So sánh phương pháp

	RevPAR Performance Analysis	Hotel Revenue Management
Lĩnh vực	Tourism	Tourism
Họ	Regression model	MCDM
Năm ra đời	2001	1989
Người khởi xướng	Cathy A. Enz, Linda Canina & Kate Walsh (RevPAR benchmarking critique)	Sheryl E. Kimes
Loại	Descriptive performance-metric analysis and benchmarking of hotel revenue indicators	Decision model for allocating fixed perishable capacity through demand forecasting, price differentiation, and inventory control
Công trình gốc	Enz, C. A., Canina, L., & Walsh, K. (2001). Hotel-industry averages: An inaccurate tool for measuring performance. Cornell Hotel and Restaurant Administration Quarterly, 42(6), 22-32.	Kimes, S. E. (1989). Yield management: A tool for capacity-constrained service firms. Journal of Operations Management, 8(4), 348-363.
Tên gọi khác	Revenue per Available Room Analysis, Hotel KPI Analysis, RevPAR Index Analysis, Hotel Performance Benchmarking	Yield Management, Hotel Yield Management, Lodging Revenue Management, Capacity and Rate Optimization
Liên quan	3	3
Tóm tắt	RevPAR performance analysis is the practice of measuring, decomposing, and benchmarking hotel performance using revenue per available room and its companion metrics. RevPAR distills a hotel's success into a single figure, rooms revenue divided by rooms available, that equals average daily rate multiplied by occupancy and so captures both the price a hotel commands and how full it is. The metric anchors revenue management, whose objective Kimes framed as maximizing yield from fixed capacity, and it is the standard yardstick for comparing hotels. Enz, Canina, and Walsh, however, showed that relying on single industry averages is misleading because hotel performance is dispersed and skewed, which is why rigorous RevPAR analysis decomposes the metric into its drivers and benchmarks it against a competitive set with indices rather than crude averages.	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.