Unintended Consequences of Algorithmic Platform Characteristics on Green Innovation Adoption: The Role of Perceived Erosion of Choice Autonomy and Digital Moral Disengagement

This study investigates the unintended consequences of algorithmic platform characteristics on the adoption of green innovation, focusing on two psychological mechanisms: perceived erosion of choice autonomy (PECA) and digital moral disengagement (DMD). Conducted in 2025, the research surveyed 330 digital consumers in major urban areas of Vietnam—specifically Ho Chi Minh City, Hanoi, and Da Nang—from March to May, employing convenience sampling and paper-based questionnaires. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 3.0 software. The most significant findings indicate that algorithmic personalization notably influences digital moral disengagement (DMD), while algorithmic framing and nudging significantly affect both PECA and DMD. Importantly, prominently displaying green information on digital platforms reduces the perception of manipulation (PECA), thereby narrowing the green attitude-behavior gap (GABG), which is identified as the primary obstacle to adopting green innovations. Consequently, the study suggests designing algorithmic platforms with transparency and user control, emphasizing the clear visibility of green information. The key strengths of the research include integrating diverse psychological theories, such as Self-Determination Theory and moral disengagement theory, within the context of sustainable consumption and employing advanced analytical models to clarify psychological mechanisms influencing sustainable consumer behavior. However, the study also acknowledges limitations, including its restricted scope within major urban centers, lack of behavioral experimentation for validation, and insufficient exploration of other algorithmic features. Information regarding the authors and the publication outlet is not explicitly provided in the document.