Perceived Risk and Behavioral Intention of Customers Using Bayesian Technique

In recent decades, the Internet has seen significant development, transforming into an expansive worldwide marketplace facilitating the exchange of various commodities and services. Nevertheless, an increasing number of individuals engaging in online transactions has resulted in a multitude of concerns and challenges. Online customers face a wider range of risks in comparison to those who participate in traditional shop purchasing experiences. The problem of customer perceptions of risk in the context of internet purchasing has emerged as a significant current concern. Thus, the current research used the Bayesian linear regression methodology to investigate the influence of perceived risk on consumers’ behavioral intention within the realm of online purchasing. The findings of the research indicate the existence of four distinct categories of perceived risk, namely product risk, financial risk, convenience risk, and non-delivery risk. These risks are evaluated negatively by customers and have a significant impact on their behavioral intention while participating in online purchase activities.