between the knowledge source and the recipient. 'Cross-classified random effect model,' one of the multi-level analysis methods, is adopted to analyze the survey responses from 337 R&D employees. The results of analysis provide several findings. First, among three dimensions of the knowledge source's social capital, network centrality (i.e., structural dimension) shows the significant direct effect on knowledge transfer. On the other hand, the knowledge recipient's network centrality is not influential. Instead, it strengthens the influence of the strength of ties between the knowledge source and the recipient on knowledge transfer. It means that the knowledge source's network centrality does not directly increase knowledge transfer. Instead, by providing access to various knowledge sources, the network centrality provides only the context where the strong tie between the knowledge source and the recipient leads to effective knowledge transfer. In short, network centrality has indirect effect on knowledge transfer from the knowledge recipient's perspective, while it has direct effect from the knowledge source's perspective. This is the most important contribution of this research. In addition, contrary to the research hypothesis, company tenure of the knowledge recipient negatively influences knowledge transfer. It means that experienced employees do not look for new knowledge and stick to their own knowledge. This is also an interesting result. One of the possible reasons is the hierarchical culture of Korea, such as a fear of losing face in front of subordinates. In a research methodology perspective, multi-level analysis adopted in this study seems to be very promising in management research area which has a multi-level data structure, such as employee-team-department-company. In addition, social network analysis is also a promising research approach with an exploding availability of online social network data.

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클라우드 컴퓨팅을 이용한 유시티 비디오 빅데이터 분석 (An Analysis of Big Video Data with Cloud Computing in Ubiquitous City)

  • 이학건;윤창호;박종원;이용우
    • 인터넷정보학회논문지
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    • 제15권3호
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    • pp.45-52
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    • 2014
  • 유비쿼터스 시티(유시티)에서는 수많은 비디오 카메라들이 설치된다. 이렇게 설치된 많은 카메라로부터 대용량의 비디오 데이터가 실시간으로 끊임없이 발생하고 유시티의 관리 시스템으로 전달된다. 유시티의 다양한 서비스들을 뒷받침하기 위해서는 이러한 비디오 데이터를 저장하고, 이렇게 저장된 대용량의 비디오 데이터를 분석할 수 있는 방법과 관리 시스템이 요구된다. 그래서, 이 논문에서는 클라우드 컴퓨팅을 기반으로 한 유시티 비디오 관리 시스템을 제안한다. 또한, 근래 주목받고 있는 데이터 병렬처리 프레임워크인 Hadoop MapReduce를 이용하여 이러한 빅데이터 비디오를 분석하는 방법을 제안하고, 이에 따른 우리의 성능 평가를 소개한다.

우울증 환자에서 D형 인격과 신체 증상 호소와의 관련성 (Association between Type D Personality and the Somatic Symptom Complaints in Depressive Patients)

  • 박우리;정성훈
    • 정신신체의학
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    • 제21권1호
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    • pp.18-26
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    • 2013
  • 연구목적 D형 인격(Type D personality)은 본래 심장 질환의 예후와 관련되는 성격 인자에 관한 연구에서 처음 제안되었고 이후 연구들에서는 다양한 내과적 질환들에서 D형 인격이 관련된다는 것을 보고하였다. 본 연구에서는 우울증 환자의 신체화 증상과 D형 인격의 관련성을 알아보고자 하였다. 방 법 우울 장애로 진단 받은 82명의 환자를 대상으로 D형 인격척도인 DS-14(Type D personality scale 14)를 사용하여 D형 인격 여부를 조사하였다. PHQ-9, PHQ-15(환자 건강 설문지, Patient health questionnaire-9,15)를 사용하여 우울증의 심각도와 신체화 경향에 대하여 평가하였고, TAS-20(한국판 토론토 감정표현불능증 척도, The Korean version of 20-item Toronto alexithymia scale)으로 감정표현불능증의 정도를 측정하였다. Student t-test와 선형 회귀분석을 시행하였고, 단계적(stepwise) 변수 추출을 통해 가장 설명력이 높은 모형을 선정하여 신체 증상에 영향을 미치는 요인을 확인하였다. 결 과 전체 대상자의 절반 이상(56%)이 PHQ-15에서 중증의 신체 증상을 호소하였고, 63.4%가 D형 인격으로 판정되었다. D형 인격군은 대조군에 비하여 PHQ-15 점수가 유의하게 높았다(PHQ-15 mean=12.7, $p=8.2{\times}10^{-7}$). 회귀 분석에서 최종적으로 선정된 모형은 연령, PHQ-9, 그리고 DS-14의 하위영역인 NA가 포함된 모형이었으며, 이들 중 연령($p=1.5{\times}10^{-3}$)과 NA($p=1.5{\times}10^{-7}$)가 신체 증상에 가장 큰 영향을 주는 변인으로 분석되었다. 결 론 본 연구 결과는 D형 인격이 우울증 환자의 신체 증상 호소의 강력한 예측 인자임을 시사한다. 특히 사회적 억제 성향보다 부정적 정서 성향이 신체화 경향과 더 관련성이 깊었다는 결과는 기존의 신체화에 대한 이해, 즉 부정적 정서를 표현해내는 능력이 결여된 경우 이를 신체 증상으로 표출한다는 설명과는 다소 차이가 있는 것으로 보인다. 감정표현불능증이 유의한 예측인자가 아닌 것으로 나타났다는 결과 또한 이러한 차이와 관련된다. 그러나 사회적 억제 성향과 부정적 정서 성향(r=0.65), 감정표현불능증(r=0.44) 간에는 높은 상관 관계를 보였기 때문에 이를 고려한 대규모 연구가 필요할 것으로 생각된다.

