Hybrid Work

Hybrid work, characterized by a blend of remote and in-person work arrangements, is a rapidly evolving field of study focused on optimizing productivity, employee well-being, and workplace efficiency. Current research emphasizes the development of AI-driven decision support systems, often leveraging large language models (LLMs) and machine learning, to personalize productivity tools and optimize workspace allocation based on individual preferences and real-time data like occupancy and infection risk. These efforts aim to improve workplace design, resource allocation, and communication strategies, ultimately impacting organizational effectiveness and employee satisfaction. Furthermore, research explores optimal information dissemination strategies to manage workplace occupancy safely and efficiently, particularly in the context of infectious disease transmission.