Most startups fail within the first three years. Every year more than 500,000 startups are created and less than 1,000 of those receive venture capital funding. Increasing the number of successful startups can lead to more jobs in the economy and improve innovation across industries. Previous research has attempted to determine characteristics of successful startups and has found that Human Capital, Structural Capital, and Social Capital have the most effect on the success of a startup.
This thesis examines the characteristics of successful startups by measuring efficiency of startups in the sample using Data Envelopment Analysis (DEA) technique. Startups included in the sample are currently active, have received at least one investment, and have been founded since January 2013. The DEA model includes Number of Investments, Total Amount of Funding ($), Global Traffic Rank (MAU), and Revenue ($) as outputs. Inputs include Human Capital characteristics such as Team Experience, Number of Founders, and Number of Employees, and Structural and Social Capital proxies such as Number of Acquisitions, and Quality of Investors. This thesis also uses the Boston Consulting Group Matrix as an additional tool to relate characteristics of startups to efficiency scores. Case studies on select startups provide insights on determinants of successful startups
This research contributes to the existing literature by providing rigorous analysis of startups and identifying characteristics of highly efficient startups. Prospective entrepreneurs may benefit from knowing characteristics that are likely leading to successful startups and which industries have room for innovation.