AI Product Factors and Pro-Environmental Behavior: An Integrated Model with Hybrid Analytical Approaches

Based on three theories—the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and Responsible Environmental Behavior (REB)—the present study proposes a model of AI product factors and pro-environmental behavior. This study aims to investigate AI product factors that promote pro-environmental behavior by examining behavioral intentions to use AI technology. Unlike previous research, which predominantly focused on external variables such as social norms, cost, and inconvenience, or individual variables like demographic and psychological factors, this study emphasizes the underexplored role of technological factors. It integrates the Fuzzy Decision-Making Trial and Evaluation Laboratory (F-DEMATEL), Structural Equation Modeling (SEM), and Artificial Neural Network (ANN) approaches to assess the relationships among constructs. For the F-DEMATEL, opinions were collected from 20 experts in the environmental field, while SEM and ANN data were gathered from 1726 participants in Taiwan. F-DEMATEL results demonstrated causal relationships between external factors (perceived trust, self-efficacy, and perceived awareness) and the main variables of the TAM. Likewise, SEM results revealed that perceived trust (PT), self-efficacy (SE), and perceived awareness (PA) influence the main variables of TAM. However, the direct relationships between PT and behavioral intention (BI) and PA and BI were not significant. PT and PA indirectly influence BI through perceived usefulness (PU) and perceived ease of use (PEOU). The results also established that BI positively influences pro-environmental behavior. The author has also outlined how stakeholders aiming to encourage sustainable environmental behaviors can utilize the study’s findings to protect the environment.