Beyond addressing multicollinearity: Robust quantitative analysis and machine learning in international business research

We reconcile the recommendations made by Kalnins (J Int Bus Stud, 2022) on one hand and Lindner, Puck Verbeke Stud 51(3):283–298, 2020) other, how international business (IB) quantitative researchers should treat multicollinearity. explain that, in principle, treatment depends underlying data generation process, but note that datasets based any single process are rare. In doing so, we broaden discussion to include research methods be selected robust statistical models built. addition, highlight importance of a comprehensive literature review selecting appropriate control variables. also make suggestions addressing cross-level dependencies robustness checks avoid bias results. Finally, go beyond regression broader palette methodologies building machine-learning approaches.