Research and application flow-based live-streaming shopping towards compulsive buying
本研究基于SOR模型，通过517名中国直播电商用户的调查数据，利用结构方程模型和人工神经网络分析，揭示了心流状态驱动因素和后心流状态中介如何影响强迫性购买行为，为理解直播购物中的消费者行为提供了理论和实践启示。
Abstract The purposes of this research were: (1) to study and justify customer behaviors in live-streaming e-commerce; (2) to study the flow state drivers and post-flow state mediators as crucial factors influencing compulsive buying; (3) to analyze a quantitative survey is used to collect the data. Artificial neural networks and structural equation modeling (SEM) provide the analysis for evaluating the validity of the hypotheses; and (4) to find both theoretical and practical implications provide many insights to help expand the understanding of consumer behaviors in live-streaming e-commerce. The samples used in this study were 517 valid persons who are frequently watching live-streaming e-commerce in China. The stimulus-organism-response (SOR) model captures the stimuli (both personal and flow activity levels), the organism (trust, enjoyment, and flow experience), and the responses (represented by loyalty, addiction, and compulsive buying). Theoretical Contributions is that the validated SEM structure shares the pattern of the SOR model, capturing the stimuli (both personal and flow activity levels), the organism (trust, enjoyment, and flow experience), and responses (represented by loyalty, addiction, and compulsive buying). Practical Implications is that Consumer behavior should be guided by notions of social capital, social exchange, and trust. The social context is an essential stimulant in a socio-commercial environment like live streaming e-commerce. This study gives several examples, such as the capacity of perceived social values to increase consumer trust predictably; and the social influence on consumers to elicit affective emotions like enjoyment through interactions and support from others throughout the decision-making process and in the environment of live-streamed shopping.