This study proposes an integrated scheduling optimization model for human staff and service robots (kiosks, logistics robots) to enhance operational efficiency in the hotel industry, which faces chronic labor shortages and rapid labor cost increases. Hotel managers have traditionally employed complex staffing strategies, such as cross-training human staff to work across multiple departments, to improve operational efficiency. However, securing this human resource-based flexibility also increases management costs and operational complexity. Analysis of numerical examples in this study confirms that robot adoption is an alternative that not only reduces costs but also dramatically lowers the complexity of workforce management. When operating solely with human staff, significant differences in operational efficiency arose depending on whether cross-departmental work was permitted, making detailed deployment strategies by managers essential. Conversely, in environments with service robots, stable operations became possible without relying on the flexibility of human staff deployment, due to the robots' constant operational capability and high cost-effectiveness. In conclusion, robot adoption suggests it is a key strategic tool that simultaneously resolves managers' administrative concerns about human staff multifunctionality and complex scheduling, while ensuring service quality maintenance and operational stability.

Keywords

Service Robot, Staff Scheduling, Integrated Optimization Model, Operational Flexibility, and Hotel Operational Stability.