Analysis of ocean cleanup technologies support among early adopters in the Philippines: An integrated SEM-neural network assessment

The Philippines generates large volumes of plastic waste that flow into the oceans due to poor waste management and weak public engagement. While ocean cleanup technologies continue to improve, few studies examine what drives people to support or adopt these solutions. This study aimed to identify the behavioral and sustainability-related factors influencing support for ocean cleanup technologies using an integrated machine learning approach among early Filipino adopters. A combined framework of the Sustainability Theory of Planned Behavior and the modified AMATA framework was used to evaluate key influences through Structural Equation Modeling, then Artificial Neural Network. Based on 690 valid responses, key behavioral drivers were identified, emphasizing behavioral intention (Normalized Importance Score (NI) = 100.0%), climate protection (NI = 94.7%), and social impact (NI = 92.3%). These results further revealed that individuals are more likely to support cleanup initiatives when they are linked to environmental responsibility and community well-being. With this, government and environmental institutions may consider these findings when designing campaigns and programs to strengthen public involvement in marine protection. The results of this study can help future engagement strategies and contribute to long-term solutions for plastic pollution. Additionally, the framework and method used can be applied in other environmental studies to assess public support for sustainability technologies in developing countries.