Simulation of employee behaviour psychology based on stochastic cellular automata

Employee behavior exhibits diversity at different times and environments, with obvious characteristics of complex systems. Cellular automata (CA) is a mathematical model with discrete time, space, and state, suitable for complex dynamic system problems that are difficult to quantitatively describe mathematically. This article has established a model based on random CA simulation of employee behavior, calibrated parameters such as cell state and moving steps, and designed cell transfer rules. This article conducted experiments on two organizational structures: single employee enterprises and mixed employee enterprises. The experimental results indicated that the cohesion of employees who adopted reverse incentives before positive incentives in management organizations was greater than that of employees who adopted consistently positive incentives. When the number of iterations was 12, the cohesion of group a of mixed employees reached its peak. As t increased, influenced by surrounding neighbors, loyalty Y2 decreased and eventually reached a stable value, which was greater than the value of Y2 of group b. The simulation results indicated that CA is suitable for practical applications and provides assistance for decision-makers in human resource management.