Restriction of variance interaction effects and their importance for international business research

Abstract

A recent Journal of International Business Studies editorial on interaction effects within and across levels highlighted the importance of and difficulty associated with justifying and reporting of such interaction effects. The purpose of this editorial is to describe a type of interaction hypothesis that is very common in international business (IB) research: the restricted variance (RV) hypothesis. Specifically, we describe the nature of an RV interaction and its evidentiary requirements. We also offer several IB examples involving interactions that could have been supported with RV arguments. Our hope is that IB researchers can use this paper to bolster their arguments for interaction hypotheses by explaining them in terms of RV.

An overview of Hofstede-inspired country-level culture research in international business since 2006

“…The interpretation of marginal effects in (multilevel) interaction models however can be challenging. Only recently has the literature provided accessible articles and analytical techniques for an easier statistical assessment and conceptual explanation of how to estimate marginal effects in interaction models (Aguinis, Gottfredson, & Culpepper, 2013;Bowen, 2012;Brambor, Clark, & Golder, 2006;Cortina, Köhler, & Nielsen, 2015). In addition, software packages on how to estimate and present effect sizes have become publicly available, which too has facilitated the examination of effects sizes.…”

What’s in a p? Reassessing best practices for conducting and reporting hypothesis-testing research

“…• alternative proxies of focal constructs (i.e., variables mentioned in the hypotheses as independent or explanatory variables), especially for those that involve abstract concepts that cannot be measured directly; • alternative sets of control variables, especially when correlation is present in the dataset between a focal explanatory variable and a control variable; and/or • alternative functional forms of the regression models, especially for the hypotheses that suggest nonlinear effects (Haans et al, 2016;Meyer, 2009), or moderating or mediating effects (Andersson et al, 2014;Cortina et al, 2015).…”

From the Editors: Can I trust your findings? Ruling out alternative explanations in international business research

“…BUSINESS RESEARCH Trusting the findings from empirical analyses has a longer tradition and there are already several JIBS editorials that have analyzed ways to handle the analysis of large samples (e.g., Andersson et al, 2014;Cortina et al, 2015;Peterson et al, 2012;Reeb et al, 2012). To complement and extend these ideas, in this editorial we analyze how to use controls in IB.…”

“…Controls are particularly important in quantitative IB research, which is characterized by analyzing complex phenomena, often spanning multiple disciplines, theories and levels of analysis. The study of cross-border phenomena not only adds an additional layer of country-level influences to the relationships, but can also modify how such relationships operate as new mechanisms emerge that alter existing arguments (Andersson et al, 2014;Cortina et al, 2015). This complexity is the source of new insights on the behavior of economic actors that extend not only IB theory but also theories developed with a single country in mind.…”

“…This additional complexity emerges from several sources: from the cross-border relationships that organizations engage in as they have to deal with differences in economic, political, social, and geographic conditions; from the cross-country comparison of relationships that take into account additional variation in how the environment shapes relationships; and from the inclusion of the country level of analysis that alters relationships at lower levels of analysis. Previous editorials have explained how to deal with some of these issues by, for example, providing suggestions on how to: explain interaction effects within and across levels of analysis (Andersson, Cuervo-Cazurra, & Nielsen, 2014;Cortina, Köhler, & Nielsen, 2015), address multilevel challenges (Peterson, Arregle, & Martin, 2012), solve endogeneity problems (Reeb, Sakakibara, & Mahmood, 2012), improve qualitative research (Birkinshaw, Brannen, & Tung, 2011), address common method challenges (Chang, Van Witteloostuijn, & Eden, 2010), improve the theoretical identification of relationships (Bello & Kostova, 2012;Thomas, CuervoCazurra, & Brannen, 2011), and more generally how to benefit from, and deal with, the inherent interdisciplinary nature of IB research (Cantwell & Brannen, 2011;Cantwell, Piepenbrink, & Shukla, 2014;Cheng, Birkinshaw, Lessard, & Thomas, 2014;Cheng, Henisz, Roth, & Swaminathan, 2009).…”