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- Uncovering the affective turmoil during opportunity recognition and exploitation: A nonlinear approachPublication . Santos, Susana Correia; Caetano, Antonio; Costa, Silvia; Lopes, Rita Rueff; Silva, Ana Junça; Neumeyer, XaverThis study explores the affective turmoil experienced by nascent entrepreneurs during opportunity recognition and exploitation. Based on the affect circumplex model, we employed nonlinear methods to identify configurations of affect that emerge during these early stages of the entrepreneurial journey. We analyzed data from 50 nascent entrepreneurs using Artificial Neural Networks (ANNs) trained with twenty affect dimensions as input variables and opportunity recognition and opportunity exploitation as outcomes. Results show that nascent entrepreneurs experience different affect configurations during opportunity recognition and exploitation. While four configurations of affect emerged associated with opportunity recognition and exploitation, their nature and importance to the experienced event are significantly different. Specifically, “active screening” is the most important configuration of affect during opportunity recognition, while “vigilant” is the most important during opportunity exploitation. We posit that nonlinear methods can help to uncover the affective turmoil experienced by entrepreneurs during a particular event. These findings provide new insights on how affect associates differently with cognition during the early stages of entrepreneurship.
- Why am I so successful? Self-presentation and deliberative attributions of success in entrepreneurshipPublication . Santos, Susana Correia; Caetano, Antonio; Brochado, AnaThis study explores the complexities of causes of success mentioned in entrepreneurs’ narratives in a broadcasted context. Building on strategic self-presentation and attribution theories, we employed inductive methods to map the configurations of public narratives explaining entrepreneurial success. The data analyzed were gathered from 173 reflective interviews featuring entrepreneurs on the United States’ National Public Radio, using machine learning techniques for semantic content analysis. The results show that entrepreneurs can adopt three strategic presentation narratives to explain success in entrepreneurship. Significantly different patterns emerge in the three strategic narrative configurations. First, “lucky charming” narratives reflect an ingratiation strategy, mentioning external and uncontrollable causes of success to increase the entrepreneurs’ likability for the audience. Second, “work striving” narratives use self-promotion strategies to push for recognition of accomplishments, efforts, and intellectual abilities. Third, “social connecting” narratives simultaneously make use of ingratiation and exemplification strategies, including capitalizing on the positive signals given by the social support attracted during their entrepreneurial journey. These three discourse patterns have implications for influencing reputation and driving business- and personal-related outcomes. The findings provide a better understanding of deliberate appearances by entrepreneurs in broadcast contexts and tools for nascent entrepreneurs to leverage their role models among those with acclaimed entrepreneurial success.