Scheduling in hybrid work environments: Maximizing employee interaction and satisfaction

This research is the first to introduce a mathematical model for hybrid workforce scheduling with a focus on enhancing in-person interaction. By integrating organizational requirements and individual preferences, it provides a framework that can be tailored to different institutional needs, offering a valuable tool to managers aiming to design hybrid work schedules. A mixed-integer linear programming model is developed to optimize weekly hybrid work schedules by maximizing in-office interactions and minimizing conflicts with employees’ remote work preferences. Numerical experiments, based on randomly generated instances, explore trade-offs between interaction and satisfaction under varying parameter values, including minimum office attendance, fixed office days, and penalties for violating employee preferences. The findings provide practical insights for managers: (1) Increasing structured office attendance substantially enhances interaction but sharply decreases employee satisfaction, particularly when fixed office days remove individual choice. (2) Skewed remote work preferences further complicate scheduling, potentially increasing dissatisfaction and reducing flexibility. (3) However, measures such as moderate enforcement of in-office presence achieves a balance, maintaining relatively high interaction with limited dissatisfaction. The proposed model can serve as a practical decision-support tool, adaptable to diverse organizational contexts and policies, offering a customized approach to equitable hybrid workforce planning.