This study utilized discrete event simulation (DES) in order to optimize the staff scheduling within the housekeeping department for hotel operation during high-occupancy conditions. High-occupancy situations within hotels occur during peak season times in which guests occupy a greater number of rooms than throughout the year. A literature review showed that DES has been used to optimize various types of schedules. This study was unique in the case that it incorporates computer modeling into the staffing portion of lodging establishments; an area with limited amount of research. Data was collected from historical records and through actual observations. A validated computerized model of the hotel was constructed using Arena 13 to determine an optimal staff schedule, which would decrease guests' waiting times as well as payroll costs in the housekeeping department. A sensitivity analysis was conducted in order to determine the number housekeepers to employ and their length of schedule depending on the acceptable wait time allowed for guests and the number of checkouts. The product of this study was a model that could be used by other lodging establishments to determine how many housekeepers to employ based on the number of rooms checking out and staying over. Future studies could incorporate the rate to stay at the establishment and how that could have an effect on the arrival rate of guests and their willingness to stay at the hotel.
","abstract_html":"<p>This study utilized discrete event simulation (DES) in order to optimize the staff scheduling within the housekeeping department for hotel operation during high-occupancy conditions. High-occupancy situations within hotels occur during peak season times in which guests occupy a greater number of rooms than throughout the year. A literature review showed that DES has been used to optimize various types of schedules. This study was unique in the case that it incorporates computer modeling into the staffing portion of lodging establishments; an area with limited amount of research. Data was collected from historical records and through actual observations. A validated computerized model of the hotel was constructed using Arena 13 to determine an optimal staff schedule, which would decrease guests' waiting times as well as payroll costs in the housekeeping department. A sensitivity analysis was conducted in order to determine the number housekeepers to employ and their length of schedule depending on the acceptable wait time allowed for guests and the number of checkouts. The product of this study was a model that could be used by other lodging establishments to determine how many housekeepers to employ based on the number of rooms checking out and staying over. Future studies could incorporate the rate to stay at the establishment and how that could have an effect on the arrival rate of guests and their willingness to stay at the hotel.</p>","abstract_has_math":false,"creators":["Malony, Robert Joseph"],"institution":null,"degree_name":"Master of Science in Human Factors & Systems","degree_level":"Thesis - Open Access","degree_discipline":"Human Factors and Systems","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-10-01T07:00:00Z","date_published":"2011-10-01T07:00:00Z","updated_at":"2026-07-27T19:26:22Z","subjects":["staff scheduling","hospitality","service efficiency","DES","high-occupancy","Hospitality Administration and Management"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/99","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Malony, Robert Joseph"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Human Factors and Systems"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Human Factors & Systems"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["staff scheduling","hospitality","service efficiency","DES","high-occupancy","Hospitality Administration and Management"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/99"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This study utilized discrete event simulation (DES) in order to optimize the staff scheduling within the housekeeping department for hotel operation during high-occupancy conditions. High-occupancy situations within hotels occur during peak season times in which guests occupy a greater number of rooms than throughout the year. A literature review showed that DES has been used to optimize various types of schedules. This study was unique in the case that it incorporates computer modeling into the staffing portion of lodging establishments; an area with limited amount of research. Data was collected from historical records and through actual observations. A validated computerized model of the hotel was constructed using Arena 13 to determine an optimal staff schedule, which would decrease guests' waiting times as well as payroll costs in the housekeeping department. A sensitivity analysis was conducted in order to determine the number housekeepers to employ and their length of schedule depending on the acceptable wait time allowed for guests and the number of checkouts. The product of this study was a model that could be used by other lodging establishments to determine how many housekeepers to employ based on the number of rooms checking out and staying over. Future studies could incorporate the rate to stay at the establishment and how that could have an effect on the arrival rate of guests and their willingness to stay at the hotel.
"]},{"key":"dc:title","label":"Title","values":["Analysis of Staff Scheduling Effect on Hospitality Staffing Service Efficiency During High-Occupancy Conditions Using Discrete Event Simulation (DES)"]}]}],"canonical_facts":{"dc:creator":["Malony, Robert Joseph"],"dc:description.abstract":["This study utilized discrete event simulation (DES) in order to optimize the staff scheduling within the housekeeping department for hotel operation during high-occupancy conditions. High-occupancy situations within hotels occur during peak season times in which guests occupy a greater number of rooms than throughout the year. A literature review showed that DES has been used to optimize various types of schedules. This study was unique in the case that it incorporates computer modeling into the staffing portion of lodging establishments; an area with limited amount of research. Data was collected from historical records and through actual observations. A validated computerized model of the hotel was constructed using Arena 13 to determine an optimal staff schedule, which would decrease guests' waiting times as well as payroll costs in the housekeeping department. A sensitivity analysis was conducted in order to determine the number housekeepers to employ and their length of schedule depending on the acceptable wait time allowed for guests and the number of checkouts. The product of this study was a model that could be used by other lodging establishments to determine how many housekeepers to employ based on the number of rooms checking out and staying over. Future studies could incorporate the rate to stay at the establishment and how that could have an effect on the arrival rate of guests and their willingness to stay at the hotel.
"],"dc:identifier":["https://commons.erau.edu/edt/99"],"dc:subject":["staff scheduling","hospitality","service efficiency","DES","high-occupancy","Hospitality Administration and Management"],"dc:title":["Analysis of Staff Scheduling Effect on Hospitality Staffing Service Efficiency During High-Occupancy Conditions Using Discrete Event Simulation (DES)"],"thesis:degree_discipline":["Human Factors and Systems"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Human Factors & Systems"]},"updated_at":"2026-07-27T19:26:22Z"}