Learning and skill set formation: A structural examination of version upgrades, user visibility, and AI strategies

• 成果类型: Article
• 署名作者: Chen, Jialie
• 署名单位: University of Arkansas System; University of Arkansas Fayetteville; University of Arkansas System; University of Arkansas Fayetteville
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.14065
• 发表日期: 2023
• 页码: 3856-3872
• 关键词: interactive dynamics; learning; massively multiplayer online role-playing game; structural model; user/player engagement

摘要

For many multiplayer games, including massively multiplayer online role-playing games, consumer skill sets with the game play an important role in engagement. Despite their importance, many aspects of consumers' skill sets are still less well understood. This research considers the formation and evolution of players' skill sets from two perspectives: (1) learning-by-doing, in which a consumer gradually improves his or her skill set with the game from past experiences with other players, and (2) learning about matched players' skill sets from their observed characteristics (i.e., learning-about-others). Using policy simulations, we further demonstrate how inferences of players' latent skill sets could help game developers design strategies for better engagement, from the perspectives of version upgrades, targeted user visibility, and artificial intelligence-powered bots.