A TWO-PATH BAYESIAN PROBABILITY MODEL FOR EXAMINING INDIVIDUAL AND PROCESS HETEROGENEITY IN THE AISAS FRAMEWORK
A TWO-PATH BAYESIAN PROBABILITY MODEL FOR EXAMINING INDIVIDUAL AND PROCESS HETEROGENEITY IN THE AISAS FRAMEWORK

Summary/Abstract: The AISAS (Attention-Interest-Search-Action-Share) model is widely utilized to explore the influence of social media on information diffusion and marketing campaign applications. However, traditional approaches often overlook the concurrent variations across individual consumers and transition processes. This paper constructs a Bayesian probability model to predict both consumer individual differences and process-specific variations across the AISAS steps. Utilizing empirical data from diverse social media platforms, including individual media behaviors and the specific duration of each AISAS stage, we estimate model parameters and evaluate the goodness of fit. The empirical results demonstrate satisfactory predictive power, offering critical insights and managerial implications for future marketing applications.

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