เปรียบเทียบวิธี

	Hotel DEA Efficiency Analysis	Hotel Revenue Management
สาขาวิชา	Tourism	Tourism
ตระกูล	MCDM	MCDM
ปีกำเนิด	1978	1989
ผู้ริเริ่ม	Abraham Charnes, William W. Cooper & Edwardo Rhodes (DEA); applied to hotels by Morey & Dittman	Sheryl E. Kimes
ประเภท	Linear-programming frontier method for relative efficiency of decision making units	Decision model for allocating fixed perishable capacity through demand forecasting, price differentiation, and inventory control
แหล่งต้นตำรับ	Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.	Kimes, S. E. (1989). Yield management: A tool for capacity-constrained service firms. Journal of Operations Management, 8(4), 348-363.
ชื่อเรียกอื่น	Hotel Efficiency Benchmarking, Lodging Data Envelopment Analysis, DEA Hotel Benchmarking, Hotel Operational Efficiency Analysis	Yield Management, Hotel Yield Management, Lodging Revenue Management, Capacity and Rate Optimization
ที่เกี่ยวข้อง	3	3
สรุป	Hotel DEA efficiency analysis applies data envelopment analysis, the linear-programming frontier method introduced by Charnes, Cooper, and Rhodes in 1978, to benchmark how efficiently hotels convert their inputs into outputs. Rather than assuming a functional form, DEA builds a best-practice frontier directly from the observed hotels and measures each property's efficiency as its distance from that frontier, handling multiple inputs such as rooms, staff, and expenses and multiple outputs such as revenue and occupancy simultaneously. Morey and Dittman brought the method into hospitality with their study benchmarking hotel general managers, showing that DEA can control for differences across properties and identify the efficient performers whose practices others can emulate. The result is a relative efficiency score, a set of peer benchmarks, and concrete improvement targets for each hotel.	Hotel revenue management, also called yield management, is the decision discipline of selling the right room to the right guest at the right price at the right time to maximize revenue from a fixed, perishable inventory. Sheryl Kimes's 1989 paper crystallized the concept for capacity-constrained service firms, identifying the conditions, fixed capacity, perishable inventory, segmentable demand, low marginal cost, and advance sales, under which managing yield rather than simply chasing occupancy pays off. Because an unsold room-night is lost forever, the hotel must forecast segmented demand, erect rate fences that separate price-sensitive from price-insensitive guests, and decide how much capacity to protect for higher-paying late bookers. Enz, Canina, and Walsh further showed that performance must be judged on revenue per available room rather than misleading single averages, anchoring revenue management to the right objective.