Analysis of Support Efficiency of Support Projects according to the Characteristics of Start-ups

In recent years, as the importance of startups has increased, interest in startups has continued to increase. Universities are carrying out various forms of support projects to support startups and create an startups culture and ecosystem. This study aims to analyze how the University Startup Support Project works according to the characteristics of startups through support efficiency. To this end, 85 startups that benefited from the Southeast University Startup Support Project were selected as samples and data envelopment analysis (DEA) was performed. Next, the characteristics of the startups were classified and the efficiency between groups was compared. The input variables of efficiency were set as government grants, in-kind matching funds, and cash matching funds. The output variables were set as sales and new hires from an economic perspective, and R&D project contract amount and number of applications from a research perspective. The characteristic variables of startups were set as startup stage, age group, business type, area, faculty status, and region, and then comparative analysis was conducted. The results showed that the efficiency was high in the order of preliminary, initial, and leap forward stages by startup stage, and individual businesses had higher support efficiency than corporate businesses. According to the business application classification, the support efficiency was high in the order of general, regional, and university-based businesses. Based on location, the metropolitan area had the best support efficiency. That is, it was confirmed that the effect of support projects conducted by universities may differ depending on the characteristics of the startups. Through these results, practical implications are provided so that regional environmental improvement, education, and financial support for the startup ecosystem can be distributed to where they are required.