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Apply PLS-SEM Method in Minutes. With No Headaches!

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Joe F. Hair, DBA Director, Cleverdon Chair of Business, University of South Alabama, USA

SmartPLS 3 is a milestone in latent variable modeling. It combines state of the art methods (e.g., PLS-POS, IPMA, complex bootstrapping routines) with an easy to use and intuitive graphical user interface.

Joe F. Hair, DBA Director, Cleverdon Chair of Business, University of South Alabama, USA

Running your SmartPLS analyses is fun and hassle free.

Get deep insights into your data easily!

SmartPLS Modeling Environment
The powerful modeling environment lets you create a path model in minutes.
SmartPLS Project Manager
The project manager helps you to keep track of all your analyzes and files.
SmartPLS Colors and Fonts Customization
Customize your model with colors, borders and fonts to underline your ideas individually!
SmartPLS Algorithm Explanations
In-built explanations of the algorithms and meaningful defaults give you an easy start into the PLS-SEM world.
SmartPLS Result Reports
Well-organized reports provide full insights into your results.
SmartPLS HTML and Excel Export
Save your results permanently as HTML report or Excel file.
SmartPLS Datagroup Analysis
Create data groups to run multi group analyses effortlessly.
SmartPLS Moderating Effects
Create interaction terms and run moderator analyses without any problems.

SmartPLS is the workhorse for all PLS-SEM analyses - for beginners as well as experts

Here is our (constantly growing) list of all available calculation methods. Relevant innovative algorithms will also be made available in SmartPLS within a short time. We promise.

  • Partial least squares (PLS) path modeling
  • Ordinary least squares (OLS) regression based on sumscores
  • Consistent PLS (PLSc)
  • Weighted PLS (WPLS), weighted OLS (WOLS) and weighted consistent PLS (WPLSc)
  • Bootstrapping and the use of advanced bootstrapping options
  • Blindfolding
  • Importance-performance map analysis (IPMA)
  • PLS multi-group analysis (MGA): Analyses the difference and significance of group-specific PLS path model estimations
  • Higher-order Models
  • Mediation: Estimation of indirect effects and their bootstrap-based significance testing
  • Moderation: Estimation of interaction effects and their bootstrap-based significance testing
  • Nonlinear relationships: Estimation of quadratic effects and their bootstrap-based significance testing
  • Confirmatory tetrad analysis (CTA): A statistical technique which allows for empirical testing the measurement model setup
  • Finite mixture (FIMIX) segmentation: A latent class approach which allows identifying and treating unobserved heterogeneity in path models
  • Prediction-oriented segmentation (POS): An approach to identify groups of data
  • PLS Predict: A technique to determine the predictive quality of the PLS path model
  • Prediction-oriented model selection
Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)
Available on Amazon
Get started with PLS-SEM! With applications using SmartPLS, the primary software used in partial least squares structural equation modeling (PLS-SEM), this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM)
Available on Amazon
Learn Advanced PLS-SEM Techniques! This book provides a concise yet very practical guide to understanding and applying advanced concepts and approaches of PLS-SEM. With research questions becoming more sophisticated and data more readily available, researchers need to apply more advanced SEM analyses, which are increasingly being requested by journal editors and reviewers. This is the first book that equips researchers with a sound understanding of and the competencies to apply advanced PLS-SEM approaches. This text includes easy-to-follow examples of the SmartPLS 3 software.

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SmartPLS Korea

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SmartPLS Iran

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SmartPLS China and Taiwan

Germany

SmartPLS Germany

I have a long background in technology IT (product management and engineering) and I¹ve developed applications for many years. I think that SmartPLS 3 is the nicest SEM product on the market, today, and I definitely prefer using it instead of rather antiquated tools like AMOS and MPLUS.

Lori D. Kendall, Ph.D. Student in Management, Case Western Reserve University

I recommend SmartPLS to my students, and one of my graduate student is preparing his Ph.D. thesis with SmartPLS program. He is very happy to solve the difficulty of dealing with hard data for his analysis.

DaeShik Park, Professor, Chungnam National University, Korea

PLS-SEM is a key multivariate analysis method for researchers and scholars. SmartPLS 3 gives easy access to the method. I profited in my research and Ph.D. theses from the intuitive ways to draw models and to easily get the outputs with graphics for many useful analyses.

Julen Castillo Apraiz, Ph.D. Researcher, University of the Basque Country, Spain

Having become familiar with PLS, and especially the SmartPLS tool, I have applied the technique to the Metlife Customer Satisfaction Survey data across multiple markets. The results are very useful and, thanks to SmartPLS, very easy to compute."

Martin Caplin, Metlife, United Kingdom.

Covariance-based approach limits lead us to use the variance based approach and smartpls software. Many studies done in this area. for expanding this approach among researchers with Persian language we written a book with collaboration my friends. It seems that this approach will soon become an integral part of most analysts, especially in the realm of social sciences. The new version of the software is more comprehensive, and especially at the CTA has attracted many comments. This software can help researchers to comprehensive understanding of develop and evaluate of the measurement and structural models."

Rasoul Gholamzadeh, Faculty Member of Payam Noor University, Iran
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