To reveal the influence mechanism of e-banking channel selection of elderly customers, according to the analysis of elderly customers’decision-making process, a threshold model is proposed by using small world customer relationship network and variable setting in this study. The multi-agent simulation of e-banking channel selection behavior of elderly customers is carried out from the perspectives of channel diffusion speed and customer channel selection proportion in the context of Covid-19 pandemic. The research shows that channel performance and individual differences of customers affect the adoption of e-banking by elderly customers. This study also has found that network size and network density can regulate the impact of channel performance on the selection behavior of elderly groups. However, they could play a regulatory role under certain conditions. Finally, this study puts forward some suggestions to improve the channel diffusion efficiency, such as building an elderly friendly e-financial service channel and construction of elderly business market culture.

In an omni-channel environment of banks, the information transmission between banks and customers is the basis for decision-making on both sides. This dissertation analyzes the characteristics of signals sent between banks and customers at different stages and proposes a game model of bank–customer signals in an omni-channel environment. The model explores the types of banks and customers and the influence of six signals on both parties’ action decisions. Building on this model, a genetic algorithm of the signaling game between banks and customers is developed. This algorithm improves the adaptability of customers to the bank’s omni-channel environment through the “selection–crossover–mutation” process. The algorithm determines the signal that brings the greatest utility among multiple bank–customer combinations. This is carried out by calculating the choices made, resulting in the greatest total utility. Finally, a case study is carried out on the omni-channel transformation of Agricultural Bank of China, illustrating the validity of the research results of the game relationship and action optimization. Overall, this study provides a quantitative tool for the action decision-making of banks and customers and the optimization of the relationship between the two. It also provides a reference for how banks should manage customer relationships in an omni-channel environment.