Bonus or burden? Exploring the interplay of FOMO and attitudes on DeepSeek adoption, managing information and firm performance in China

Purpose This study aims to understand the factors influencing the adoption of DeepSeek to seek and utilize information within the company, with a focus on its impact on managing and utilizing information to enhance firm performance. Specifically, this study examines how fear of missing out (FOMO) and attitudes impact firm performance through the adoption of DeepSeek for improving task efficiency, streamlining workflows, supporting effective information management and enhancing firm performance. Design/methodology/approach Data were collected from 568 full-time employees in managerial roles in China through SoJump, a widely recognized and robust online survey platform. The data analysis was conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, utilizing the SmartPLS software. Findings Results showed that personal FOMO and social FOMO have positive impact on value-expressive and utilitarian attitude to predict DeepSeek adoption in enhancing firm performance. However, social-adjustive attitude was found to be an insignificant predictor in DeepSeek adoption. The research highlighted that there is a need for AI developers to promote DeepSeek adoption from the perspectives of roles of attitudes and motivations to enhance work efficiency, thereby improving firm performance. Originality/value By integrating self-determination theory (SDT) and functional theory of attitudes, this research provides a novel framework linking motivations, attitudes and firm performance in the context of Generative artificial intelligence (AI) (GenAI) adoption. Specifically, it highlights FOMO as a unique and powerful motivator, integrating it with functional attitude theories to predict user behavior in DeepSeek adoption This study contributes to the technology adoption literature by emphasizing the contextual relevance of China’s digital ecosystem and exploring the interplay between motivations and functional attitudes – an innovative approach in the AI context that advances our understanding of how GenAI adoption drives firm performance.