Welcome to our guide on creating your first regression model using SmartPLS! We suggest that you start with our step-by-step guide on how to create your first project and import data into SmartPLS. On these grounds continue with this tutorial, which will guide you through the following steps:

1. Creating a PLS path model
2. Estimating the model and evaluating the results

We will be using the enterprise reputation model from the textbooks "Primer on PLS-SEM" by Hair et al. (2022) and "Advanced PLS-SEM issues" by Hair et al. (2024) as a case study. These resources will provide more in-depth information on PLS-SEM and SmartPLS. If you prefer video tutorials, check out our video collection on PLS-SEM using SmartPLS 4.

Throughout the tutorial, we will be using SmartPLS to perform the analysis and visualize the results. Make sure you have downloaded and installed the software before beginning. Let's get started!

Fast lane

Why read when you can watch? For those who prefer video tutorials, James Gaskin's Fastlane video is a great resource for getting started.

Create your first PLS-SEM file

To create your first PLS path model, follow these steps:

1. Select your project in the Project list.
2. Click on PLS-SEM in the Main toolbar. The following dialog will open.
3. In this dialog, enter a name for your model file (e.g., My first SmartPLS model) and then press the Save button.
4. The Model editor will then open, allowing you to begin working with your new model.

Draw the PLS path model

Drag and drop indicators to create constructs

To create construct in the model:

1. Select indicators in the Indicators list on the left
2. Drag and drop these indicators to the Modeling canvas on the right
3. A text field will appear, allowing you to name the new construct.
4. If needed, amend the suggested name.
5. Press ENTER on your keyboard.

Now, drag and drop comp_1, comp_2, and comp_3 to create the COMP construct. Repeat these steps for the QUAL construct (using indicators qual_1 to qual_8) and the PERF construct (using indicators perf_1 to perf_5).

By default, all constructs are drawn with reflective relationships (arrows pointing from the construct to the indicators). You can flip the relationship to a formative one (arrows pointing from the indicators to the construct) by using a right-click on the latent variable and then choosing Invert measurement model from the context menu. Please do this for QUAL and PERF .

Connect constructs

To create relationships between your constructs in the model:

1. Select the Connect tool in the Main toolbar
2. Click on the starting construct with the left mouse button.
3. Move to the target construct.
4. Release the left mouse button.
5. This will create a relationship with an arrow pointing from the starting construct to the target construct.

Now create the necessary connections from QUAL to COMP and from PERF to COMP.

Estimate the model and open the results report

After creating your model, it's time to estimate the results using the Partial Least Squares Structural Equation Modeling (PLS-SEM) algorithm.

1. Click the Calculate button in the Main toolbar.
2. A list of available algorithms in the software will appear, from which you should select the PLS-SEM algorithm option.
3. The algorithm's dialog will open, allowing you to adjust certain parameters.
4. Just leave the default settings unchanged to start with.
5. Make sure the Open report checkbox is checked
6. Click Start calculation
7. The Results view will open automatically once the calculations are done.

Analyze the results

The Report navigation on the left side of the screen allows you to navigate the various PLS-SEM results. The PLS-SEM results provided by SmartPLS 4 software offer a comprehensive evaluation of the model, as discussed in the Hair et al. (2019, 2022) and Sarstedt et al. (2021) literature.

Significance testing of the PLS-SEM results

1. Click the Edit button to return to the Model view.
2. Click the Calculate button in the Main toolbar.
3. Select the Bootstrapping option, adjust settings if needed and click Start calculation.
4. The Bootstrapping result report will open and provide all the necessary information to conduct bootstrapping-based significance testing on your PLS-SEM results.

What’s next?

Congratulations on creating and estimating your first model in SmartPLS! To learn more about the process of creating and evaluating PLS-SEM models, we recommend checking out the "Primer on PLS-SEM" by Hair et al. (2022) and working through the step-by-step corporate reputation model example case study.

If you're interested in furthering your knowledge of PLS-SEM, consider joining one of our upcoming courses on the foundations and advanced topics PLS-SEM using SmartPLS. Alternatively, the PLS-SEM Academy offers video-based trainings on PLS-SEM if these courses don't fit into your schedule.

We hope that you have success with your future projects and wish you the best of luck!

References

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd Ed., Thousand Oaks, CA: Sage.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to Use and How to Report the Results of PLS-SEM. European Business Review, 31(1), 2-24.

Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2024). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd Ed., Thousand Oaks, CA: Sage.

Sarstedt, M., Ringle, C. M., & Hair, J. F. (2022). Partial Least Squares Structural Equation Modeling. In C. Homburg, M. Klarmann, & A. E. Vomberg (Eds.), Handbook of Market Research (pp. 587–632). Cham: Springer.