Abstract
Mobile application innovation diffusion can be used to enhance the reputation and competitiveness of Internet enterprises. However, few works have explored the process of mobile application innovation diffusion from the individual perspective. Therefore, this paper employs multi-agent methods to simulate the innovation diffusion of mobile applications from the perspective of social networks. Specifically, we combine psychology, sociology, game theory and network effect theory to model user behaviors of adoption and rejection decisions for mobile applications. The multi-agent model was built in Anylogic 8 to simulate the communication and interaction between individual users. Then, this paper discusses the evolution of decision-making of social network user groups with different network structures and network effects. We also investigate the impact of different firms’ promotion on innovation diffusion. Our findings suggest firms could make better strategies and achieve better diffusion effects from mobile applications.
Highlights
Nowadays, market competition in mobile applications is increasingly fierce
We explore the influence of social network structures on the decision-making of mobile user groups, investigating the characteristics of innovation diffusion for mobile application under global and local network effects
We find that more users choose to adopt mobile applications under the local network effect, which shows that the local network effect of the same intensity has a more substantial promotion effect on the innovation diffusion of the mobile applications
Summary
Market competition in mobile applications is increasingly fierce. The success of the mobile application in market promotion helps Internet enterprises to seize the market and create business value, and allows firms establish a good reputation and gain a competitive advantage [1,2,3].The innovation diffusion of mobile applications always occurs in user groups. Since users can communicate and interact with others, most of the diffusion of mobile applications is based on each user in a social network [4,5]. Global network effect means that, when more users adopt innovative technology in the global environment, the value of mobile applications to users will be higher. While the local network effect refers to the effect of related users on the utility value, which emphasizing the interaction between users. The value and utility of the mobile applications to the users will increase, which affects user decision-making. When the intensity of the network effects of the mobile applications is stronger, the value of the network effects will be greater. If the network effect is less intense, the user’s decision will have less impact on the surrounding users [11,12,13]
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