Business Angel Decision Making
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Business Angels (BAs) are wealthy individuals whose investments in entrepreneurial ventures enable them to increase the likelihood of both attracting subsequent Venture Capital (VC) and achieving long-term venture success. Unfortunately more than 95% of entrepreneurs seeking funds from BAs are unable to do so, raising questions about whether this high failure rate might be reduced. Scholars suggest the answer lies in gaining a better understanding of the investment decision process itself and identifying why opportunities are rejected at each stage of the decision process. However, the private nature of the interaction between BA and fund-seeking entrepreneur constrains our ability to observe the multistage nature of the interaction and how rejection reasons change at each stage. As a consequence, much research relies on BA’s biased post-decision recollections, which limits our ability to understand the decision process and identify opportunities for improvement. In this research we overcome these constraints by observing interactions from the reality TV show Dragons’ Den, where fund-seeking entrepreneurs pitch their early stage businesses to five BAs. During the interaction, each BA must either make an offer to invest or provide a reason for rejection. We develop hypotheses about why this complex decision evolves over several stages, and why rejection reasons change at each stage, which we then test by coding observations and decision outcomes. We draw on research in behavioral economics and decision making to propose that BAs use heuristics to reduce their decision making effort at each stage and initially examine the criteria that are easiest to retrieve. They then assesses each opportunity based on the most easily retrieved criteria and reject those they believe unlikely to achieve their aspiration level for required return, or because the risk of failure exceeds the BA’s own risk aspiration level. We propose that during subsequent stages of the interaction, each BA audits the entrepreneur’s behaviors to assess performance and relationship risk, rejecting those where the risk level exceeds their aspiration level. We use trained observers to code the information exchanges and behavioral cues provided by the entrepreneur to find support for our hypotheses. We observe that, during the venture assessment stage, BAs do reject opportunities that fail to reach aspiration levels for investment return or investment risk, however, contrary to normative assumptions we find BAs do not trade off investment risk for investment return. For opportunities not rejected, we observe BAs assess how the entrepreneur’s behaviors and decisions inform their assessment of managerial risk and increase the likelihood of venture failure. We note BAs are more likely to reject entrepreneurs whose behaviors indicate low level of capabilities, experiences or traits, while excess traits can also increase this likelihood. For opportunities not rejected at this stage, we observe BAs audit the entrepreneur’s trust behaviors to inform their assessment of the relationship risk. We find BAs more likely to reject entrepreneurs who damage or violate trust in comparison to those who build trust. We also observe that BAs invest in entrepreneurs who damage trust, but only if they can introduce appropriate behavioral controls. Our observations help explain the multistage nature of the decision process and why opportunities are rejected at each stage. We suggest that better prepared entrepreneurs who display appropriate behaviors are less likely to be rejected. Increased understanding of the decision process enables BAs to improve their decision-making, while knowledgeable policy makers will be better able to cost-effectively deploy appropriate resources to enhance funding activities. Our observations should encourage academics to further explore entrepreneurial behaviors, perhaps adapting our research method and coding schema in future research.
Cite this version of the work
Andrew Maxwell (2012). Business Angel Decision Making. UWSpace. http://hdl.handle.net/10012/6484