Modelling consumer intent for purchase recycled products: a pathway to future sustainability

• Resilient cyber threat detection framework that utilizes ensemble machine learning methods and the extensive UNSW-NB15 dataset, which encompasses realistic and diverse network attack scenarios. • Principal Component Analysis (PCA) and mutual information-based selection are employed to identify the most important characteristics that contribute to improving the acceleration and Precision of the process. • Random Forest (RF), K-Nearest Neighbours (KNN), and Light Gradient Boosting Machine (LightGBM) are compared, it is clear that LightGBM is superior in terms of finding incursions and has the potential to be utilized on a larger scale. Despite increasing global concern for environmental sustainability, the adoption of recycled products remains limited, particularly in developing economies where consumer skepticism and entrenched purchasing habits persist. This study examines the key determinants influencing consumers’ intentions to purchase recycled products in alignment with Sustainable Development Goal 12 (Responsible Consumption and Production). Specifically, it analyzes the effects of environmental attitude, trust, perceived credibility, and perceived product quality on purchasing decisions. A structured questionnaire survey was administered to 315 urban consumers in India using purposive sampling. The findings reveal that environmental attitude is the most influential predictor of recycled product purchase intention, indicating that environmentally conscious consumers are more likely to engage in sustainable consumption. Trust and perceived credibility also significantly affect purchasing behavior, emphasizing the importance of authenticity and reputation in fostering acceptance of recycled products. Although perceived product quality has a comparatively weaker influence, it remains relevant in meeting expectations related to usability and design. The study contributes theoretically by integrating psychological, perceptual, and normative factors into an SDG 12–oriented behavioral framework. Practically, it provides insights for marketers and policymakers to enhance communication strategies, build consumer trust, and promote circular economy practices.