Friends of the Behavioral Economics Blog, this week we present the paper “How can biases affect entrepeneurial decision making? Toward a behavioral approach to unicorns”, by Abatecola, G.; Cristofaro, M.; Giannetti, F. and Kask, J. (2021), in which authors analyze what cognitive biases affect the decision-making process when it comes about unicorn companies.
How can cognitive biases influence the birth and evolution of entrepreneurial ventures?
Business research is increasingly focusing on analyzing decision-making in entrepreneurship. Commonly, these are decisions regarding opportunity recognition (discovering and recognizing potential opportunities), opportunity evaluation, and opportunity exploitation (it is said, for economic benefit).
Over time, it is a fact that business entrepreneurship decision making coincides with the survival, success or failure of the company.
Many experts have pointed out that entrepreneurs rely heavily on cognitive biases in their decision making. Biases would be the product of cognitive-emotional intertwining in decision making, and their appearance depends mainly on personal experience, the entrepreneur’s network of contacts and his/her capital.
However, the implications of many biases in business, how they interact, and the link to other factors are still unknown. In a nutshell, we still have a big puzzle in front of us.
This article aims to explain what entrepreneurial biases can appear when investors, company founders, and other important stakeholders make decisions that shape the birth and evolution of unicorn companies.
These are, simply put, startups whose very fast grow has provided them with a lot of capital. The aim would be to analyze what cognitive mechanisms impact their formation and growth.
Zhang and Cueto proposed in 2017 to advance in the study of biases in entrepreneurship. Specifically, consider that there were three types of bias to be aware of.
First, the “happy” biases. These tend to reduce the perception of risk and have both positive and negative effects on performance. They occur mainly due to the inexperience of the entrepreneurs, their young age, the environmental complexity, the risk of the contexts, etc.
Then the “incomplete attributes” biases appear. These lead people to pay attention to one attribute, even though there are others that are more relevant, tending to reduce the perception of risk. They occur mainly because of the network of contacts and the personal capital of entrepreneurs.
Lastly, “psychophysical” biases would appear. It refers to the variations in the human perception of certain attributes; however, it is a very little studied category.
Then, what would be the stages to study in the development of unicorn companies? Birth, transition and consolidation.
At birth, it is believed that “happy” biases would intervene. For example, when making a decision, people can recall the most vivid memories of a specific situation, this is called recall and is often intertwined with similarity (this would be an “incompleteness” bias). That is, there would be a tendency to evaluate more positively what is similar to oneself.
In the transition stage, decision makers often unconsciously seek only information that reinforces their emotionally charged point of view. That is, “happy” biases, while avoiding information that may contradict them.
Regarding the consolidation stage, the choice of decision makers is reinforced over time due to positive and circular feedback. This would increasingly lead them to discard information that does not reinforce this mechanism, which could cause a decision block.
Consequently, within consolidation, investors and founders can focus on continuing growth strategies. That is, both founders and investors tend to reinforce each other and escalate in commitment, legitimizing the unicorn company.
Authors consider that understanding the main cognitive mechanisms is the key to properly interpret the decision-making process in companies in general and unicorns in particular. Therefore, they hope that what is proposed in the article contributes to a better understanding of how these multimillion-dollar companies operate.
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