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Beyond Statistical Power and Significance in Entrepreneurship and Management Research
Abstract
Findings in most empirical research on entrepreneurship and management focuses on a few things: statistical representativeness of the data, the methodological rigor used for arriving at the results, and the statistical power of the results. However, both results and data are far from being free of criticism. This chapter provides a way forward that uses the mixed-methods approach without falling into the common confusion of multiple methods used in one research. It looks back at the reliance of statistical testing, null-hypothesis, and testing the statistical significance as the criteria. It explores available alternatives that can offer to overcome the problem of non-significance, rather than rejecting it as is usually done. It acknowledges some quantitative solutions like replication, conjoint, and comparative analyses and extends the use of some qualitative methods like exploratory methods, case studies, and theory development studies that offer alternatives to treating the presence or absence of significance. It discusses the concepts used and gives the limitations of the study.
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