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Fundamental research in physics has long been a prerequisite for computer scientists and engineers to design innovative products, such as laptops and cell phones. Technological innovations and fundamental research are both part of the so-called STEM fields (Science, Technology, Engineering, and Mathematics), which are known to substantially contribute to economic growth. However, the questions still remain: how much contribution do these fields make to both wealth accumulation and inequality at different levels of analysis? First, analyzing the lists of world’s wealthiest individuals, the Zipf plot analysis demonstrates that STEM billionaires contribute more to wealth inequality than their non-STEM counterparts. Analyzing the companies in the S&P500, we find that STEM firms contribute more to wealth inequality and have larger growth rates on average than the non-STEM firms. Finally, we show that the more STEM graduates in a country, the larger its GDP growth rate. In combination, we demonstrate that STEM is a fractal mechanism that drives wealth accumulation—and the wealth inequality— at different scales of economy—from individual wealth to firm valuation to country GDP. 

Over the last four decades, Academy of Management Review has devoted a great deal of attention to the scholarly debate about the theoretical nature of entrepreneurs, entrepreneurship, and entrepreneurial opportunities. Most recently, an entire Dialogue section of the journal was devoted to four articles that provided alternative ontological, epistemological, and philosophical views of “opportunity.” Inasmuch as the domain appreciates the effort to advance entrepreneurship theory, these arguments appear to constitute what past AMR editor-in-chief, Roy Suddaby, termed “fetishism,” where “theory becomes an exercise in writing and interpretation but is detached from the empirical world” (2014: 408). That reality was demonstrated in the Crawford, Aguinis, Lichtenstein, Davidsson, & McKelvey (2015) study, which discovered highly skewed power law distributions in all of the domain’s theoretically relevant input variables and all generalizable outcome measures. The significant number of outliers in these distributions provide necessary and sufficient cause for a paradigm shift in the domain. In response, this paper uses the empirical reality of power law distributed phenomena for 1) developing historical and empirical justification for the difficulties in building theory about opportunities and entrepreneurship, 2) identifying how the seemingly antithetical perspectives of discovery and creation theories can be synthesized, and 3) proposing a generalizable framework—of Endowments, Expectations, Engagement, and Environments—around which new entrepreneurship theory can be developed.