An Analysis of Educational Performance Efficiency and Its Determinants in Universities Participating in the University Innovation Support Project Using Double Bootstrap DEA

Key Points

• This research aims to measure the relative efficiency in converting financial investments into educational performance in universities.
• Constructed panel data from private universities participating in the project from 2019 to 2023.
• Performed input-oriented variable returns to scale data envelopment analysis (DEA) using specific input and output factors.
• Applied double bootstrap algorithm to correct statistical biases and reinforce inference reliability.
• Confirmed economies of scale effects due to increased student enrollment.
• Found that the proportion of education-related investment significantly reduces inefficiency, regardless of timing.
• Identified the need for considering lag factors when interpreting the relationship between financial input and performance indicators.

Abstract