• Title/Summary/Keyword: structural equation model (SEM)

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SCHEMATIC ESTIMATING MODEL FOR CONSTRUCTION PROJECTS -USING PRICIPLE COMPONENT ANALYSIS AND STRUCTURAL EQUATION METHOD

  • Young-Sil Jo;Hyun-Soo Lee;Moon-Seo Park
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.1223-1230
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    • 2009
  • In the construction industry, Case-Based Reasoning (CBR) is considered to be the most suitable approach and determining the attribute weights is an important CBR problem. In this paper, a method is proposed for determining attribute weights that are calculated with attribute relation. The basic items of consideration were qualitative and quantitative influence factors. These quantitative factors were related to the qualitative factors to develop a Cost Drivers-structural equation model which can be used to estimate construction cost by considering attribute weight. The process of determining the attribute weight-structural equation model consists o 4 phases: selecting the predominant Cost Drivers for the SEM, applying the Cost Driers in the SEM, determining and verifying the attribute weights and deriving the Cost Estimation Equation. This study develops a cost estimating technique that complements the CBR method with a Cost Drivers-structural equation model which can be actively used during the schematic estimating phases of construction.

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글로벌 기업의 고객만족과 경쟁력 모델 구축: 품질요인확인을 위한 구조방정식모델 적용 (Customer satisfaction and competitiveness in Global Company: Structural Equation Modeling(SEM) approach to identify the role quality factor)

  • 김계수;박종철
    • 품질경영학회지
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    • 제43권1호
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    • pp.43-56
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    • 2015
  • Purpose: In this research, We made the conceptual frameworks for SEM(Structural Equation Modeling) on Global quality's origin and empirical research. Developing conceptual frameworks is an important step in theory building and theory testing. This research model was developed by strong theoretical foundation which is quality and systematical model. Methods: Questionnaire was developed, and data was collected and analyzed for this study. The analysis was conducted using SEM(Structural Equation Modeling). Results: Results show that process quality and interaction quality are important drivers in customer satisfaction. Customer satisfaction is strongly impact on customer loyalty(repeated purchase). Conclusion: In turbulent business era, Global company require not only excellent quality but also create customer oriented culture and control over operation in the foreign country.

경영정보학 분야의 구조방정식모형 적용분석 : Lisrel과 PLS 방법을 중심으로 (The Structural Equation Modeling in MIS : The Perspectives of Lisrel and PLS Applications)

  • 김인재;민금영;심형섭
    • 한국IT서비스학회지
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    • 제10권2호
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    • pp.203-221
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    • 2011
  • The purpose of this study is to investigate the applications of Structural Equation Modeling(SEM) into MIS area in recent years. Two methodologies, Lisrel and PLS, are adopted for the method comparison. A research model, based upon TAM(Technology Acceptance Model) is used for the analysis of the data set of a previous study. The research model includes six research variables that are composed of twenty-eight question items. 272 data are used for data analyses through Lisrel v.8.72 and Visual PLS v.1.04. This study shows the statistical results of Lisrel are the same to those of PLS. The contribution of this study can be suggested as the followings; (1) A theoretical comparison of two methodologies is shown, (2) A statistical analysis is done at a real-situated data set, and (3) Several implications are suggested.

순서형 자료로 측정된 구조방정식모형 분석 (The Structural Equation Model with Ordinal Data)

  • 윤상운;박정선;이태섭
    • 품질경영학회지
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    • 제30권3호
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    • pp.38-52
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    • 2002
  • This paper is concerned with the analysis of structural equation model(SEM) with the ordinal data such as Likert scale. The SEM is misused when the arbitrary scores allocated to the Likert scale are treated as quantitative data. The underlying distribution approaches have been studied to solve this problem, and the partial least squares(PLS) Is also tried. In this paper the quantification methods for the Likert scale are proposed to analyze the SEM. We assume that the Likert scale is an observation of the interval of the continuous underlying distribution, and the respondents have their own patterns in the response of some questions. Normal and beta distributions as the response patterns are considered to quantify the Likert scale. To compare the efficiency of the proposed method the bootstrap simulations are tried.

구조방정식모형(SEM)을 활용한 버스 이용자의 통행시간 중요도-만족도 분석(IPA) (An Importance-Performance Analysis(IPA) for Bus Users Travel Time by Using Structural Equation Model(SEM))

  • 안우영;이솔
    • 대한토목학회논문집
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    • 제35권3호
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    • pp.663-670
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    • 2015
  • 현재 수립된 대부분의 대중교통관련 계획에서는 투자우선순위를 결정함에 있어 중요도(importance) 분석 없이 시설물 조사와 설문 조사를 통해 시설물에 대한 설치율과 만족도(performance)가 낮은 항목을 우선적으로 고려하여 투자순위를 결정하고 있다. 본 연구에서는 구조방정식모형(SEM: Structural Equation Model)을 활용하여 버스 이용자의 통행시간에 대한 중요도와 만족도를 동시에 고려할 수 있는 중요도-만족도 분석(IPA: Importance-Performance Analysis) 기법을 제시하였다. 수도권과 비수도권을 대상으로 버스이용자에 대한 IPA 분석을 실시한 결과 수도권의 경우 우선적인 개선이 필요한 항목으로는 버스정차횟수, 교차로수, 배차간격, 승차대기시간 및 신호체계 순서로 분석되었고, 비수도권의 경우 수도권의 역순인 신호체계, 승차대기시간, 배차간격, 버스전용차로 및 교차로수 순서로 분석되었다.

