Evolutionary game analysis on the diffusion of general purpose technologies with government multiple supports
Yuelong Zheng,
Chunguang Bai,
Lin Wang,
Chunjia Han,
Mu Yang and
Anusha Pappu
Economics of Innovation and New Technology, 2024, vol. 33, issue 3, 436-454
Abstract:
General purpose technologies (GPTs) are seen as engines of economic growth, which is achieved through diffusion in various application sectors. The diffusion of GPTs is the key to unleashing their potential value. However, the market and organisational failure of GPT diffusion are seen as hurdles to realise this potential. To address this issue, a single-group evolutionary game model was established to analyse the GPT diffusion process and its influencing factors and reveal the evolutionary mechanism of GPT diffusion. The main findings of the study show that the GPT diffusion is an evolutionary process influenced by many factors. GPT diffusion is negatively related to adoption and commercial development costs and positively related to the success rate of commercial development. In addition, government support is found to be positive for GPT diffusion, but a disproportionate share of government funding supports dampens the diffusion process. It is also found that government funds, knowledge and technological support are conducive to GPT diffusion. The effect of knowledge and technological support on GPT diffusion is positively regulated by the technology conversion coefficient, but the intellectual property rights system has a negative impact. The study sheds light on strategic choices for the diffusion and supply of GPTs.
Date: 2024
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/10438599.2023.2196418 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:ecinnt:v:33:y:2024:i:3:p:436-454
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GEIN20
DOI: 10.1080/10438599.2023.2196418
Access Statistics for this article
Economics of Innovation and New Technology is currently edited by Professor Cristiano Antonelli
More articles in Economics of Innovation and New Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().