Сравнение на методи

	RevPAR Performance Analysis	Hotel DEA Efficiency Analysis
Област	Tourism	Tourism
Семейство	Regression model	MCDM
Година на възникване	2001	1978
Създател	Cathy A. Enz, Linda Canina & Kate Walsh (RevPAR benchmarking critique)	Abraham Charnes, William W. Cooper & Edwardo Rhodes (DEA); applied to hotels by Morey & Dittman
Тип	Descriptive performance-metric analysis and benchmarking of hotel revenue indicators	Linear-programming frontier method for relative efficiency of decision making units
Основополагащ източник	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.	Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Други названия	Revenue per Available Room Analysis, Hotel KPI Analysis, RevPAR Index Analysis, Hotel Performance Benchmarking	Hotel Efficiency Benchmarking, Lodging Data Envelopment Analysis, DEA Hotel Benchmarking, Hotel Operational Efficiency Analysis
Свързани	3	3
Резюме	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 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.