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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...

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Detalles Bibliográficos
Autores principales: Liu, Baotong, Zou, Hua, Qin, Hao, Ji, Huimin, Guo, Yongquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
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.
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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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