In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use artificial (...) intelligence image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce. (shrink)

The online healthcare community has attained rapid development in recent years in which users are facilitated to exchange disease information and seek medical treatment. However, users’ motivation of participation in OHCs is still under investigation. Taking the perspective of user perceived value, this paper examined the impacts of different incentive levels including identity incentive, privilege incentive, and material incentive on user perceived value, user engagement, and user loyalty. To test the proposed hypotheses, the study adopted the methods of the between-subjects (...) experiment and questionnaire. Based on the data analysis by ANOVA and structural equation model, the results show there are significant differences in the impacts of different incentive levels on users’ perceived value. Most of the incentive measures exert significant effects on simple user hedonic value and community identity value. Accordingly, the research findings suggest that affective support value and self-health management value demonstrate more importance for user engagement and user loyalty. Therefore, OHCs should try to improve users’ affective support value and self-health management value which are the ultimate aims of the OHCs. Our study sheds some light on profoundly understanding the design of incentive mechanism of OHC and contributes to the research of OHC services. (shrink)