Bayesian Network-based Modeling of Consumer Behavioral Decision Making Processes in Digital Economy Platforms

In order to more comprehensively study the influencing role mechanism of consumer behavioral decision-making process in the digital economy platform and explore the influencing factors of consumer behavioral decision-making, this paper constructs a model of consumer behavioral decision-making process based on Bayesian network.With the help of Netica software to construct the Bayesian network topology, using EM algorithm to learn the parameters of the Bayesian network model, and proposed to use the Bayesian network to carry out sensitivity analysis and probabilistic inference, and formulate the corresponding Bayesian network model framework.Subsequently, the influencing factors of channel search willingness and purchase willingness and their relationships in the consumer behavioral decision-making process in the digital economy platform environment are analyzed.The structural equation model is introduced, the measurement equation and structural subequation calculation methods are determined, and the sample data are collected by means of questionnaires to carry out the test and analysis of the model of consumer behavioral decision-making process.The CR value of each variable in the model of this paper is higher than 0.7, and the AVE values are all greater than 0.5, and the model performs well in terms of intrinsic quality.The exogenous latent variables such as perceived benefits, channel trust, and transfer costs have a significant positive effect relationship on the endogenous latent variables such as search behavior and purchase intention (P<0.05).