RESEARCH NOTES AND REPORTS
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Annals of Tourism Research, Vol. 31, No. 3, pp. 712–715, 2004 # 2004 Elsevier Ltd. All rights reserved. Printed in Great Britain 0160-7383/$30.00
A DEA Evaluation of Taipei Hotels
Wan-Erh Chiang Ming-Hone Tsai Li Shau-Mei Wang National Central University, Taiwan It is always a major concern for top management to measure efﬁciency. Data Envelopment Analysis (DEA) is an excellent tool for assessing the relative efﬁciency of decision-making units. This research is aimed at measuring hotel performance by DEA under three operational styles of International Tourist Hotels (ITHs) commonly seen in Taiwan since 2000: Independently owned and operated, franchise licensed, and managed by international hotel operators. The results are expected to provide hoteliers with a basis for constructing strategies and promotion plans. With carefully selected indicators (input/output variables), DEA is able to locate and diagnose inefﬁciencies, and to provide information for improvements. Several in-depth interviews were conducted with top managers of some Taipei ITHs for critical indicators. Therefore, this study explored the operational efﬁciency of ITHs not only from a theoretical standpoint but also according to ideas and practical experiences of hoteliers. The data were obtained from the Annual Operation Report of the ITHs 2000, published by the Tourism Bureau of Taiwan. On the basis of market segmentation and geographical location variation 712
RESEARCH NOTES AND REPORTS
Table 1. Estimated Overall, Pure Technical, and Scale Efﬁciency Scores DMU Overall Efﬁciency Pure Technical Efﬁciency Scale Efﬁciency
A. Franchise Licensed Hotel 16 0.878 Hotel 18 1 Hotel 21 1 B. Internationally Managed Hotel 6 1 Hotel 11 1 Hotel 12 0.978 Hotel 15 0.730 Hotel 25 1 C. Independently Hotel 1 Hotel 2 Hotel 3 Hotel 4 Hotel 5 Hotel 7 Hotel 8 Hotel 9 Hotel 10 Hotel 13 Hotel 14 Hotel 17 Hotel 19 Hotel 20 Hotel 22 Hotel 23 Hotel 24
0.885 1 1 1 1 0.984 0.838 1
0.992 1 1 1 1 0.994 0.872 1 0.989 1 1 1 1 0.885 1 0.986 1 1 0.985 0.943 1 0.887 0.996 1 0.942
Owned and Operated 0.877 0.886 1 1 1 1 1 1 1 1 0.677 0.765 1 1 0.716 0.726 1 1 1 1 0.727 0.738 0.65 0.69 1 1 0.887 1 0.711 0.714 1 1 0.942 1
(Ismail, Dalbor and Mills 2002), 25 four or ﬁve star hotels in Taipei were selected for evaluation. The four input variables chosen by the hoteliers were hotel rooms, food and beverage (F&B) capacity (area in pings, the total space utilized by all such outlets in a hotel), number of employees, and total cost of the hotel (including employee salaries, F&B costs, room costs, utilities, advertising, operational cost, maintenance fees, taxes, and miscellaneous costs). The three output variables were yielding index, F&B revenue (the total generated from such businesses), and miscellaneous revenue (the total excluding the room and F&B revenues). The RevPar (revenue per available room) is the most universally accepted measure for overall hotel operating performance (Enz and Canina 2002). Yielding index (personal communication with R. Hanks in 1998, Cornell School of Hotel Administration) is used speciﬁcally to examine room performance (yielding index = RevPar of individual hotel/Market RevPar). If the yielding index for an individual hotel is greater than one, it means that its performance is better...
References: Banker, R., A. Charnes, and W. Cooper 2003 Some Models for Estimating Technical and Scale Inefﬁciencies in Data Envelopment Analysis. Management Science 30:1078–1092. Charnes, A., W. Cooper, and E. Rhodes 1999 Measuring the Efﬁciency of Decision Making Units. European Journal of Operational Research 2:429–444. Enz, C., and L. Canina 2002 Best of Times, The Worst of Times: Differences in Hotel Performance Following 9/11. Cornell Hotel and Restaurant Administration Quarterly 43(5):22–32. Ismail, J., M. Dalbor, and J. Mills 1991 Using RevPar To Analyze Lodging- Segment Variability. Cornell Hotel and Restaurant Administration Quarterly 43(5):73–80.
Submitted 4 April 2003. Resubmitted 4 July 2003. Accepted 10 July 2003. Final version 30 August 2003
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