Research in international entrepreneurship (IE) is inherently complex, spanning cross-border opportunity recognition, international new ventures, born global firms, and the role of entrepreneurial ecosystems across institutional environments (Oviatt & McDougall, 1994; Knight & Cavusgil, 2004; Autio et al., 2011; Reuber et al., 2018). These characteristics demand the application of methodologically sophisticated research designs capable of capturing the multilevel, contextual, and dynamic causal structures that distinguish IE phenomena. This editorial clarifies whether and how researchers using partial least squares structural equation modeling (PLS-SEM) can address key challenges in IE research. We explain how researchers can benefit from the advanced capabilities of PLS-SEM—either as a stand-alone method or in triangulation efforts that leverage complementary approaches including qualitative data analyses, fuzzy-set qualitative comparative analyses (QCA), and necessary condition analyses (NCA). We review the IE literature for PLS-SEM applications and identify considerable room for improvement in the application of advanced capabilities and the triangulation of PLS-SEM with asymmetric and necessity-based techniques. Our seven-point research agenda provides a roadmap for bridging the methodological gap in IE research.
