The dynamic DEA assessment of the intertemporal efficiency and optimal quantity of patent for China’s high-tech industry

Abstract

This study uses the dynamic data envelopment analysis (DEA) model to evaluate intertemporal efficiency for high-tech industries in China. The significant difference from previous studies is the assumption for patents, which are defined to be a carry-over intermediate linking different terms. The model further provides an indicator of adjustment ratio for patents, based on the assessment of optimal quantity of patents. Output and input inefficiency indicators are also developed in the model to explore the sources of operational inefficiency. The empirical results conclude that intertemporal efficiency trends upward over time; the quantity of patents is assessed to be in shortage during the early terms, but excessive in recent terms; and that deficits in financial output is a significant factor in creating inefficiency.

Keywords:

• data envelopment analysis
• intertemporal efficiency
• high-tech industry
• carry-over intermediate
• patent