방법 비교

	LODGSERV Lodging Service Quality Index	RevPAR Performance Analysis
분야	Tourism Hospitality	Tourism
계열	Latent structure	Regression model
기원 연도	1990	2001
창시자	Bonnie Knutson; Pete Stevens; Colleen Wullaert; Mark Patton; Fumito Yokoyama	Cathy A. Enz, Linda Canina & Kate Walsh (RevPAR benchmarking critique)
유형	Multi-item service-quality expectations index	Descriptive performance-metric analysis and benchmarking of hotel revenue indicators
원전	Knutson, B., Stevens, P., Wullaert, C., Patton, M., & Yokoyama, F. (1990). LODGSERV: A Service Quality Index for the Lodging Industry. Hospitality Research Journal, 14(2), 277-284.	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.
별칭	LODGSERV, Lodging Service Quality Index, Hotel Expectation Service Quality Index, Lodging SERVQUAL	Revenue per Available Room Analysis, Hotel KPI Analysis, RevPAR Index Analysis, Hotel Performance Benchmarking
관련	4	3
요약	LODGSERV is a 26-item index developed by Knutson, Stevens, Wullaert, Patton, and Yokoyama in 1990 to measure consumers' expectations of service quality in the hotel experience. Building directly on the SERVQUAL framework, it organizes lodging expectations into the five generic service-quality dimensions — tangibles, reliability, responsiveness, assurance, and empathy — and was reported with a high internal-consistency reliability of 0.92. LODGSERV was one of the first industry-specific adaptations of SERVQUAL and served as the methodological forerunner to the restaurant-focused DINESERV from the same research group. It gives hoteliers a validated way to capture what guests expect from a stay and to structure those expectations for comparison with delivered performance.	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.