Beyond Net Effects: Configurational Pathways to Misinformation Sharing About Eco-Friendly Brands—A Combined SEM and fsQCA Analysis

1. Purpose: This dataset was created to investigate the psychological and behavioral drivers behind the sharing of fake news specifically targeting eco-friendly brands on social media. The research aimed to unravel the complex interplay between immersive online experiences, status-seeking motivations, trust constructs, social media engagement, and platform usage behaviors. By employing a dual-method analytical approach (Structural Equation Modeling and fuzzy-set Qualitative Comparative Analysis), the study sought to identify both the net effects of individual predictors and the specific combinations of conditions that lead to high levels of fake news sharing behavior. 2. Nature and Scope of the Data: The dataset comprises primary quantitative survey data collected to test an integrated theoretical model. Its scope encompasses individual perceptions, motivations, and self-reported behaviors related to environmental content, social media use, and fake news. Included Files: Survey Data (SPSS .sav file): Contains the raw and cleaned responses from [Number] participants. Variables measure key constructs including: Immersive Flow in Pro-Environmental Content (IFPC) Status-Seeking Motivation (SSM) Pro-Environmental Social Media Engagement Trust in Social Media (for eco-friendly content) Trust in Eco-Friendly Brands Social Media Usage (intensity/duration) Fake News Sharing Behavior (regarding eco-friendly brands) Social Media Competence Standard demographic variables (e.g., age, gender, education).