The purpose of this study is to discuss best practices for the methods and results sections in quantitative international business (IB) studies, with emphasis on data collection, analytical techniques and additional robustness tests to improve replicability and reproducibility.
This paper reviews best practices in quantitative IB research. It focuses on three key themes: research design, data transparency and rigor. It analyzes exemplar studies in IB research and discusses specific challenges in emerging market contexts.
This paper identifies ways researchers can strengthen quantitative IB research, including (1) the importance of thorough research design documentation and justification, (2) the need for increasing transparency in data collection and analytical procedures, (3) the value of triangulation across methods, data sources and analytical techniques, and (4) guidelines for reporting results, including presentation of moderating effects and robustness tests.
The best practices and recommendations have important implications for scholars developing quantitative studies – increased transparency and rigor – both of which can improve the quality of a study. More broadly, they help researchers to enhance the credibility and replicability of quantitative research, particularly in dealing with cross-cultural and emerging market contexts. This study includes specific recommendations for handling data collection, analysis and presenting results.
Adopting best practices enhances the credibility of a study with practitioners (as well as the scholarly community).
This study discusses how failures to incorporate fully best practices can compromise the rigor of a study and introduce ethical issues.
This paper provides guidelines for strengthening quantitative research methods in IB. It addresses current challenges in research credibility and replicability while offering specific guidance for emerging market contexts. This study combines methodological best practices with practical examples from exemplar studies.
