Evaluation of green technology innovation efficiency in a regional context: A dynamic network slacks-based measuring approach

As green technology innovation efficiency is considered an effective indicator to evaluate energy conservation and emission mitigation, the question of how to estimate it has become a hot topic. Research primarily calculates the cross-section efficiency from a static perspective or the network efficiency alone; however, few studies have considered dynamic characteristics and the network structure of the innovation process simultaneously. To address this gap, this paper employs slacks-based dynamic network data envelopment analysis to calculate the overall, intertemporal, and divisional green technology innovation efficiency covering China's 30 provinces over 2012-2019. The results indicate that (1) a strong spatial dependence of efficiency scores exists, accounting for 60 % of the aggregate statistics. (2) China's overall scores are low, and inefficient regions need to improve ef-ficiency by at least 31.41 % to become efficient. (3) Economically developed regions, provinces with advanced manufacturing, and nonresource-based areas have relatively high scores. (4) The period scores fluctuate greatly up and down around the overall scores, showing a significant spatial imbalance within consecutive multiple periods. (5) Regarding divisional scores, the internal structure of green technology innovation efficiency in China is inferior in R & D and superior in commercialization. Generally, policy-makers should improve local conditions for green technology innovation efficiency.

Automated summary

This paper calculates the green technology innovation efficiency of 30 provinces in China from 2012 to 2019 using slacks-based dynamic network data envelopment analysis. The findings reveal spatial dependence, regional disparities, and temporal fluctuations in efficiency scores. The results provide valuable insights for policymakers to improve green technology innovation efficiency.