Nicos Nicolaou’s research while affiliated with SECO/WARWICK and other places

We leverage a rich online social network and entrepreneurial performance dataset to identify the effect of entrepreneurs’ social network activity on their professional success. We focus our analysis on ~79K founders of organizations listed in Crunchbase with an active personal Twitter account. We employ Ordinary Least Squares (OLS) multiple linear regression, where the dependent variable is the founder’s career success indicator as extracted from Crunchbase, and the predictor variables are the social network presence and activity indicators as extracted from Twitter. We find that the founder’s average annual number of tweets is negatively associated with different success indicators, demonstrating a significant adverse impact of mere tweeting on success. To address endogeneity concerns, we implement panel data analysis with Fixed Effects (FE) and Instrumental Variables (IV) by the means of Two-Stage Least Squares (2SLS) regression, the results of which are largely consistent with those of OLS main analysis.

Tertius iungens brokering that brings together people who might not otherwise meet is crucial for organizational effectiveness. But we know little about whether and why women and men differ in their propensity to engage in this brokering. Our paper focuses on the origins and mitigation of gender differences in the propensity to bring people together. In study 1, we showed that the Totterdell et al. (2008) propensity-to-join-others scale that we used in study 2 and the Obstfeld (2005) tertius iungens scale overlapped not only conceptually, but also empirically, and that these measures of tertius iungens were distinct from mediation- and separation-brokering propensities (Grosser et al. 2019). In study 2, we used a natural experiment to examine the tertius iungens brokering propensities of 876 identical and 625 fraternal same-sex twins. We found that brokering propensity was lower for women than for men, although the propensity toward sociability in terms of making friends and acquaintances was lower for men. We also found that for women, relative to men, tertius iungens brokering propensity was largely affected by environmental influences, such as the experience of stereotyping and discrimination, rather than representing an inherited disposition. Moreover, the differences between men and women with respect to brokering were mitigated for empowered samples, such as well-educated or entrepreneurial individuals. Our research asks new questions about how environmental pressures and empowerment affect social networking. Gender differences in brokering may be amenable to mitigation through empowering practices that include education and entrepreneurial experience.

Facial appearance has been associated with leader selection in domains where effective leadership is considered crucial, such as politics, business and the military. Few studies, however, have so far explored associations between facial appearance and entrepreneurship, despite the growing expectation that societies project on entrepreneurs for providing exemplary leadership in activities leading to the creation of disruptive start-ups. By using computer vision tools and a large-scale sample of entrepreneurs and non-entrepreneurs from Crunchbase, we investigate whether three geometrically based facial characteristics - facial width-to-height ratio (fWHR), cheekbone prominence, and facial symmetry - as well as advanced statistical models of whole facial appearance, are associated with a) the likelihood of an individual to emerge as an entrepreneur and b) the performance of the company founded by that individual. We find that cheekbone prominence, facial symmetry and two whole facial appearance statistical models are associated with the likelihood of an individual to emerge as an entrepreneur. In contrast to entrepreneurship emergence, none of the examined facial characteristics are associated with performance. Overall, our results suggest that facial appearance is associated with the emergence of leaders in the entrepreneurial endeavor, however, it is not informative about their subsequent performance.

Sentiment analysis is an evolving field of study that employs artificial intelligence techniques to identify the emotions and opinions expressed in a given text. Applying sentiment analysis to study the billions of messages that circulate in popular online social media platforms has raised numerous opportunities for exploring the emotional expressions of their users. In this paper we combine sentiment analysis with natural language processing and topic analysis techniques and conduct two different studies to examine whether engagement in entrepreneurship is associated with more positive emotions expressed on Twitter. In study 1, we investigate three samples with 6.717.308, 13.253.244, and 62.067.509 tweets respectively. We find that entrepreneurs express more positive emotions than non-entrepreneurs for most topics. We also find that social entrepreneurs express more positive emotions, and that serial entrepreneurs express less positive emotions than other entrepreneurs. In study 2, we use 21.491.962 tweets to explore 37.225 job-status changes by individuals who entered or quit entrepreneurship. We find that a job change to entrepreneurship is associated with a shift in the expression of emotions to more positive ones.

The past decade has experienced a significant increase in the number of papers on the biology of entrepreneurship. This trend is aligned with the general interest in the biology of management studies as evidenced by the more than 300 articles already published (Nofal et al., 2018). It illustrates the progression of science along two dimensions. First is the drive to seek smaller units of analyses to identify the core mechanisms of action. Second is the opposing drive to seek larger units of analyses to identify general principles. These simultaneous processes move our understanding of social and natural phenomena closer to a unified theory. In this editorial, we reflect on how the biology of why, how, what, when, and where of entrepreneurship represents a natural progression from the institutional, organizational, and psychological explanations. We call this the biological perspective in entrepreneurship (BPE), which is illustrated by the papers in this volume. We examine the key domains of inquiry, various methodologies, and reflect on the directions that future research should take.

Although prior research has shown that risk-taking preferences and choices are correlated across many domains, there is a dearth of research investigating whether these correlations are primarily the result of genetic or environmental factors. We examine the extent to which common genetic factors account for the association between general risk-taking preferences and domain-specific risk-taking preferences, and between general risk-taking preferences and risk taking choices in financial investments, stock market participation and business formation. Using data from 1898 monozygotic (MZ) and 1344 same-sex dizygotic (DZ) twins, we find that general risk-taking shares a common genetic component with domain-specific risk-taking preferences and risk-taking choices.

Does genetic distance between countries explain differences in the level of entrepreneurship between them? Genetic distance, or very long-term divergence in intergenerationally transmitted traits across populations, has been recently tied to a variety of outcomes ranging from differences in economic development to differences in risk preferences between countries. Extending this recent work, we ask whether the genetic distance between countries is associated with differences in new firm entry. Based on a sample of 103 countries and 5253 country-pair observations and controlling for a large variety of factors, we find that genetic distance is positively associated with between country differences in new firm entry. The effects sizes, as expected, are small. In assessing the differences in entrepreneurial activity between country-pairs, policymakers could consider adjusting for genetic distance as an explanation for differences in entrepreneurial activity.