A highlight from Rock Star Theory: How to Explain and Predict Entrepreneurial Success



And welcome to research pod. Thank you for listening and joining us today. And this episode. We will be looking at the research of g. Christopher crawford at rutgers business school dr crawford explains which factors drive the performance of the most successful individuals and businesses. What do richard branson steve jobs and elon. Musk have in common. In addition to being finders of multibillion dollar companies they are also outliers art can be people businesses institutions or events depending on the specific context lying way outside the normal outliers we'd disproportionate influences on both the business world on society their inputs an puts either qualitative or quantitative in nature are considerably more diverse from those of the rest of the population. More often on. I-drive represents an exception to the normal rules. Dr g christopher crawford assistant professor of professional practice of entrepreneurship strategy and management out rutgers business school newark a new brunswick models. The emergence of art layers and entrepreneurship on develops a theory that is applicable to both academia and mainstream culture. He has closely examined more than twelve thousand companies. At various stages of development they encompass a broad spectrum ranging from small businesses employing only one or two people to behemoth companies boasting more than one million employees dr crawford. Undis- collaborators are particularly interested in high growth entrepreneurship. Which is the hallmark of the largest fastest growing companies. Their aim is to dissect the success of these high achievers which they call rockstars. Dr crawford has identified the anomalies and a set of variables that are common to all businesses namely the number of employees annual revenue on the growth of both overtime. He analyzed data sets from the s and p five hundred a stock market index measuring the stock performance of the five hundred largest publicly traded. Us companies on the inc. Five thousand the five thousand fastest growing private companies in both europe and the us. This revealed that each of these variables has distributed according to a par law were an overabundance of lars is so good that they skew the curve. Far to the right. crawford discusses hide these findings. Challenge a long held assumption. That the normal guy. She and distribution characterizes the variables of interest and the traditional bail shipped curve. A few observations are very good. A few very bad on most reside somewhere around the middle in normal distributions. Like this every observation can be accurately characterized by the main on some standard deviation from it the normality assumption applies to social science research. More generally were it serves as the underlying statistical principle for data analysis including hypothesis testing under this assumption art layers viewed as random statistical anomalies cold freaks under common data-processing practice is to have them clans from the data set thereby reducing the art liars true effects on the entire system. Dr crawford point site some of the most successful companies of our time such as apple amazon. Google and facebook are extremely liars. That changed the nature of higher. We engage with the world. They transformed what we do on how we think he argues that these companies have a significant impact on businesses on society as a whole therefore rather than fixing or excluding these exceedingly influential anomalies from our theories and data analysis. We should turn the spotlight on them.

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