Online games are garnering large numbers of gamers, stimulating strong competition among game developers, who continue to explore new ways to increase the amount of time players spend on such games. Online games require players to concentrate on game content, seek knowledge and learn how to complete in-game tasks. However, past research has not examined how knowledge seeking intensity, which likely strengthens knowledge schemas and helps foster game loyalty and use, motivates online gameplay. To address this research gap, we draw on schema theory to construct a research model and test it using both survey and system-captured data from 385 players. We found that knowledge seeking intensity has a stronger effect than does in-game flow on enhancing players’ knowledge schemas and learning satisfaction, thus facilitating their goal progress and further strengthening their game loyalty and actual game use. We modelled and examined the mechanism underlying the influence of knowledge seeking intensity and in-game flow on knowledge schemas. Specifically, we suggest that game developers should establish actionable strategies by urging players to seek more in-game knowledge that ensures players’ further engagement.

In a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause drastic and widespread shifts in many aspects of life that are comparable to those of the Internet and smartphones. More specifically, generative AI utilizes machine learning, neural networks, and other techniques to generate new content (e.g. text, images, music) by analyzing patterns and information from the training data. This has enabled generative AI to have a wide range of applications, from creating personalized content to improving business operations. Despite its many benefits, there are also significant concerns about the negative implications of generative AI. In view of this, the current article brings together experts in a variety of fields to expound and provide multi-disciplinary insights on the opportunities, challenges, and research agendas of generative AI in specific industries (i.e. marketing, healthcare, human resource, education, banking, retailing, the workplace, manufacturing, and sustainable IT management).

Lack of user participation and contribution has been a long-standing problem for online communities. We proposed and examined new strategies for cultivating opinion leadership and enabling users to post articles outside of the community theme. We used social role theory to propose that online communities should encourage highly committed users to take administrator roles, which will increase their opinion leadership and contributions to both public spaces and their own user-controlled spaces. We collected multiple-wave and multiple-source data from 1,115 users of a large online community. The results indicate that encouraging users to take administrator roles increases their community contributions.