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묶음제품 가격 할인 제시 프레이밍 효과: 지각된 소비 혜택과 품질 불확실성의 영향을 중심으로 (Discount Presentation Framing & Bundle Evaluation: The Effects of Consumption Benefit and Perceived Uncertainty of Quality)

  • 임미자
    • Asia Marketing Journal
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    • 제14권1호
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    • pp.53-81
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    • 2012
  • 묶음제품의 매력도를 증가시키기 위해 소비자들이 번들 오퍼에서의 가격 제시 프레이밍(framing)에 민감하다는 것을 이해할 필요가 있다. 동일 가격을 할인하더라도 묶음제품 요소 중 어느 요소에 가격할인을 표시하느냐에 따라 소비자의 묶음제품에 대한 지각된 매력도를 바꿀 수 있기 때문이다. 선행연구는 더 중요한 제품 요소에 할인이 할당될 때 효용이 증가한다는 주장과 덜 중요한 제품 요소에 할인을 위치시키는 것이 선호를 증가시킨다는 주장을 동시에 보이고 있다. 본 연구는 선행연구를 보완하여 묶음제품 가격 할인 제시 프레이밍효과에 대한 새로운 기제를 제시한다. 그리고 선행연구에서 믹스드(mixed)된 결론을 보이는 이유를 분석하여 밝힌다. 본 연구는 현실적인 번들링 전략 사용 상황을 고려하였으며, 좀 더 리얼한 번들링 세팅을 이용하여 가격 할인 제시 프레이밍 효과를 조사하고, 순수번들 및 혼합번들을 포함한 다양한 묶음제품을 이용하여 품질 불확실성 지각에 따른 조절효과를 분석하였다. 본 연구 결과, 소비자들은 높은 소비 혜택(high consumption benefit)보다 낮은 소비 혜택(low consumption benefit) 요소에 가격 할인을 위치시키는 것을 더 선호하였다. 가격민감성(price sensitivity)이 주요혜택에서는 낮고, 낮은 혜택에서는 높기 때문에 동일 가격이 할인될 때 낮은 혜택을 할인한 매장 제품에 대한 평가가 더 높게 나타났다. 또한 구매 시점에서 품질의 불확실성(perceived uncertainty of product quality)이 높을수록 가격민감성이 혜택 지각에 가지는 효과가 더 커지고 있었다. 본 연구의 공헌은 소비 혜택 지각 및 가격민감성 기제와 지각된 품질 불확실성의 조절효과를 통해 선행연구를 통합하고, 가격 제시 형태의 프레이밍 효과를 명확하게 설명하였다는 점이다.

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한정된 O-D조사자료를 이용한 주 전체의 트럭교통예측방법 개발 (DEVELOPMENT OF STATEWIDE TRUCK TRAFFIC FORECASTING METHOD BY USING LIMITED O-D SURVEY DATA)

  • 박만배
    • 대한교통학회:학술대회논문집
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    • 대한교통학회 1995년도 제27회 학술발표회
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    • pp.101-113
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    • 1995
  • The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

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웹기반 지능형 기술가치평가 시스템에 관한 연구 (A Study on Web-based Technology Valuation System)

