Does Estimation Methods in Structural Equation Modeling Impact Theory Development in Marketing?

2015 ◽  
pp. 84-84
Author(s):  
Ulf H. Olsson ◽  
Tor Wallin Andreassen ◽  
Kenneth Wathne
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Theory Development ◽  
Estimation Methods ◽  
Equation Modeling ◽  
Impact Theory

Challenges in Nonlinear Structural Equation Modeling

Methodology ◽  
2007 ◽  
Vol 3 (3) ◽  
pp. 100-114 ◽  
Author(s):  
Polina Dimitruk ◽  
Karin Schermelleh-Engel ◽  
Augustin Kelava ◽  
Helfried Moosbrugger
Keyword(s):  
Structural Equation Modeling ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Nonlinear Effects ◽  
Structural Equations ◽  
Estimation Methods ◽  
Equation Modeling ◽  
Parameter Estimates ◽  
Nonlinear Structural ◽  
Nonlinear Structural Equation

Abstract. Challenges in evaluating nonlinear effects in multiple regression analyses include reliability, validity, multicollinearity, and dichotomization of continuous variables. While reliability and validity issues are solved by employing nonlinear structural equation modeling, multicollinearity remains a problem which may even be aggravated when using latent variable approaches. Further challenges of nonlinear latent analyses comprise the distribution of latent product terms, a problem especially relevant for approaches using maximum likelihood estimation methods based on multivariate normally distributed variables, and unbiased estimates of nonlinear effects under multicollinearity. The only methods that explicitly take the nonnormality of nonlinear latent models into account are latent moderated structural equations (LMS) and quasi-maximum likelihood (QML). In a small simulation study both methods yielded unbiased parameter estimates and correct estimates of standard errors for inferential statistics. The advantages and limitations of nonlinear structural equation modeling are discussed.

scholarly journals Factors Affecting Satisfaction and Loyalty in Public Transport using Partial Least Squares Structural Equation Modeling (PLS-SEM)

2019 ◽  
Vol 8 (12) ◽  
pp. 569-575 ◽  
Keyword(s):  
Structural Equation Modeling ◽  
Least Squares ◽  
Partial Least Squares ◽  
Public Transport ◽  
Structural Equation ◽  
Theory Development ◽  
Equation Modeling ◽  
Factors Affecting ◽  
Effective Strategies ◽  
Transportation Research

With an increasing number of privately own vehicles in Malaysia, the popularity of public transports is increasingly challenged by ride-hailing services such as Grab, MyCar, JomRides and MULA. To develop effective strategies aimed at retaining users, it is necessary to understand the factors that affect users’ satisfaction and loyalty in public transport. In this study, we propose that satisfaction and loyalty in public transport are associated with five key factors: accessibility, reliability, perceived value, comfort, and safety and security. Data collected from a survey of 179 public transport users in Kuching city was used to test the research model. Partial least squares structural equation modeling (PLS-SEM) was used to analyse the data. The main findings were that safety and security, and reliability significantly affected the users’ satisfaction and loyalty in public transport, while no statistically significant relationship was found among accessibility, satisfaction and loyalty. These findings not only contribute to the theory development of transportation research but also help practitioners to develop novel strategies aimed at increasing public transport usage.

scholarly journals Tourism sector, Travel agencies, and Transport Suppliers: Comparison of Different Estimators in the Structural Equation Modeling

2015 ◽  
Vol 6 (1) ◽  
pp. 11-24 ◽  
Author(s):  
Nataša Kovačić ◽  
Darja Topolšek ◽  
Dejan Dragan
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Model ◽  
Estimation Methods ◽  
Equation Modeling ◽  
Estimation Of Parameters ◽  
Confirmatory Factor Analyses ◽  
Estimated Parameters ◽  
Tourism Sector ◽  
Travel Agencies

Abstract The paper addresses the effect of external integration (EI) with transport suppliers on the efficiency of travel agencies in the tourism sector supply chains. The main aim is the comparison of different estimation methods used in the structural equation modeling (SEM), applied to discover possible relationships between EIs and efficiencies. The latter are calculated by the means of data envelopment analysis (DEA). While designing the structural equation model, the exploratory and confirmatory factor analyses are also used as preliminary statistical procedures. For the estimation of parameters of SEM model, three different methods are explained, analyzed and compared: maximum likelihood (ML) method, Bayesian Markov Chain Monte Carlo (BMCMC) method, and unweighted least squares (ULS) method. The study reveals that all estimation methods calculate comparable estimated parameters. The results also give an evidence of good model fit performance. Besides, the research confirms that the amplified external integration with transport providers leads to increased efficiency of travel agencies, which might be a very interesting finding for the operational management.

The Effect of Latent and Error Non-Normality on Measures of Fit in Structural Equation Modeling

2021 ◽  
pp. 001316442110462
Author(s):  
Lisa J. Jobst ◽  
Max Auerswald ◽  
Morten Moshagen
Keyword(s):  
Structural Equation Modeling ◽  
Root Mean Square ◽  
Latent Variables ◽  
Structural Equation ◽  
Generalized Least Squares ◽  
Estimation Methods ◽  
Equation Modeling ◽  
Analytic Structure ◽  
Mean Square ◽  
Test Statistic

Prior studies investigating the effects of non-normality in structural equation modeling typically induced non-normality in the indicator variables. This procedure neglects the factor analytic structure of the data, which is defined as the sum of latent variables and errors, so it is unclear whether previous results hold if the source of non-normality is considered. We conducted a Monte Carlo simulation manipulating the underlying multivariate distribution to assess the effect of the source of non-normality (latent, error, and marginal conditions with either multivariate normal or non-normal marginal distributions) on different measures of fit (empirical rejection rates for the likelihood-ratio model test statistic, the root mean square error of approximation, the standardized root mean square residual, and the comparative fit index). We considered different estimation methods (maximum likelihood, generalized least squares, and (un)modified asymptotically distribution-free), sample sizes, and the extent of non-normality in correctly specified and misspecified models to investigate their performance. The results show that all measures of fit were affected by the source of non-normality but with varying patterns for the analyzed estimation methods.

Theory Development in Information Systems Research Using Structural Equation Modeling

2010 ◽  
pp. 77-94 ◽  
Author(s):  
Nicholas Roberts ◽  
Varun Grover
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Theory Development ◽  
Theoretical Models ◽  
Equation Modeling ◽  
Is Research ◽  
Significant Potential ◽  
Systems Research ◽  
Information Systems Research ◽  
Is Theory

Structural equation modeling (SEM) techniques have significant potential for assessing and modifying theoretical models. There have been 171 applications of SEM in IS research, published in major journals, most of which have been after 1994. Despite SEM’s surging popularity in the IS field, it remains a complex tool that is often mechanically used but difficult to effectively apply. The purpose of this study is to review previous applications of SEM in IS research and to recommend guidelines to enhance the use of SEM to facilitate theory development. The authors review and evaluate SEM applications, both component-based (e.g., PLS) and covariance-based (e.g., LISREL), according to prescribed criteria. Areas of improvement are suggested which can assist application of this powerful technique in IS theory development.

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