• Journal of Information Technology Services
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• v.10 no.2
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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.

• Information Systems Review
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• v.16 no.3
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• pp.89-112
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• 2014

This tutorial presents an approach to perform the PLS structural equation modeling using the R. For this purpose, the practical guide defines the criteria for the PLS structural equation modeling by reviewing previous studies, and shows how to analyze the research model with an example using the "plspm" which is the R package for the performing PLS path analysis against the criteria. This practical guide will be useful for the study of the PLS model analysis for new researchers and will provide the knowledge base for in-depth analysis through the new PLS structural equation modeling technique using R which is the integrated statistical software operating environment for the researchers familiar with the PLS structural equation modeling.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.87-93
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• 2010

The partial least squares (PLS) method is popularly used for estimating the structural equation model, but the existing algorithm may not be directly implemented when probabilities are involved in some constructs or manifest variables. We propose a structural equation model including the brand choice as one construct having brand choice probabilities as its manifest variables. Then, we develop a PLS-based algorithm for the structural equation model by utilizing the multinomial logit model. A case is introduced as an application and simulation studies are performed to validate the proposed algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.64-70
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• 2013

Estimation approaches for casual relation model with high-order factors have strict restrictions or limits. In the case of ML (Maximum Likelihood), a strong assumption which data must show a normal distribution is required and factors of exponentiation is impossible due to the uncertainty of factors. To overcome this limitation many PLS (Partial Least Squares) approaches are introduced to estimate the structural equation model including high-order factors. However, it is possible to yield biased estimates if there are some differences in the number of measurement variables connected to each latent variable. In addition, any approach does not exist to deal with general cases not having any measurement variable of high-order factors. This study compare several approaches including the repeated measures approach which are used to estimate the casual relation model including high-order factors by using PLS (Partial Least Squares), and suggest the best estimation approach. In other words, the study proposes the best approach through the research on the existing studies related to the casual relation model including high-order factors by using PLS and approach comparison using a virtual model.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.117-124
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• 2015

As the acceptance of statistical analysis has been increased because of Big Data, the needs for an advanced second generation of statistical analysis method like Structural Equation Model are also increasing. This study suggests how R-Program, as open software, can be utilized when Partial Least Square Model, one of the SEMs, is applied to statistical analysis. R is a free software as a part of GNU projects as well as a powerful and useful tool for statistical analysis including Big Data. The study utilized R and SmartPLS, a representative statistical package of PLS-SEM, and analyzed internal consistency reliability, convergent validity, and discriminant validity of the measurement model. The study also analyzed path coefficients and moderator effects of the structural model and compared the results, respectively. The results indicated that R showed the same results with SmartPLS on the measurement model and the structural model. Therefore, the study confirmed that R could be a powerful tool that is alternative to a commercial statistical package in the future.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.1
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• pp.131-147
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• 2016

This study investigated the relationship between fashion behavior, impression management behavior, and career success. A conceptual model and hypotheses were established based on theoretical linkages between the constructs. Thereafter, empirical data were collected using a set of questionnaires. For this reason, the sample was taken from 720 office workers' who worked at 14's Korea Enterprise, 697 of which was used for an empirical analysis (sample: men over 30 years of age and more than three years continuous service). This study conducted an exploratory factor analysis and confirmatory factor analysis for the validity test. Cronbach's alpha test is used for the reliability test. Moreover, PLS structural equation modeling (SEM) was employed to test hypothesized relationships in the conceptual model (SPSS 20.0 window/Smart PLS 3.0). This study shows that the proposed model is reasonably fit to the actual data. The following results were obtained from the analyses. First, fashion behavior and impression management behavior is positively related to career success. The result shows that economics of the fashion behaviors sub-types were statistically more significant to influence career success. The self-focused of the impression management behavior sub-types were more than statistically significant to influence career success. This finding has great implications to understand self-management behavior and the career success of male office workers.

• The Journal of Industrial Distribution & Business
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• v.10 no.5
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• pp.7-20
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• 2019

Purpose - This study provides appropriate procedures for EFA to help researchers conduct empirical studies by using PLS-SEM. Research design, data, and methodology - This study addresses the absolute and relative sample size criteria, sampling adequacy, factor extraction models, factor rotation methods, the criterion for the number of factors to retain, interpretation of results, and reporting information. Results - The factor analysis procedure for PLS-SEM consists of the following five stages. First, it is important to look at whether both the Bartlett test of sphericity and the KMO MSA meet the qualitative criteria. Second, PAF is a better choice of methodology. Third, an oblique technique is a suitable method for PLS-SEM. Fourth, a combined approach is strongly recommended to factor retention. PA should be used at the onset. Next, it is recommended using the K1 criterion. In addition, it is necessary to extract factors that increase the total variance explanatory power through the PVA-FS. Finally, it is appropriate to select an item with a factor loading into 0.5 or higher and a communality of 0.5. Conclusions - It is expected that the accurate factor analysis processed for PLS-SEM as previously presented will help us extract more precise factors of the structural model.

• Journal of the Korean Society of Safety
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• v.28 no.2
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• pp.78-83
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• 2013

The traffic culture index is used as a major index in evaluating the traffic safety services of local governments and also serve as important data for the planning and implementation of traffic safety services. However, as the traffic culture index gradually became a standard for comparison among local governments, in part, certain cases arose which questioned the grounds for selecting variables for the index and the validity of the index in terms of its influential relationship between evaluation items. This study analyzed the index's influential relationship by utilizing a PLS structural equation model based on the evaluation results of the 2011 traffic culture index. A variable-linking model was created which recognized the relativity taking into account of the indirect effects between latent variables and this model was proven to be a model suitable in explaining the traffic culture index with a 97.8% explanation power. It was found that traffic safety(0.530), driving behavior(0.527), pedestrian behavior(0.187) and vulnerable road users(0.147), in such order, had an effect on the traffic culture index. It was also found that human casualties due to traffic accidents under "traffic safety" and traffic light compliance rate under "driving behavior" had an important effect. The study showed that motor vehicle share in illegal parking in school zones did not have a valid explanation power regarding "vulnerable road users".

• Korea Trade Review
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• v.44 no.6
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• pp.169-185
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• 2019

The purpose of this study is to analyze the structural relationships of perceived value, price sensitivity, and satisfaction between brand image and purchase intention of consumers who have experience of overseas direct purchase. This study collected questionnaires used to analyze these structural relationships. Using the R's plspm package, we analyzed the PLS (partial least squares) structural equation model. In order to examine the relationship between perceived value and price sensitivity, the research model was modified and analyzed. As a result, not only the adoption of the research hypothesis, but also the goodness of fit was higher than before the research model modifying, and the relationship between perceived value and price sensitivity was further verified. The modified research model has higher academic value, so it is necessary to select it as the final proposal model.

• Journal of Information Technology Applications and Management
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• v.30 no.6
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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.