Cause-effect relationships in PLS path models imply that exogenous constructs directly affect endogenous constructs without any systematic influences of other variables. In many instances, however, this assumption does not hold, and including a third variable in the analysis can change our understanding of the nature of the model relationships. The two most prominent examples of such extensions include mediation and moderation.
Mediation occurs when a third variable, referred to as a mediator variable, intervenes between two other related constructs. More precisely, a change in the exogenous construct results in a change of the mediator variable, which, in turn, changes the endogenous construct. Analyzing the strength of the mediator variable’s relationships with the other constructs allows substantiating the mechanisms that underlie the cause-effect relationship between an exogenous construct and an endogenous construct. In the simplest form, the analysis considers only one mediator variable, but the path model can include a multitude of mediator variables simultaneously.
When moderation is present, the strength or even the direction of a relationship between two constructs depends on a third variable. In other words, the nature of the relationship differs depending on the values of the third variable. As an example, the relationship between two constructs is not the same for all customers but differs depending on their income. As such, moderation can (and should) be seen as a means to account for heterogeneity in the data.
Mediation and moderation are similar in that they describe situations in which the relationship between two constructs depends on a third variable. There are fundamental differences, however, in terms of their theoretical foundation, modeling, and interpretation. In this chapter, we explain and differentiate mediation and moderation, as well as illustrate their implementation using the corporate reputation PLS path model.
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