University Start-Ups: The Relationship between Faculty Start-Ups and Student Start-Ups

Yoonseock Lee,Young-Hwan Lee

doi:10.3390/su12219015

Yoonseock Lee, Young-Hwan Lee

Open Access

https://doi.org/10.3390/su12219015

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Abstract

University start-ups include faculty and student start-ups. Earlier research on universities’ roles in start-ups was focused on faculty. When student start-ups outperform faculty start-ups, the resources affecting these start-ups, and their relationship, should be analyzed. This study investigates the determinants of faculty and student start-ups, comparing key resources and exploring whether faculty start-ups affect student start-ups and vice versa, as well as whether the relevant resources interact, using panel data from 92 Korean universities from 2012 to 2018. Resource variables including labor costs, bonuses, research expenses, laboratory expenses, equipment costs, and technology transfer offices were used as explanatory variables. Additionally, for faculty start-ups, central and local government funds, science citation indices, patents, technology revenues, and student start-ups were used as explanatory variables. For student start-ups, university funding, government funding, start-up clubs, Capstone Design funding, and faculty start-ups were used as explanatory variables. Using these start-ups as endogenous variables in estimations, this study adapts a simultaneous equation model with panel data, analyzing it with three-stage least square regression method. Faculty labor costs and central and local government research funds significantly positively affect faculty start-ups. Support funding, start-up clubs, and technology transfer offices significantly positively affect student start-ups. Results show that faculty start-ups significantly affect student start-ups, but there is no influence from student start-ups on faculty start-ups.

Highlights

The roles and functions of universities change over time [1]
Panel data regression is a combination of cross-sectional data and time series data that can be analyzed through explicitly considering the heterogeneity of the panel objects, as follows: yit f = α + βixit + ui + εit, i(university) = 1, 2, 3, . . . , n and t(year) = 1, 2, 3, . . . , t yits = α + βixit + ui + εit, i(university) = 1, 2, 3, . . . , n and t(year) = 1, 2, 3, . . . , t where yit f is the faculty start-up, yits is the student start-up, and x is the determinant vector
The results showed that there was no difference in the number of faculty start-ups from year to year

Summary

Introduction

Universities that had focused on knowledge, education, and research began to emphasize industry-university cooperation in the late 1970s [2]. Entrepreneurial colleges emerged that, while continuing to emphasize knowledge and skills [3], focused on research and development through cooperation with companies, utilization of university research results, transfer of university patents and technologies, and start-ups at universities [4]. While university research results had been initially concentrated more on promoting patents and technology transfers, recent emphasis has been placed on start-ups at universities [5]. Universities are offering education and support for start-ups in various forms, such as reforming the curriculum through industry-academic cooperation projects, encouraging capstone projects, developing idea-based start-up items through start-up clubs, and finding star start-ups through start-up competitions. A start-up club is an autonomous group of students who meet regularly to promote entrepreneurship

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