METHODS: Social Cognitive Theory (SCT) was used as a guide in developing the PEB framework. Specifically, three factors were identified-Self-awareness (Personal), Attitude (Personal and Environment) and Safe Practice (Behavior) as the potential predictors for online fraud victimization. A self-reporting questionnaire was developed based on the PEB framework and used to collect data targeting Malaysian adults. The study reports result from two separate datasets collected across two separate timelines. Study I involved data collection in January 2023 (n = 820) whereas Study II was conducted with a modified questionnaire from November 2023 -January 2024 (n = 629). Study I identified the online fraud victimization predictors through an Exploratory Factor Analysis (EFA) and a hierarchical binary logistic regression. The dataset from Study II was used to validate the online fraud victimization model derived from Study I by executing another round of hierarchical binary logistic regression.
RESULTS: Results from both the samples show that most of the respondents are aware of digital privacy. EFA from Study I yielded a five-factor solution with a total variance of 60.6%, namely, Self-awareness, Safe Practice, Bank Trust, Overconfidence and Social Influence. Hierarchical binary logistic regression results from both the studies were found to be consistent. Specifically, Overconfidence (β = 0.374; OR = 1.453; 95% CI [1.119, 1.887]; p = 0.005) and Social Influence (β = 0.332; OR = 1.225; 95% CI [1.077, 1.512]; p = 0.006) were found to significantly predict online fraud victimization as well as gender (β = 0.364; OR = 1.440; 95% CI [1.008, 2.016]; p = 0.045) with females exhibiting higher risks to victimization.
IMPLICATIONS: The emergence of Overconfidence and Social Influence as significant predictors can guide the development of targeted online fraud awareness campaigns and/or tools emphasizing critical thinking and skepticism. Policymakers can leverage this knowledge to implement regulations that reduce deceptive practices online, promote digital literacy programs, and mandate clearer consumer protections to mitigate the impact of social manipulation and overconfidence on fraud victimization.
CONCLUSION: This study identifies online fraud victimization predictors, hence improving our understanding of the factors behind this phenomenon-allowing for the development of effective preventive measures and policies to safeguard individuals and improve digital security. For instance, gender- specific educational campaigns can be developed to enhance awareness and equip women with strategies to detect and avoid scams. Additionally, addressing systemic factors like social norms and digital literacy gaps is crucial for creating equitable and effective solutions to reduce online fraud victimization.