This study examines the mechanisms underlying the relationship between motivation and massive open online course (MOOC) learning intention, and the contextual moderators that affect this mechanism. Drawing on motivational theory and the related literature, this study investigates how motivation affects students’ intention to learn with MOOCs and the related meditation and moderation effects. The findings of our study show that both extrinsic and intrinsic motivations have a significant influence on intention to learn with MOOCs. In addition, the results also suggest that the relationship between extrinsic motivation and intention to learn is mediated by the technology fit perceived by learners but not the relationship between intrinsic motivation and intention to learn. Furthermore, the relationships between both extrinsic and intrinsic motivation and intention to learn are moderated by subjective norms. This study enriches the extant literature on the impact of technology fit and subjective norms on MOOC learning. Few studies have focused on how students can be effectively encouraged to take MOOCs. Given the lack of theoretical and empirical research, this study developed a theoretical model and conducted an empirical study to fill the research gap.

This study examines the impacts of psychological empowerment and subjective norm on knowledge sharing in organizations, and the moderation effects aroused by power distance. Quantitative data from 567 valid questionnaires are collected by survey from a large company. The results demonstrate that subjective norm and psychological empowerment are positively associated with attitude toward knowledge sharing. Moreover, the findings further suggest that power distance undermines the influence of psychological empowerment on knowledge sharing but strengthens the effect of motivation to comply. Both theoretical and practical implications are discussed.

The existence of network effects not only changes traditional product diffusion patterns but also has significant impacts on individuals’ decision behaviors. Previous studies on competitive product diffusion have focused on macro-level diffusion speed and effects while neglecting the micro-level impacts of individual heterogeneity and social interaction on product diffusion. This paper introduces the individual heterogeneities and social interactions of consumers into the competitive product diffusion model on the basis of a two-sided market framework and complex network theory. We proposed a small world network model and behavioral game theory. Specifically, the small world network model was used to build interactions between users, and behavioral game theory was utilized to describe the interactions between users. In our model, the direct network effect was distinguished from the indirect network effect on the basis of the synergy of multiple complementary products. The results show that the final distribution often presented a situation wherein two products coexisted, but the market share was very different. In an asymmetric first-mover situation, the direct network effect dominated the indirect network effect. Moreover, the dominant position of one product at present can be changed by the other under certain conditions. Finally, when the switching and learning costs were high, the market maintained its concentration, and the prior platform was unable to dominate the market. A decrease in the costs raised the prior platform’s market share and the speed of market occupation.

A Q&A community typically employs various types of external incentives to motivate knowledge contribution from their community members. This study aims to examine the effects of different external incentives, which are conceptualized as different types of motivational factors, on community participants’ sustained knowledge contribution. Drawing on motivation crowding theory, the present study proposes that different motivators interact and jointly influence knowledge contribution behavior. The panel data were collected from a Chinese Q&A community by using the Python Scrapy crawler, and the Poisson regression model with fixed effects was used to validate the integrative model. The results revealed that generalized reciprocity and social learning undermined the effect of online attractiveness on sustained knowledge contribution, whereas peer feedback strengthens this effect. The findings contribute to the extant research on sustained contribution behavior and provide practical insights into sustaining virtual communities.