Predicting virtual goods purchases in Vietnam’s MMOGs with a TAM-PERVAL model using PLS-SEM and ANN

This study investigates the factors influencing virtual goods purchase intention among Vietnamese Massively Multiplayer Online Game (MMOG) players by integrating the Technology Acceptance Model (TAM) and PERVAL framework. Using a sample of 539 players, an online survey examines functional (usefulness, ease of use), value-based (emotional, social, price, quality), and context-specific factors (blockchain utility, mobile payment ease, trust, immersion, aesthetics), with satisfaction and social influence as mediators and income and gaming experience as moderators. An integrated approach combining Partial Least Squares Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) methods provides both explanatory and predictive insights. Key findings highlight blockchain utility, mobile payment ease, and perceived usefulness as primary drivers of purchase intention, with social influence playing a significant role in Vietnam’s collectivist culture. The study advances digital consumption research in non-Western contexts by offering a comprehensive framework for understanding virtual goods purchases. It provides practical implications for game developers and marketers to leverage blockchain technology and mobile payment systems, enhancing engagement in Vietnam’s rapidly growing MMOG market.