An evolutionary game analysis of digital transformation of multiagents in digital innovation ecosystems

Abstract

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.

Intelligence level evaluation and influencing factors analysis of equipment manufacturing industry in the Yangtze River Delta

“…Enterprise costs include production, research and development, management, and so on. These findings are similar to the costs findings of Liu et al, [ 31 ]. Reducing enterprise costs can improve the competitiveness of enterprises, thus promoting the intelligence development of the manufacturing industry.…”

“…The development and application of enterprise cost theory is significant for enterprises to improve economic efficiency, reduce business risks, and improve competitiveness. At the same time, with the development of economic technology, enterprise cost theory is also constantly developing and improving, providing theoretical support and practical guidance for the development of enterprises [ 31 ].…”

Multi-group symbiotic evolutionary mechanisms of a digital innovation ecosystem: Numerical simulation and case study

“…In the case that it is difficult to accurately obtain a large amount of time-series data on digital innovation ecosystems, empirical research cannot be easily performed [ 58 , 59 ]. Then, numerical simulation is an effective method to explore the internal symbiotic evolution law [ 4 , 6 ]. However, numerical simulation methods have certain limitations in that they do not comprehensively reflect real scenarios.…”

“…Chae observed that the digital innovation ecosystem consists of digital innovation and innovation ecosystems [ 5 ]. It is a complex system of competition symbiosis in which different innovation actors and environments in a particular region combine various digital and non-digital resources using digital technology to create new products and services [ 6 ]. Kolloch and Dellermann pointed out that the rise of the Internet of Things has brought ecosystems to the forefront of innovation, and effectively managing the evolution of these ecosystems during the process of digital innovation is important [ 7 ].…”

“…Suseno et al examined how value is generated through the interaction between consumers and professional stakeholders in a digital innovation ecosystem [ 8 ]. Liu et al proposed a tripartite evolutionary game model of digital transformation based on expectation theory and Lyapunov’s first law to analyze the obstacles faced by stakeholders in the digital ecosystem for undertaking digital transformation [ 6 ].…”