  • 성태응;전승표;김상국;박현우
    • 지능정보연구
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    • 제23권1호
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    • pp.23-46
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    • 2017
  • 2000년대 이전부터 북미 유럽의 선진국을 중심으로 특정 기업이나 사업(프로젝트)에 관한 가치를 평가하는 사례는 있어 왔으나, 개별 기술(특허)의 경제적 가치를 산정하는 체계나 방법론은 국내를 중심으로 최근 들어 활성화되어 왔다. 이러한 기술가치평가 분야는 기술이전(거래), 현물출자, 사업타당성 분석, 투자유치, 세무/소송 등의 다양한 용도로 활용되고 있다. 물론 기술보증기금의 KTRS, 발명진흥회의 SMART 3.1과 같이, 평가대상기술에 대한 기술력(등급) 평가 혹은 특허등급평가를 정성적으로 수행하는 온라인 시스템은 존재해 왔으나, 대상기술의 정량적인 가치금액까지 산출해 주는 웹기반 지능형 기술가치평가 시스템은 한국과학기술정보연구원(KISTI)에 의해 유일하게 개발 및 공식 오픈되어 확산 활용되고 있다. 본 고에서는 KISTI에서 개발 운영중인 웹기반 'STAR-Value' 시스템을 중심으로, 탑재된 방법론 및 평가모델의 유형, 이를 지원하는 참조정보 및 데이터베이스(D/B)가 어떻게 연계 활용되는지를 소개한다. 특히 미래에 발생할 경제적 수익을 추정하여 현재가치화하는 소득접근법 기반의 대표 모델인 현금흐름할인(DCF) 모델과 특정 로열티율을 기반으로 로열티수입료의 현재가치를 기술료 대가로 산정하는 로열티절감모델을 포함한 6개 모델, 그리고 관련 지원정보(기술수명, 기업(업종)재무정보, 할인율, 산업기술요소 등)의 데이터 기반 연계 방식에 대해 살펴본다. STAR-Value 시스템은 평가대상기술에 대한 국제특허분류(IPC) 혹은 한국표준산업분류(KSIC) 등의 분류 정보로부터 기술순환주기(TCT) 지수, 유사업종(혹은 유사기업)의 매출액 성장률 및 수익성 데이터, 업종별 가중평균자본비용(WACC) 및 산업기술요소 지수 등 메타데이터값을 자동적으로 불러오고 여기에 조정요인을 반영하여 기술가치의 산출결과가 높은 신뢰성 및 객관성을 가지도록 한다. 나아가 대상기술의 잠재적 시장규모와 해당 사업화주체의 시장점유율에 대한 정보까지 보유 재무데이터 기반으로 참조값을 제시하거나 기존에 완료된 평가사례 축적 기반으로 업종별 유사 기술의 가치범위값을 제시해 준다면, 본 시스템이 보다 지능형으로 지원 모듈을 연계 활용하고 실시간으로 손쉽게 고(高)정확도의 기술가치범위를 제시해 줄 수 있을 것으로 기대된다. 본 고에서는 웹기반 STAR-Value 시스템이 참조데이터 기반으로 지능형 연계를 수행하도록 해주는 모형선택 가이드라인 지원기능, 기술가치범위 추론 지원기능, 유사기업 선정 기반의 시장점유율 산정 지원기능의 내부 로직 구성을 설명한다. 상기 지원기능을 통해 비전문가(또는 초보자) 수준에서 최적의 평가모형 선택, 기술가치 범위 추론, 유사기업 선택 및 시장점유율 산정에 대한 정보지원이 데이터 사이언스 및 기계학습 기반으로 수행될 수 있다. 본 연구는 기술가치평가 분야의 이론적 타당성을 평가실무에서 활용할 수 있는 평가모델 및 지원정보를 실제 탑재한 웹기반 시스템의 소개에 의미가 있으며, 추가적으로 보다 객관적이고 손쉬운 지능형 지원시스템의 활용성을 높임으로써, 앞으로 기술사업화의 제 분야에서 다양하게 활용할 수 있을 것으로 기대된다.

Computer Aided Innovation 역량이 연구개발역량에 미치는 효과: 국내 중소기업을 대상으로 (The Effects of the Computer Aided Innovation Capabilities on the R&D Capabilities: Focusing on the SMEs of Korea)

  • 심재억;변무장;문효곤;오재인
    • Asia pacific journal of information systems
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    • 제23권3호
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    • pp.25-53
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    • 2013
  • This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.

