Abstract
The successful diffusion of mobile applications in user groups can establish a good image for enterprises, gain a good reputation, fight for market share, and create commercial profits. Thus, it is of great significance for the successful diffusion of mobile applications to study mobile application diffusion and social network coevolution. Firstly, combined with a social network’s dynamic change characteristics in real life, a mobile application users’ social network evolution mechanism was designed. Then, a multi-agent model of the coevolution of a social network and mobile application innovation diffusion was constructed. Finally, the impact of mobile applications’ value perception revenue, use cost, marketing promotion investment, and the number of seed users on the coevolution of social network and mobile application diffusion were analyzed. The results show that factors such as the network structure, the perceived value income, the cost of use, the marketing promotion investment, and the number of seed users have an important impact on mobile application diffusion.
Highlights
With the rapid development of mobile Internet technology, China’s mobile 4G network construction is in full swing
We present a discussion of the coevolution characteristics and the interaction between social network structures and user group decision-making evolution
The multi-agent model of the coevolution of a social network and mobile application innovation diffusion was constructed in Anylogic 8
Summary
With the rapid development of mobile Internet technology, China’s mobile 4G network construction is in full swing. We considered the dynamic changes in social networks in the process of innovation diffusion, mainly studying the laws and the relationship between social networks and innovation diffusion, and the roles of various internal and external factors in the process of coevolution to gain further insight into the internal mechanisms and characteristics of mobile application innovation diffusion. We present a discussion of the coevolution characteristics and the interaction between social network structures and user group decision-making evolution. A multi-agent model considering the dynamic changes in network structures was developed to simulate mobile application diffusion. By accumulating users’ individual decision-making results, we combined the micro behavior of user decision-making in complex systems with the innovation diffusion of mobile applications to better explore mobile application innovation diffusion’s internal mechanism and laws
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