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You describe a reflective-formative higher-order construct. And it seems you model it by using the repeated indicator approach. Such a model is generally valid, but comes with some problems. 1) As you describe it does not allow you to assess the R² etc. because the endogenous construct in your model...

You should find the same results given that you have used the same data and algorithm settings. If you continue to find differences please send the project including data and model to our support: https://support.smartpls.com/

If you have a problem with common method bias there is not much you can do, but collect new (better) data. Harman's single factor test is usually very insensitive to common method bias. It has been critizied in the literature for this problem. Thus, if it detects a bias there is likely a problem in ...

There is no literature on this yet.

I agree that Figure 8 is misleading and I would have liked to present it differently, but some of the co-authors think it is better this way. Why? The estimation Mode A and Mode B are not necessarily linked to the mode of measurement (reflective / formative). SmartPLS uses as a default Mode A for re...

Identification is realtively simple in PLS. PLS models are theoretically identified if each construt is connected to at least one other construct. If you have a higher-order construct it means that your higher-order construct needs to be connected to at least one other construct which is not one of ...

Please see for example this discussion:
viewtopic.php?f=5&t=25924

Low R² means that you are not able to explain much variance in your dependent variable. That can have several reasons. For example, your DV is very noisy (i.e., has a lot of variance). This may be because of error variance or because of many things contribute to the DV and your predictor is only one...

You may want to read the Primer on PLS-SEM to get a basic understanding of the method and evaluation:
https://www.smartpls.com/documentation/ ... s-sem-book

You have to calculate that yourself using the data provided under Path Coefficients > Samples

The interpretation of standardized coefficients is: when you increase the IV by one standard deviation, the DV increases by 0.53 standard deviations. It is a dimension-less measure, similar to a correlation (but not necessarily bound between -1 and 1). If all you indicators are on the same scale you...

The index of moderated mediation is given by p2*p5. You can find this as the specific indirect effect of Y1*M -> Y2 -> Y3. This is exactly p2*p5. You can assess its significance using bootstrapping.

Maybe there is simply no relationship between your variables in your context? Or you have the wrong predictors?

The p-values are based on a true null, which might not be very useful. It is only the standard option in bootstrapping. However, 1) I would not use typical p-value / t-value test here because the distribution of the reliabilities is unknown, hence I would use bootstrap confidence intervals. 2) confi...

You need to run the IPMA also for the first-stage model and then take the unstandardized latent variables scores as indicators into the next stage. This is something that I would generally recommend, as you will get the same standardized results, but have some additional flexibility. For example, it...