교통사고 데이터의 마이닝을 위한 연관규칙 학습기법과 서브그룹 발견기법의 비교 (Comparison of Association Rule Learning and Subgroup Discovery for Mining Traffic Accident Data)

  • 김정민;류광렬
    • 지능정보연구
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    • 제21권4호
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    • pp.1-16
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    • 2015
  • 교통사고의 원인을 규명하고 미래의 사고를 방지하기 위한 노력의 일환으로 데이터 마이닝 기법을 이용한 교통 데이터 분석의 연구가 이루어지고 있다. 하지만 기존의 교통 데이터를 이용한 마이닝 연구들은 학습된 결과를 사람이 이해하기 어려워 분석에 많은 노력이 필요하다는 문제가 있었다. 본 논문에서는 많은 속성들로 표현된 교통사고 데이터로부터 유용한 패턴을 발견하기 위해 규칙 학습 기반의 데이터 마이닝 기법인 연관규칙 학습기법과 서브그룹 발견기법을 적용하였다. 연관규칙 학습기법은 비지도 학습 기법의 하나로 데이터 내에서 동시에 많이 등장하는 아이템(item)들을 찾아 규칙의 형태로 가공해 주며, 서브그룹 발견기법은 사용자가 지정한 대상 속성이 결론부에 나타나는 규칙을 학습하는 지도학습 기반 기법으로 일반성과 흥미도가 높은 규칙을 학습한다. 규칙 학습 시 사용자의 의도를 반영하기 위해서는 하나 이상의 관심 속성들을 조합한 합성 속성을 만들어 규칙을 학습할 수 있다. 규칙이 도출되고 나면 후처리 과정을 통해 중복된 규칙을 제거하고 유사한 규칙을 일반화하여 규칙들을 더 단순하고 이해하기 쉬운 형태로 가공한다. 교통사고 데이터를 대상으로 두 기법을 적용한 결과 대상 속성을 지정하지 않고 연관규칙 학습기법을 적용하는 경우 사용자가 쉽게 알기 어려운 속성 사이의 숨겨진 관계를 발견할 수 있었으며, 대상 속성을 지정하여 연관규칙 학습기법과 서브그룹 발견기법을 적용하는 경우 파라미터 조정에 많은 노력을 기울여야 하는 연관규칙 학습기법에 비해 서브그룹 발견기법이 흥미로운 규칙들을 더 쉽게 찾을 수 있음을 확인하였다.

치열궁의 성장 변화 (GROWTH AND DEVELOPMENT OF ARCH FORM)

  • 손병화;백형선
    • 대한치과교정학회지
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    • 제28권1호
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    • pp.17-27
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    • 1998
  • 치열궁의 성장 변화에 대한 연구는 교정 진단과 치료 계획 수립시와 결과의 분석에 있어서 중요한 자료가 될 수 있으며, 이러한 치열궁의 형태는 자연 인류학과 치의학 특히 보철학과 교정학 분야에서 더욱 중요한 의미가 있다. 특히 교정학 분야 에서는 상,하악 치아의 기능적인 면과 치료후의 치열과 교합의 안정성 유지에 대한 정보를 얻기 위하여 일찍 부터 연구가 진행 되어 왔다. 이에 대한 연구로는 이미 많은 선학들의 연구가 보고 되어 오고 있다. 초기에는 두개골을 직접 측정하여 치궁의 성장 변화를 설명 하였고,그 후 방사선이 소개 됨으로 방사선 사진을 이용한 계측과 또한 경석고 토형을 사용한 선계측 방법도 많이 시도 되어 왔다. 그 방법으로는 치열궁의 폭경, 치열궁 장경 및 주위경 등을 계측하여 치열궁의 성장 변화를 연구 하여 왔다. 본 연구에서는 강원도 지역과 서울 지역에 거주하는 교정 치료를 받지 않고, 건강한 심신과 정상적인 성장 발육을 하고 있는 정상 교합자 3세 에서 12세 까지의 남,녀 아동 600여명을 대상으로 하였으며, 각각 두부 측면 방사선 사진, 파노라마 사진, 그리고 치열궁 모형을 두해 연속해서 채득을 한 이후 계속 follow up 하고 있으며 현재까지 follow up 된 두해에 걸친 각각 200여 쌍, 총 400여 쌍의 모형을 채택하여 본 연구를 하였다. 본 연구에서는 치아의 근원심 폭경, 견치간 폭경, 구치간 폭경, 견치 치열궁 장경, 구치 치열궁 장경, 그리고 치열궁 주위경을 측정하여 연령별 성별 평균과 표준 편차를 내고 도표로 표시 하여 다음과 같은 결론을 얻었다. 1. 견치간 폭경은 계속 완만히 증가하다가 10세 이후 12세까지는 증가하지 않았다. 2. 제 1 대구치간 폭경에 대해서는 상악은 완만한 증가를 보이지만 하악의 경우는 유의성있는 변화를 보이지 않다가 9세 이후 증가하는 양상을 보였다. 3. 견치 치열궁 장경은 6세 이후 비교적 급격한 증가를 보였고 하악의 경우 더욱 뚜렷하다. 4. 구치 치열궁 장경은 상.하악 모두 서서히 증가하다가 10세 이후 부터는 감소하는 양상을 보였다. 이러한 감소 경향은 하악에서 더욱 두드러진다. 5. 치열궁 주위경은 서서히 증가하는 경향을 보이다가 그 증가량이 점차 완만해지고 10세이후에는 다시 감소하는 경향을 보이는데 이러한 경향은 하악에서 약간 크고 빠르게 나타났다.

