Now that’s interesting and important!

Research Paper Title:

“Now that's interesting and important! Moving beyond averages to increase the inferential value of empirical findings in entrepreneurship research”

Authors:

Scott L. Newbert (Baruch College)
Romi Kher (Baruch College)
Shu Yang (Hofstra University)

Background:

The authors as entrepreneurship scholars need not choose between doing research that is "interesting" (Davis, 1971) and research that is "important" (Tihanyi, 2020). Rather, the authors can achieve both ends by acknowledging the role context plays in our discipline and designing our research so that it enables us to dig beneath the surface of our samples and explore and exploit their heterogeneity. Given the attention that has heretofore been given to what types of theories and/or phenomena scholars should study, The authors focus on how scholars can actually test them in order to generate more unexpected, counterintuitive, interesting results that can provide more accurate answers to the relevant, real-world, important problems entrepreneurs face. To this end, the authors propose a non-exhaustive list of empirical approaches that can enable scholars to look past the initial sample-wide averages that most statistical analyses provide in order to explore the nuances that exist beneath the surface of those findings. By contextualizing our research in these ways, scholars can better understand where, when, and for whom a given finding is (or is not) true, thereby increasing the inferential value of our findings.

Highlights:

• Entrepreneurship research that relies on averages ignores the discipline's dynamism.

• By exploring the context, scholars can explore and exploit the heterogeneity of our data.

• The authors highlight approaches and methods that can help researchers explore context.

• Contextualizing empirical research can yield more interesting and important findings.

Results:

By employing an empirical generalization design with subgroup analysis, our illustrative example shows that empirical findings for a sample as a whole do not hold for various subgroups, providing evidence that empirical results are dependent upon context.

Conclusion:

Entrepreneurship research that relies on averages ignores the discipline’s dynamism. Exploring contexts, such as employing the analytical approaches and empirical methods the authors highlight, can help researchers better explore and exploit the heterogeneity of entrepreneurship data. Contextualizing empirical research can, in turn, yield more interesting and important findings