Understanding Healthcare Knowledge Diffusion in WeChat

Social media such as We Chat provide new ways of communicating healthcare information and knowledge. Many healthcare institutions leverage We Chat public platform to disseminate healthcare knowledge in the hope of attracting public attention. It is critical for them to build a comprehensive understanding of the factors affecting WeChat users’ willingness to diffuse healthcare knowledge, an issue that has seldom been studied in the literature. This research aims to address this gap. Drawing on prior research on word-of-mouth, we develop a research model by integrating six factors regarding three key elements of healthcare knowledge communications: content (interestingness, usefulness, emotionality and positivity), source (source credibility) and channel (institution-based trust). The research model will be tested through a scenario-based online survey. This research is expected to contribute by (1) integrating factors that determine healthcare knowledge diffusion including the factors about content, source and channel, especially including institution-based trust as an important determinant, (2) examining the diffusion of healthcare knowledge and taking WeChat as the research context, and (3) using survey with subjective measurements to test a more comprehensive model. Potential practical implications are offered for healthcare organizations and practitioners

Heterogeneous characters modeling of instant message services users’ online behavior

Research on temporal characteristics of human dynamics has attracted much attentions for its contribution to various areas such as communication, medical treatment, finance, etc. Existing studies show that the time intervals between two consecutive events present different non-Poisson characteristics, such as power-law, Pareto, bimodal distribution of power-law, exponential distribution, piecewise power-law, et al. With the occurrences of new services, new types of distributions may arise. In this paper, we study the distributions of the time intervals between two consecutive visits to QQ and WeChat service, the top two popular instant messaging services in China, and present a new finding that when the value of statistical unit T is set to 0.001s, the inter-event time distribution follows a piecewise distribution of exponential and power-law, indicating the heterogeneous character of IM services users’ online behavior in different time scales. We infer that the heterogeneous character is related to the communication mechanism of IM and the habits of users. Then we develop a combination model of exponential model and interest model to characterize the heterogeneity. Furthermore, we find that the exponent of the inter-event time distribution of the same service is different in two cities, which is correlated with the popularity of the services. Our research is useful for the application of information diffusion, prediction of economic development of cities, and so on.National Natural Science Foundation (China) (61201153)National Basic Research Program of China (973 Program) (Grant 2012CB315805)CCF Venus Research Project (CCF-VenustechRP2016004)Jiangsu Industrial Technology Research Institute. Institute of Future Networks Technology (BY2013095-2-16

Analysis of Users' Behaviour and Adoption Trends of Social Media Payment Platforms

The recent proliferation of Electronic Commerce (E-commerce) has been further escalated by multifaceted emerging payment solutions such as cryptocurrencies, mobile, peer-to-peer (P2P) and social media payment platforms. While these technological advancements are gaining tremendous popularity, mostly for their ease of use, various impediments such as security and privacy concerns, societal and cultural norms etc. forbear the users' adoption trends to some extents. This article examines the current status of the social media payment platforms as well as the projection of future adoption trends. Our research underlines the motivations and obstacles to the adoption of social media platforms

Social Environment of Virtual Collaboration Using Mobile Social Media

Mobile social media such as WhatsApp and WeChat greatly facilitate virtual collaboration within and across organizations. Based on the theory of self-interest and collective action, this study investigates how social environment influences user behavior. Corresponding to social capital, weak ties, and adoption thresholds, extrinsic motivation, communication climate and top management support are identified respectively as the main factors of member environment, group environment and organization environment that impact virtual collaboration. The research model hypothesizes that these social-level variables interact with the psychological processes related to technology use at the individual level. The survey results from virtual teams provide supporting evidence to most hypothesized relationships. The findings yield some interesting theoretical and practical implications for the collaborative use of social information systems

Examining Individuals’ Ads Click Intention in the Wechat Moments: A Lens of Elaboration Likelihood Model

Drawing upon elaboration likelihood model (ELM), we compared the dual routesin determining users’ ads click intentions and examined the mediation mechanism of cognitive vs. affective trust on the influence processesin the Wechat Moments. A scenario-based survey was conducted in a university of China, and 183 data was collected. Structural equation modelling analysis was used to test the research model. The empirical results suggestedthat content personalization and social recommendation weresignificant antecedents of ads click intention, and their effects weremediated by cognitive trust and affective trust. Moreover, amulti-group analysis indicatedthat the two influence processes weremoderated by prior product experience. Theoretical and practical implications areillustrated in the final section