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).1. 研究目的：本数据集旨在探究社交媒体上针对环保品牌的假新闻分享行为背后的心理与行为驱动因素。本研究旨在厘清沉浸式线上体验、地位寻求动机、信任维度、社交媒体参与度与平台使用行为之间的复杂交互关系。本研究采用双方法分析路径——结构方程建模（Structural Equation Modeling）与模糊集定性比较分析（fuzzy-set Qualitative Comparative Analysis），以期识别出个体预测变量的净效应，以及引发高水平假新闻分享行为的特定条件组合。 2. 数据性质与范围：本数据集包含用于检验整合理论模型的一手定量调查数据，其覆盖范围涉及个体与环境内容、社交媒体使用及假新闻相关的感知、动机与自我报告行为。 包含文件： 调查数据（SPSS .sav文件）：包含来自[Number]名受访者的原始与清洗后问卷应答数据，所测核心构念包括： - 亲环境内容沉浸式心流（IFPC） - 地位寻求动机（SSM） - 亲环境社交媒体参与度 - 针对环保内容的社交媒体信任度 - 环保品牌信任度 - 社交媒体使用强度/时长 - 针对环保品牌的假新闻分享行为 - 社交媒体使用能力 - 标准人口统计学变量（如年龄、性别、受教育程度）