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병원서비스코디네이터 교육과정이 교육만족과 의료서비스 품질에 미치는 영향 (The Effect of Hospital Service Coordinator Education Curriculum on the Education Satisfaction and the Quality of Medical Service)

  • 최은경;박창식;서종범
    • 보건의료산업학회지
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    • 제2권1호
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    • pp.137-154
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    • 2008
  • The increase of the supply of medical service and the increase of hospitals have intensified the competition of hospitals, and the advancement towards internationalization in the opening of medical industry has triggered the infinite competition of medical profession. In addition, the high expectation of customers and quality improvement in the medical care in accordance with the improvement of overall income, and the change of active role of medical consumers according to the popularization and the improvement of rights awareness reflect the customer needs and choice in the medical service. Customers wanted to receive the kind and pleasant service under the up-to-date medical service. Therefore, as a solution, hospital coordinators were emerged for the purpose of smooth treatment and customer satisfaction by generalizing all service of hospital. Accordingly, this thesis attempted to investigate the effect of hospital coordinator education curriculum on the education satisfaction and the quality of medical service. In order to solve the purpose of this study, I, author reviewed the existing literatures, established hypothesis, and verified hypothesis by using the variety of statistics techniques such as reliability, validity, frequency analysis, and regression analysis. The verification of hypothesis is as followings: First, among education training factors of hospital coordinators, the quality of instructor significantly affects the satisfaction of hospital coordinator education training. Second, among training factors of hospital coordinator, the attitude of trainee significantly affects the training satisfaction of hospital coordinator. Third, among education training factors of hospital coordinator, education course significantly affects the training satisfaction of hospital coordinator education. As the qualities of instructor are better equipped, the satisfaction of education becomes higher. It indicates that the education method of instructors is important as an index to represent the qualities of instructor such as the appropriateness of education method, preparation, passion, visual materials, the adequacy of education procession, and specialized knowledge, and it has important effect on the satisfaction of education. In order to enhance the satisfaction of hospital coordinator education, the creation of education environment, making trainee concentrate on the education, is required by appropriately allocating programs, arousing interest in education, based on the attitude of trainee, discussion, and preliminary programs, preparation, ahead of enforcement of education. Fourth, the satisfaction of hospital coordinator education training significantly affects the reliability among the qualities of medical service. Fifth, satisfaction of hospital coordinator education training significantly affects hospitality I kindness among the qualities of medical service. If the education satisfaction of trainee is high, it is effective in the practical application such as dealing with complaints, the duty performance for the patients, and so on in offering the medical service, related to reliability and furthermore, we can find the positive change in the attitude change of medical professions related to the reliability of hospital coordinator. In addition, in the process of offering medical services such as the kind explanation on the duty, rapid response to the customers inquiry, and tidy uniform, practical effect was verified. Sixth, the education training factor of hospital coordinator significantly affects the reliability among the quality of medical service. Seventh, the education training factors of hospital coordinator significantly affect hospitality/kindness. In the education of hospital coordinator, the methods to attract the interest of trainee by emphasizing reliability should be sought and for gaining the practical effect of hospital coordinator education, the sufficient preparation and investigation on the education curriculum should be prerequisite and under this condition, intensified discussion on the instructor and education course is needed. In the design of education course, more education hours and subjects should be allocated in the part of hospitality in order to improve the practical application of hospitality. Therefore, it is meaningful in a sense that this study newly approached the components of hospital coordinator education and the need to modify the quality components of medical service in accordance with the study subjects was raised. This study also finds its meaning in that it provides basic materials for the study of future hospital coordinator education by suggesting the system development model of hospital coordinator education through preliminary study of education training. In addition, this study is meaningful in the aspect that it suggested the direction of education training by showing how the hospital coordinator education training would applied to the hospital coordinator course of the Continuing Education Center at Pusan and Kyungnam National University to some extent. Since all investigation of this study was approached from the side of hospital coordinator, the thoughts of patients who are beneficiaries of medical service, and care givers cannot be identified. Therefore, the satisfaction of patients and care givers through the experience of medical service, which is the essential prerequisite of medical service, should be importantly considered and investigated. Accordingly, The study of comparing and analyzing the views of both patients and care givers should be carried out in the future.

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