Yes, it is possible to conduct a meta-SEM using Smart PLS4 software. Smart PLS4 is a software package that is specifically designed for partial least squares (PLS) modeling. PLS is a type of structural equation modeling (SEM) that is well-suited for analyzing data with small sample sizes and/or non-normally distributed data.

To conduct a meta-SEM using Smart PLS4, you will need to collect data from multiple studies that have used the same SEM model. You will then need to prepare the data for PLS analysis. This involves converting the data to a format that is compatible with Smart PLS4 and transforming the data to ensure that it meets the assumptions of PLS.

Once the data is prepared, you can then create a meta-SEM model in Smart PLS4. This involves specifying the latent variables in the model and the relationships between them. You can also specify the measurement models for each latent variable.

Once the model is created, you can then estimate the model parameters using the Smart PLS4 algorithm. Smart PLS4 will generate a variety of outputs, including the estimated path coefficients, standard errors, and p-values. You can then interpret the results of the meta-SEM to identify the relationships between the latent variables in the model.

Here are some additional tips for conducting a meta-SEM using Smart PLS4:

• Use high-quality data. The quality of the data will have a significant impact on the results of the meta-SEM. Therefore, it is important to use data from studies that have been well-designed and conducted.
• Use a consistent SEM model. All of the studies that you include in the meta-SEM should have used the same SEM model. This will ensure that the results of the meta-SEM are comparable.
• Use the appropriate PLS algorithm. Smart PLS4 offers a variety of PLS algorithms. You should choose the algorithm that is most appropriate for your data and research questions.
• Carefully interpret the results. The results of the meta-SEM should be interpreted carefully, taking into account the quality of the data and the limitations of the PLS method.

I hope this information is helpful. Good luck with your meta-SEM study!