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An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems
In an innovation ecosystem, the digital transformation decisions and game mechanisms of entities are paramount issues to be studied. Consequently, this study constructs a digital transformation SD evolutionary game model based on expectancy theory and Lyapunov’s first law to address the above issues...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10361489/ https://www.ncbi.nlm.nih.gov/pubmed/37478085 http://dx.doi.org/10.1371/journal.pone.0289011 |
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author | Liu, Baotong Zou, Hua Qin, Hao Ji, Huimin Guo, Yongquan |
author_facet | Liu, Baotong Zou, Hua Qin, Hao Ji, Huimin Guo, Yongquan |
author_sort | Liu, Baotong |
collection | PubMed |
description | In an innovation ecosystem, the digital transformation decisions and game mechanisms of entities are paramount issues to be studied. Consequently, this study constructs a digital transformation SD evolutionary game model based on expectancy theory and Lyapunov’s first law to address the above issues. The results demonstrate the following: (1) Digital technology empowerment benefits, spillover effects, and supervision benefits are positively correlated with the willingness of the three players to engage in digital transformation; (2) Regardless of how the initial will of the players changes, the decision of the evolutionary game system is ultimately stable in (empower, transform, supervise). Compared with governments, platform centers, and nodal enterprises have a stronger will for digital transformation. However, the governments’ will is the key to the convergence speed of the game system to the equilibrium point. (3) If the static/dynamic spillover effect can cover the transformation loss, even if the transformation profits of nodal enterprises are negative, nodal enterprises will still choose the game strategy of "transformation". When the government subsidies are less than the initial value of 2, the game system has two possible strategy choices: (empower, nontransform, nonsupervise) and (empower, transform, supervise). As such, this study can fill the research gaps and address the barriers to digital transformation among stakeholders. |
format | Online Article Text |
id | pubmed-10361489 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-103614892023-07-22 An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems Liu, Baotong Zou, Hua Qin, Hao Ji, Huimin Guo, Yongquan PLoS One Research Article In an innovation ecosystem, the digital transformation decisions and game mechanisms of entities are paramount issues to be studied. Consequently, this study constructs a digital transformation SD evolutionary game model based on expectancy theory and Lyapunov’s first law to address the above issues. The results demonstrate the following: (1) Digital technology empowerment benefits, spillover effects, and supervision benefits are positively correlated with the willingness of the three players to engage in digital transformation; (2) Regardless of how the initial will of the players changes, the decision of the evolutionary game system is ultimately stable in (empower, transform, supervise). Compared with governments, platform centers, and nodal enterprises have a stronger will for digital transformation. However, the governments’ will is the key to the convergence speed of the game system to the equilibrium point. (3) If the static/dynamic spillover effect can cover the transformation loss, even if the transformation profits of nodal enterprises are negative, nodal enterprises will still choose the game strategy of "transformation". When the government subsidies are less than the initial value of 2, the game system has two possible strategy choices: (empower, nontransform, nonsupervise) and (empower, transform, supervise). As such, this study can fill the research gaps and address the barriers to digital transformation among stakeholders. Public Library of Science 2023-07-21 /pmc/articles/PMC10361489/ /pubmed/37478085 http://dx.doi.org/10.1371/journal.pone.0289011 Text en © 2023 Liu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Liu, Baotong Zou, Hua Qin, Hao Ji, Huimin Guo, Yongquan An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems |
title | An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems |
title_full | An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems |
title_fullStr | An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems |
title_full_unstemmed | An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems |
title_short | An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems |
title_sort | evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10361489/ https://www.ncbi.nlm.nih.gov/pubmed/37478085 http://dx.doi.org/10.1371/journal.pone.0289011 |
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