Importance-performance map analysis (IPMA) of PLS-SEM results.Short recap on the fundamentals of PLS-SEM model evaluation.More specifically, participants will understand the following topics: The objectives of this course are to (1) provide advanced knowledge on the PLS-SEM approach, (2) gain insights on additional analysis methods within the PLS-SEM modeling framework that increase your publication success, and (3) improve your PLS-SEM modeling and analytical skills. This course has been designed to familiarize participants with the potentials of using the multivariate analysis method PLS-SEM in their research. Take a look at recent PLS-SEM publications ! PLS-SEM has become a standard method in researchers' multivariate analysis toolbox as evidenced in numerous methodological extensions and reviews in disciplines as diverse as Human Resource Management ( Ringle et al., 2018), Hospitality Research ( Ali et al., 2018), Information Systems Research ( Hair et al., 2017), Management Accounting ( Nitzl, 2016), International Business ( Richter et al., 2016), Tourism ( do Valle and Assaker, 2016), Psychology ( Willaby et al., 2015), Supply Chain Management ( Kaufmann and Gaeckler, 2015), Family Business ( Sarstedt et al., 2014), Operations Management ( Peng and Lai, 2012), Strategic Management ( Hair et al., 2012), Marketing ( Hair et al., 2012), Management Information Systems ( Ringle et al., 2012), Accounting ( Lee et al., 2011), and International Marketing ( Henseler et al., 2009). Furthermore, PLS-SEM allows to estimate reflective and formative constructs and generally offers much flexibility in terms of data requirements. Compared to other SEM techniques, PLS-SEM allows researchers to estimate very complex models with many constructs and indicator variables.
#Smartpls advanced full
“This book provides all the essentials in comprehending, assimilating, applying and explicitly presenting sophisticated structured models in the most simplistic manner for a plethora of Business and Non-Business disciplines.” – Professor Siva Muthaly, Dean of Faculty of Business and Management at APU.Ĭlick here to see full contents.PLS-SEM is a composite-based approach to SEM, which aims at maximizing the explained variance of dependent constructs in the path model. Filled with useful illustrations to facilitate understanding, you’ll find this guide a go-to tool when conducting marketing research. Coupled with business examples and downloadable datasets for practice, the guide includes step-by-step guidelines for advanced PLS-SEM procedures in SmartPLS, including: CTA-PLS, FIMIX-PLS, GoF (SRMR, dULS, and dG), HCM, HTMT, IPMA, MICOM, PLS-MGA, PLS-POS, PLSc, and QEM. Ken Kwong-Kay Wong wrote this reference guide with graduate students and marketing practitioners in mind. When applied correctly, PLS can be a great alternative to existing covariance-based SEM approaches.ĭr. Marketers can use PLS to build models that measure latent variables such as socioeconomic status, perceived quality, satisfaction, brand attitude, buying intention, and customer loyalty. Partial least squares is a new approach in structural equation modeling that can pay dividends when theory is scarce, correct model specifications are uncertain, and predictive accuracy is paramount.