Malaysia's e-commerce sector faces critical cybersecurity challenges that mirror global trends, with a significant year-over-year increase in fraud incidents threatening digital economic growth. Despite behavioural biometrics offering sophisticated protection against these escalating threats, adoption remains limited. This research addresses a theoretical gap by proposing the Augmented Protection Motivation Theory (APMT), introducing risk appraisal as a sequential cognitive construct between threat appraisal and ownership appraisal. The framework examines relationships between threat perception factors (perceived vulnerability, severity, susceptibility), risk evaluation components (perceived security, invasiveness, privacy), psychological ownership (acceptance of responsibility), coping mechanisms (self- efficacy, response efficacy, response cost), and adoption intention, while investigating system trust as a mediator. Using Partial Least Squares Structural Equation Modelling (PLS-SEM) with data from approximately 400 Malaysian e-commerce users, this study investigates whether the sequential cognitive processing approach provides superior explanatory power compared to traditional PMT applications. Preliminary framework testing suggests that the sequential cognitive processing approach (Threat Appraisal → Risk Appraisal → Ownership Appraisal → Coping Appraisal) provides enhanced explanatory power, with response efficacy and self-efficacy expected to demonstrate the strongest direct effects on behavioural biometric adoption intentions. The study anticipates that perceived trust will serve as a significant mediator between coping appraisal factors and adoption intention, particularly in the Malaysian cultural context where institutional trust plays a crucial role in technology acceptance. This research aims to advance cybersecurity adoption frameworks and support policy development for Malaysia's digital economy agenda targeting 25% GDP contribution by 2025.