The evaluation of innovation efficiency and analysis of government subsidies influence—Evidence from China's metaverse listed companies

Limei Chen, Siyun Tao, Xiaohan Xie, Weidong Huang and Weiwei Zhu

Technological Forecasting and Social Change, 2024, vol. 201, issue C

Abstract: The emergence of the metaverse industry is a potential new engine of economic growth. The government, which has a stake in every innovation, should respond by providing a favorable business environment. Metaverse companies, for their part, need to measure the efficiency of the innovation process and the rationality of resource allocation to sustain its competitive edge. However, the relationship between government subsidies (GS) and companies' innovation efficiency is unclear. Based on a three-stage data envelopment analysis (DEA) model and a Tobit-regression model, this study analyzes the relationship between government subsidies and innovation efficiency accounting for the influence of environmental variables on innovation performance. There were several main findings: (1) Using a three-stage Data Envelopment Analysis (DEA) model, the first-stage efficiency is far from the production frontier. After removing external environmental variables and random disturbance factors, the third stage efficiency increased notably due to the increase of pure technical efficiency. Government support and regional innovation atmosphere positively influence the innovation efficiency. This paper further classifies the 119 companies into four categories based on pure technical efficiency and scale efficiency. (2) Drawing upon the Tobit-regression model, the paper reveals that government subsidies have positive influence on the innovation efficiency of metaverse listed companies. These findings contribute to a deeper understanding of the role of government subsidies in innovation efficiency and their important implications for policymakers.

Keywords: Government subsidies; Innovation efficiency; Three-stage DEA; Metaverse listed companies (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:201:y:2024:i:c:s004016252400009x

DOI: 10.1016/j.techfore.2024.123213

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