Hybrid analytical approach to understanding male consumer behavior: Integrating PLS-SEM, ANN, and sentiment analysis in the context of green grooming products

This research investigates the application of chatbots, specifically in the male grooming industry. It explores the transformative potential of solutions enabled by chatbots. While consumers are willing to adopt new technologies, the extent of their adoption of green grooming products and chatbots for purchase decisions remains unclear. This research addresses the gap by developing a conceptual framework grounded in chatbot technology. This study examines male consumers’ interactions with chatbots in purchasing green grooming products, focusing on technological and behavioral factors influencing acceptance and adoption. A two-stage mixed-methods design was employed. In the first stage, consumer reviews (n = 3503) were analyzed to capture insights grounded in real-world experiences. In the second stage, survey data from male consumers (n = 390) were examined using partial least squares structural equation modeling, based on the Technology Acceptance Model. Artificial neural network analysis was conducted to enhance model validation and predictive accuracy, offering nonlinear insights into the differential significance of predictors of purchase intention. This research contributes to the literature on digital adoption in sustainable markets by extending TAM to the underexplored context of green grooming among male consumers. Findings highlight the significance of empathic capacity and responsive communication in chatbot design, revealing consumer preference for human-like and personalized digital interactions. Managerially, the results guide integrating chatbots into green marketing strategies, fostering effective engagement, and encouraging eco-friendly grooming practices.