구조방정식을 이용한 도시부 4지 신호교차로의 사고원인 분석 (A Causational Study for Urban 4-legged Signalized Intersections using Structural Equation Method)

  • 오주택;이상규;허태영;황정원
    • 한국도로학회논문집
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    • 제14권6호
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    • pp.121-129
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    • 2012
  • PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

구조방정식을 이용한 고령운전자 교통사고 인적 피해 심각도 분석 (고양시를 중심으로) (An Analysis of Traffic Accident Injury Severity for Elderly Driver on Goyang-Si using Structural Equation Model)

  • 김솔람;윤덕근
    • 한국도로학회논문집
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    • 제17권3호
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    • pp.117-124
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    • 2015
  • PURPOSES : The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS : To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS : This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including ${\chi}^2/df$, GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS : Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

SEM-Artificial Neural Network 2단계 접근법에 의한 클라우드 스토리지 서비스 이용의도 영향요인에 관한 연구 (A SEM-ANN Two-step Approach for Predicting Determinants of Cloud Service Use Intention)

  • ;권순동
    • Journal of Information Technology Applications and Management
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    • 제30권6호
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    • pp.91-111
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    • 2023
  • This study aims to identify the influencing factors of intention to use cloud services using the SEM-ANN two-step approach. In previous studies of SEM-ANN, SEM presented R2 and ANN presented MSE(mean squared error), so analysis performance could not be compared. In this study, R2 and MSE were calculated and presented by SEM and ANN, respectively. Then, analysis performance was compared and feature importances were compared by sensitivity analysis. As a result, the ANN default model improved R2 by 2.87 compared to the PLS model, showing a small Cohen's effect size. The ANN optimization model improved R2 by 7.86 compared to the PLS model, showing a medium Cohen effect size. In normalized feature importances, the order of importances was the same for PLS and ANN. The contribution of this study, which links structural equation modeling to artificial intelligence, is that it verified the effect of improving the explanatory power of the research model while maintaining the order of importance of independent variables.

SEM에서 위계모형을 이용한 다중공선성 문제 극복방안 연구 : 소셜커머스의 재구매의도 영향요인을 중심으로 (Exploring a Way to Overcome Multicollinearity Problems by Using Hierarchical Construct Model in Structural Equation Model)

  • 권순동
    • Journal of Information Technology Applications and Management
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    • 제22권2호
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    • pp.149-169
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    • 2015
  • This study tried to find out how to overcome multicollinearity problems in the structural equation model by creating a hierarchical construct model about the repurchase intention of social commerce. This study selected, as independent variables, price, quality, service, and social influence, based on literature review about social commerce, and then, as detailed variables of independent variables, selected system quality, information quality, transaction safety, order fulfillment and after-sales service, communication, subjective norms, and reputation. As results of empirical analysis about hierarchical construct model, all the independent variables were accepted having a significant impact on repurchase intention of social commerce. Next, this study analyzed the competition model that eight independent variables of price, system quality, information quality, transaction safety, order fulfillment and after-sales service, communication, subjective norm, and reputation directly influence the repurchase intention of social commerce. As results of empirical analysis, system quality, information quality, transaction safety, communication appeared to be insignificant. This study showed that hierarchical construct model is useful to overcome the multicollinearity problem in structural equational model and to increase explanatory power.

R을 이용한 공분산 기반 구조방정식 모델링 튜토리얼: Lavaan 패키지를 중심으로 (A Tutorial on Covariance-based Structural Equation Modeling using R: focused on "lavaan" Package)

  • 윤철호;최광돈
    • 디지털융복합연구
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    • 제13권10호
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    • pp.121-133
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    • 2015
  • 본 튜토리얼은 R을 이용하여 공분산 기반의 구조방정식모델링을 수행하는 방법을 제시하고 있다. 이를 위해 본 튜토리얼에서는 기존 연구들에 대한 리뷰를 통해 공분산 기반의 구조방정식모델링을 위한 기준들을 정의하고, 하나의 예시 연구모형을 제시하여 공분산 기반의 구조방정식모델링을 지원하는 R 패키지인 "lavaan"을 이용하여 이 예시 모형을 분석하는 것을 보여준다. 결과물로 본 튜토리얼에서는 예시모형을 대상으로 한 R을 이용한 공분산 기반의 구조방정식모델링 기법과 실습 스크립트가 제시되었다. 본 튜토리얼은 공분산 기반의 구조방정식모델링을 처음 접하는 연구자들에게는 연구모형을 구조방정식 모델링으로 분석하는데 유용한 가이드가 될 것이며, 이미 공분산 기반의 구조방정식모델링에 익숙한 연구자들에게는 R을 이용한 새로운 공분산 기반의 구조방정식모델링 분석기법 제시를 통하여 R이라는 통합된 통계 소프트웨어 운영환경에서 심도 있는 연구를 위한 기반 지식을 제공할 것이다.