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Note: This paper was originally published in 2018 as part of my Love Award research project at Elon University. Minor edits have been made in this version.
Acknowledgments
I am greatly indebted to Dr. Adam Aiken, my research mentor and advisor. This research could not have been made possible without his mentorship, guidance, and experience in the field of financial research, coding, financial analysis, and project planning. Dr. Aiken is a major asset to Elon University and I am honored to have been able to work with him. I would also like to thank Alyssa Martina, J.D./M.B.A., who helped set up many of my VC and angel interviews, particularly in regards the Michigan and North Carolina investors. Likewise, I am thankful for Elon Parent’s Council member Scott Barnum, who was a major help with setting up interviews with West Coast-based investors. In addition, I would like to acknowledge and thank all of the people associated with the Love Award, including but not limited to Dean Raghu Tadepalli, Kristin Barrier, Nicole Filippo, the selection committee, and everyone else who makes The Love Award possible for Elon students. I am deeply grateful for all of the investors interviewed taking valuable time out of their days to contribute to this research. I also am indebted to all the finance faculty who have taught me — Dr. Todd Stonitsch, Dr. Jongwan Bae, Dr. Kate Upton, and Dr. Chris Harris. I would never have been where I am today without them. Above all, I owe everything to my parents who have always supported me, particularly in my education.
Abstract
The venture capital industry is inherently network and relationship focused, yet research on the impact of the network effects of VC firms on the performance of their portfolio companies is seriously lacking. Given the economic impact of venture capital and its role in the major technological revolution going on in the 21st century, this is an opportunity to create serious benefits for multiple stakeholders in the entrepreneurial ecosystem.
This paper analyzes VC network effects’ impact on startup success using a qualitative method, interviewing thirteen angel and VC investors, along with a quantitative method analyzing 19,000 unique startup investments made by 460…
