Research on the Game Relationship and Behavior Optimization between Banks and Customers in the Omni-Channel Environment

Abstract

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.