Live streaming with goods is developing rapidly as an emerging platform economic model. Consumers can interact with the e-commerce platform in real-time and get a good shopping experience. This in turn generates value co-creation behaviors such as word-of-mouth communication. However, due to the lack of effective audit mechanisms on some platforms, the phenomenon of value co-destruction among them is becoming more and more common. This brings value loss to consumers, e-commerce platforms, and other multiple subjects. Based on the SOR model, this paper collects 212 sample data by using a questionnaire survey. The impact of live banding platform characteristics on consumers' value co-creation and value co-destruction behaviors is analyzed through multiple regression and other methods. The results show that platform information quality, functional quality, and interactive quality all positively affect consumers' value co-creation behavior and negatively affect value co-destruction behavior. Perceived value plays a mediating role, and promotional incentives enhance the positive relationship between platform features and perceived value. Therefore, if the live streaming bandwagon platform provides consumers with sufficiently rich, complete, and timely product information, responds quickly to consumer needs, and has high interaction quality. Consumers are more likely to exhibit value co-creation behavior. This study enriches the theoretical results of value co-creation and value co-destruction. It provides theoretical references for live streaming platforms to inhibit consumers' value co-destructive behaviors and promote value co-creation behaviors. In practice, it is pointed out that live streaming platforms should provide consumers with real information on all aspects of the products, update and improve the performance of the platform in a timely manner, and provide regular training to the staff.

Globally, many enterprises are currently focusing on big data technology to improve their performance and operations. Recent literature points out several factors that influence the adoption of big data. However, enterprises often resist using the business value of big data due to a lack of knowledge. The purpose of this study is to investigate the factors influencing big data adoption by Chinese enterprises and to develop an indicator system based on the Motivation–Opportunity–Ability (MOA) model. Moreover, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to construct a network relationship map and to analyze its effects. Using the DEMATEL-based Analytic Network Process (ANP) (DANP) method to identify the weight distribution of index, this study quantitatively evaluates the influencing factors. The results show that leadership support, perceived usefulness, financial support, data resources, industrial development, data talents, and technical capability are key elements affecting the application of big data. Accordingly, some targeted suggestions are proposed.

Continuous enhancements of the intelligence of electronic products can lead to the homogenization of products and innovation of offline experiential marketing modes. The diversified development of brand sales channels is inevitable, to fulfill the diversified shopping demands of consumers. Based on 226 valid questionnaires, this study conducts empirical research with SPSS and AMOS to examine the impact of experience characteristics on consumer brand identity and brand loyalty. Then, the fanship consumer attribute is added to conduct path-moderating analysis. The results illustrated the following: (a) consumers act and relate experiences, which affects brand cognitive identity; thinking, acting, and relating experiences positively affect brands’ emotional identity; (b) cognitive identity and emotional identity can jointly create brand loyalty, and play a partial mediating role between offline experience and brand loyalty. Finally, the higher the fanship, the higher the consumer identity and the higher the brand loyalty. Overall, this study provides a certain basis for decision-making and suggestions for the offline operation of electronic brands.