1997
DOI: 10.1002/(sici)1099-1603(199706)3:2<119::aid-pth74>3.0.co;2-2
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The use of data envelopment analysis to monitor hotel productivity
Abstract: Data envelopment analysis (DEA) was used to monitor and benchmark productivity in a chain of 15 hotels over a 12‐month period. Quarter results were compared with each other and with standard accounting data for the same period. In this way it was possible to identify and study units which showed anomalous behavour in terms of their measured productivity and gross profit. These were apparently related to factors other than size or staffing levels. Advantages and disadvantages of DEA are discussed, as well as it…
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Cited by 166 publications
(74 citation statements)
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“…Data regarding productivity outputs included number of room nights, occupancy (%), length of stay (days), average room rate (ARR), number of restaurant and banqueting covers served, and total annual revenue from RD, F&B, minor operations, and telephone. These metrics are consistent with previous studies of hotel productivity (e.g., Johns Howcroft, and Drake 1997;Sigala 2002a;Wöber 2000).…”
Section: Study Aims and Methodssupporting
confidence: 92%
“…Data regarding productivity outputs included number of room nights, occupancy (%), length of stay (days), average room rate (ARR), number of restaurant and banqueting covers served, and total annual revenue from RD, F&B, minor operations, and telephone. These metrics are consistent with previous studies of hotel productivity (e.g., Johns Howcroft, and Drake 1997;Sigala 2002a;Wöber 2000).…”
Section: Study Aims and Methodssupporting
confidence: 92%
“…Inefficient units may not only look for guidance to the individual benchmarking partners, as their characteristics may not fully match (Wöber, 2002). Instead, they can opt for identifying "hypothetical composite" units of their suggested benchmarking partners or virtual benchmarksin other words, the composite score that inefficient DMUs would have had if they were efficient (Johns et al, 1997(Johns et al, ). Ö nder et al (2017 describe the calculation of the virtual benchmark as a way of overcoming the incomparability of units, thus, as one of the ways to account for heterogeneity.…”
Section: Resultsmentioning
confidence: 99%
“……”
Section: Discussionmentioning
confidence: 98%
