원문정보
초록
영어
Xiaohongshu, a community-centric social media platform, has pioneered a unique e-commerce model known as 'buyer commerce,' leveraging user-generated content (UGC). Distinctively, Xiaohongshu Live Commerce focuses on fostering deep user relationships and providing superior product and information services, crucial for sustained consumer engagement. This study investigates consumer behavior in purchasing health functional foods via Xiaohongshu Live Commerce, aiming to understand the determinants of continuous usage intention. A novel theoretical framework was devised by integrating the Expectation Confirmation Model (ECM) and the Task-Technology Fit (TTF) model. The research model scrutinizes the impact of Xiaohongshu Live Commerce characteristics, such as perceived usefulness and perceived online intimacy, on tasktechnology fit. Additionally, it examines the moderating role of perceived risk specific to health functional foods and the influence of expectation confirmation on perceived usefulness, online intimacy, and tasktechnology fit, alongside their effects on satisfaction and continuous usage intention. The findings reveal that expectation confirmation positively influences perceived usefulness, online intimacy, and task-technology fit. Perceived usefulness significantly enhances task-technology fit, while perceived online intimacy and risk do not significantly affect task-technology fit. Moreover, perceived usefulness and intimacy positively impact consumer satisfaction and continuous usage intention, with task-technology fit playing a pivotal role. Perceived risk moderates the relationship between perceived usefulness and task-technology fit. These insights suggest that companies can augment consumer satisfaction and continuous usage intentions by enhancing the perceived usefulness of technology, effectively managing perceived risks, and continually improving user experience
목차
1. INTRODUCTION
2. THEORY
2.1. Expectation confirmation model (ECM)
2.2. Task-Technology Fit (TTF)
3. Conceptual model and hypotheses
4. Methodology
4.1. Sample
4.2. Measures
4.3. Demographic Characteristics
5. RESULTS
5.1. Measurement Model Evaluation
5.2. Structural model assessment
5.3. Verification of regulatory effects
6. CONCLUSION AND DISCUSSION
References