Evaluating performance of innovation resource allocation in industrial enterprises: an improved two-stage DEA model

Abstract

ABSTRACT Innovation resource allocation performance is an important driver of global competitiveness of nations. Due to the complexity of innovation production process, the structure of the innovation resource allocation is no longer single, but most of the existing studies on the innovation resource allocation performance are based on series cases overlooking parallel cases. We evaluate the innovation resource allocation efficiency of Chinese industrial enterprises from the research and development (R&D) stage and the commercialisation stage, where the commercialisation stage consists of two parallel sub-stages (technology commercialisation stage and product commercialisation stage). As a result, we develop a cross two-stage data envelopment analysis model (TS-DEA model) with nested parallel structure. The result shows that traditional DEA model overestimates the efficiency score due to pursuing the efficiency optimisation for decision-making unit (DMU). Compared with western China, central China was more efficient in allocating innovation resource for industrial enterprises.