• Perspectives in Nursing Science
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• v.11 no.2
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• pp.109-122
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• 2014

Purpose: The purpose of this study was to review research papers on structural equation models for hospital nurses' turnover intentions, and to identify the factors that influence these intentions. Methods: Twenty-four research papers on structural equation models for hospital nurses' turnover intentions were identified for systematic review. Results: All 24 papers assessed nurses' turnover intentions in general hospitals and university hospitals. A total of 36 indicators and 105 items were used to measure turnover intention. Turnover intention was positively related with 10 variables, and negatively with 17 variables. Organizational commitment, job satisfaction, job stress, burnout, organizational culture, and empowerment were found to have significant direct and indirect effects on nurses' turnover intentions. Structural equation models in 23 of the 24 research papers showed high compatibility with the data. The models accounted for 20.1% 68.0% of total variances. Conclusion: The study findings show recent trends in nurses' turnover intentions, and indicate directions for future research.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.10a
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• pp.23-28
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• 1992

The ultimate capacity of end-plate connection is investigated through nonlinear finite element analysis. The example models are divided into stiffened case and unstiffened one. The refined finite element models are analyzed by utilizing a general purpose structural analysis computer program ADINA and the moment-rotation relationships of the connection are determined. The results are compared with the regression equation deduced by Krishnamurthy. It is planned to deduce a bilinear regression equation through a parametric study on various dimensions of the connection.

• International Journal of Highway Engineering
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• v.14 no.6
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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.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.113-124
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• 2004

Customer satisfaction is becoming an increasingly salient topic in many firms and in academic research. One main rationale behind this interest is that customer satisfaction is believed to be associated with fruitful customer re-visit from the firm's point of view. Some country already had index models which can measure the degree of customer satisfaction. But, such models are ordinary models which used generally the scope of nation-wide /industry. Therefore, we needs some modifications to measure customer satisfaction for specific product & service and to provide the valuable feedback to specific firms. In this Perspectives, this study will evaluate the customer satisfaction index about automobile company and analyze it's result for valuable feedback. This study will present a model for an integrated customer satisfaction evaluation system which used structural equation modeling. Through this study, we anticipate that it will offer the measuring method about customer satisfaction and some guideline for product design process.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.04a
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• pp.111-118
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• 1996

Dynamic load models which show the practical behavior of truss bridge subjected to moving train load are presented. Three basically approaches are available for evaluating structural response to dynamic effects : moving force, moving mass, and influence moving force and mass. Simple warren truss bridge model is selected in this research, and idealized lumped mass system, modelled as a planar structure. In the process of dynamic analysis, the uncoupled equation of motion is derived from simultaneous equation of the motion of truss bridge and moving train load. The solution of the uncoupled equations of motion is solved by Newmark-$\beta$ method. The results show that dynamic response of moving mass and static analysis considering the impact factor specified in the present railway bridge code was nearly the same. Generally, the dynamic response of moving force is somewhat greater than that of moving mass. The dynamic load models which are presented by this study are obtained relatively adequate load model when apply to a truss bridge.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.65-76
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• 2013

Traffic accidents at signalized intersections have been increased annually so that it is required to examine the causation to reduce the accidents. However, the current existing accident models were developed mainly by using non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal the complicated causation for traffic accidents, though they are the right choice to study randomness and non-linearity of accidents. Therefore, it is required to utilize another statistical method to make up for the lack of the non-linear regression methods. This study developed accident prediction models for 4 legged signalized intersections with Poisson methods and compared them with structural equation models. This study used structural equation methods to reveal the complicated causation of traffic accidents, because the structural equation method has merits to explain more causational factors for accidents than others.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.227-234
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• 2003

This study presents the stress evaluation equations of circular column-box beam connection in steel frame piers. FEM analysis were carried out for circular column-box beam connection. Analysis models were made for design parameters such as joint angle, span length-width ratio(L/B), sectional-area ratio(S=A/sub w/A/sub f/), and circular column-box beam stiffness ratio(Ic/Ib). Analysis results were compared to the existing equation. Based on analysis results the stress evaluation equations of circular column-box beam connection are proposed by regression analysis.

• Structural Monitoring and Maintenance
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• v.10 no.2
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• pp.175-190
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• 2023

This article aims to quantitatively predict the snowmelt in extreme cold regions, considering a combination of grayscale and neural models. The traditional non-equidistant GM(1,1) prediction model is optimized by adjusting the time-distance weight matrix, optimizing the background value of the differential equation and optimizing the initial value of the model, and using the BP neural network for the first. The adjusted ice forecast model has an accuracy of 0.984 and posterior variance and the average forecast error value is 1.46%. Compared with the GM(1,1) and BP network models, the accuracy of the prediction results has been significantly improved, and the quantitative prediction of the ice sheet is more accurate. The monitoring and maintenance of the structure by quantitative prediction model by gray models was clearly demonstrated in the model.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.133-151
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• 2007

The purpose of this article is to examine the effects of item parceling on the consistency of significance testing of the causal parameters with regard to the relationship between the relevant constructs, as well as the effects of the item parceling on the goodness-of-fit indices of LISREL's general models. Most of the researchers' major purpose of using structural equation modeling (SEM) is to test their research hypotheses associated with the causal parameters. Therefore, we investigated three general models of LISREL, rather than the frequently used confirmatory factor analytic (CFA) models by many other researchers. The results of the study showed that there was a high level of consistency in the calculated test statics of causal parameters between the item-parceled solutions and the item-level solutions, and that the item-parceled solutions had better goodness-of-fit indices, such as GFI, AGFI, CFI, and NFI, than the solutions at the item level. However, in terms of RMSEA, there was no such tendency.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.301-311
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• 1997

The purpose of this study is to construct a structural equation model and to analyze causal relationships among variables related to attitudes to science using structural equation modeling(SEM) with LISREL VII. The sample consisted of 483 10th grade boys from a general high school in Pusan, Korea. The questionnaires (ABC-attitude scale: affection, behavioral intention, cognition scale of attitude towards science) were developed by the researcher through a pilot study. And other instruments have modified previous ones. Five instruments were used in this study: GALT(group assessment of logical thinking), MTSlS(modified test of science inquiry skill), ABC-attitude scale, MSAS(modified scientific attitude scale), CSAT(common science achievement test). Structural equation modeling with LISREL VII($J\ddot{o}reskog$ & $S\ddot{o}rbom,$ 1993) was employed to estimate the causal inferences about hypothesized relationships among observed data sets. Three competing models consisted of five latent variable(scientific thinking ability, science inquiry skill, attitude towards science, scientific attitude, science achievement) - lP(inquiry preceding) model, AP(attitude preceding) model and AM(attitude mediating) model - were developed. Among these competing models, IP model satisfied the observed data sets. The causal relationships among "attitudes to science" and other latent variables were reliably identified. According to the results of the present study, science inquiry skill was the most significant variable that can predict science achievement. But scientific thinking ability has not directly influenced science achievement. This study suggests that inquiry based teaching-learning processes should be offered to students for improvement of science achievement. At the same time, it seems to be important to develop positive attitude towards science. Understanding of relationships among variables related to attitudes to science will be helpful to the development of science curriculum and to the design of science teaching and learning process. LISREL has been recognized as a useful approach in testing a SEM. However, in this study, LISREL approach was estimated as much more useful method for research design.