Explaining Interaction Effects Within and Across Levels of Analysis

Many manuscripts submitted to the Journal of International Business Studies propose an interaction effect in their models in an effort to explain the complexity and contingency of relationships across borders. In this article, we provide guidance on how best to explain the interaction effects theoretically within and across levels of analysis. First, in the case of interactions within the same level of analysis, we suggest that authors provide an explanation of the mechanisms that link the main independent variable to the dependent variable, and then explain how the interaction variable modifies these mechanisms. Moreover, to ensure that the arguments are theoretically complete, we suggest that authors theoretically rule out the potential reverse interaction effect between the main variable and moderating variable. Second, in the case of interactions across levels of analysis, we suggest that authors identify the cross-level nature of the moderating relationships, specify the level of analysis of the main relationship and the nested nature of the cross-level influences, and theoretically explain these cross-level influences. Additionally, we suggest that authors pay particular attention to nesting in order to theoretically rule out reverse interactions.