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題名:重大災難對台北國際觀光旅館經營績效的影響
作者:江莞兒
作者(外文):Wan-Erh Chiang
校院名稱:國立中央大學
系所名稱:企業管理學系
指導教授:蔡明宏
李小梅
學位類別:博士
出版日期:2005
主題關鍵詞:國際觀光旅館季節調整經營績效資料包絡分析921 EarthquakeSARS Outbreak911 Terrorists AttacksHotel
原始連結:連回原系統網址new window
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自一九九九年至二00三年五年期間,台灣歷經三個重大災難--九二一地震,九一一恐怖攻擊,及SARS疫情的蔓延。其對觀光產業影響甚鉅。在政府推出『挑戰二00八:國家發展重點計畫』致力推動「觀光客倍增計畫」的背景之下,為釐清災難對國際觀光旅館經營績效(hotel performance)所造成之衝擊,本研究探討之焦點著重在災難對觀光旅館住房表現之變化。透過大台北地區國際觀光旅館五年間的月營運資料,分析災難影響飯店營運的程度(magnitude)與期間(duration),以及住房率與房價的關係。X12-ARIMA用來調整時間、季節對於觀光需求的影響。資料包絡分析用來區隔旅館之經營有效率或無效率。分析結果顯示,在九二一地震期間,台北地區國際觀光旅館業績平均下跌2.25個月,RevPAR平均累積下滑16.1%。相較於獨立經營的旅館,連鎖旅館有較佳的表現,,但不顯著。而以日本為主要客源的飯店,損失明顯比其他飯店嚴重。以往經營有效率的飯店,損失有比較輕微,但統計上不顯著。在九一一恐怖攻擊事件中,台北地區國際觀光旅館業績平均下跌2.18個月,RevPAR平均下滑 13.35 %。相較於獨立經營的旅館,連鎖旅館的損失較少,並不顯著。以日本為主要客源的飯店,業績損失雖然較大,但也不顯著。以往經營有效率的飯店,損失比較少,也不顯著。而在 SARS疫情爆發期間,台北地區國際觀光旅館住房業績巨幅下跌,影響有8.8個月之久,RevPAR平均累積下滑 288.8%。相較於獨立經營的旅館,連鎖旅館有較低的損失,但在統計上並不顯著。以日本為主要客源的飯店,業績損失非常高,顯著高於其他飯店。以往經營有效率的飯店,損失較少,但統計上不顯著。
During the year of 1999 to 2003, the tourism demand of Taiwan had encountered three devastating disasters: the September 21 earthquake in 1999, the 911 terrorist attacks in the USA in 2001, and the SARS outbreak in the second quarter of 2003. The X-12-ARIMA was applied to adjust the seasonal factors and further to examine the impact of disasters on the hotel performance in Taipei. The results show that the international tourist hotels suffered the greatest loss during the SARS outbreak, with an average loss of 288.8% in RevPAR for 8.8 months, followed by the 921 earthquake (16.1% in 2.25 months), and the 911 terrorist attacks (13.35% in 2.18 months).
During the 921 earthquake, the chain hotels have a lower mean RevPAR decline than the independent hotels. The hotels targeting at Japanese market suffer a significantly higher average RevPAR loss than the others. The efficient hotels have a lower average RevPAR loss.
During the 911 terrorist attacks, the chain hotels have a lower mean RevPAR decline than the independent ones. The hotels targeting at Japanese market have a higher RevPAR loss than the other ones. The efficient hotels experience less decline than the inefficient hotels.
Among the three disasters, the SARS outbreak had the biggest influence toward hotel performance. The chain hotels have a relative lower RevPAR than the independent ones. The hotels targeting at Japanese market have a higher RevPAR loss than the others. Relatively, the efficient hotels have less loss than the inefficient hotels.
REFERENCES

Banker, R.D., A. Charnes, and W. W. Cooper (1984). Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science 30(9):1078-1092.

Basso, A., and S. Funari (2001). A Data Envelopment Analysis Approach to Measure the Mutual Fund Performance. European Journal of Operational Research 135: 477-492.

Bowlin, W. F. (1987). Evaluating the Efficiency of US Air Force Real-Property Maintenance Activities. Journal of Operational Research Society 38(2):127-135.

Chandra, P., W.W. Cooper, S. Li, and A. Rahman (1998). Using DEA to Evaluate 29 Canadian Textile Companies--Considering Returns to Scale. International Journal of Production Economics 54:129-141.

Charnes, A., W. W. Cooper, and E. Rhodes (1978). Measuring the Efficiency of Decision Making Units. European Journal of Operational Research 2:429-444.

Chen, T. (1997). A Measurement of the Resource Utilization Efficiency of University Libraries. International Journal of Production Economics 53:71-80

Chen, T. (2001). An Assessment of Technical Efficiency and Cross-efficiency in Taiwan’s Electricity Distribution Sector. European Journal of Operational Research 1-13.

Chien, G. and Law, R. (2003). The Impact of the Severe Acute Respiratory Syndrome on Hotels: a case study of Hong Kong. Tourism Management 22:327-332.

Chilingerian, J. A., and H. D. Sherman (1990). Managing Physician Efficiency and Effectiveness Providing Hospital Services. Health Service Management Research 3(1): 3-15.

Chon, K. and R. T. Sparrowe (2000) Welcome to Hospitality…An Introduction. Albany, NY: Delmar.

CNN Television News Report (2001). CNN Television News Report, October 5.

Coelli, T., D. S. Prasada Rao, and G. E. Battese (1998). An Introduction To Efficiency and Productivity Analysis. Boston: Kluwer Academic Publisher.

Cummins, J. D., S. Tennyson, and M.A. Weiss (1999). Consolidation and Efficiency in the US Life Insurance Industry. Journal of Banking & Finance 23:325-357

Dagum, E. B. (1988). The X-11-ARIMA/88 Seasonal Adjustment Method: Foundations and User’s Manual, Ottawa:Statistc Canada.

Easun, S. (1994). Beginner’s Guide to Efficiency Measurement: an Application of Data Envelopment Analysis to selected school libraries in California. School Library Media Quart 22(2):103-106.

Enz, C.A., & Canina, L. (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.

Findley, D.F., Monsell, B.C., W.R., Otto, M.C., and Chen, B.C. (1998). New capabilities and Methods of the X-12-ARIMA Seasonal Adjustment
Program. Journal of Business and Economic Statistics 16:127-176.

Golany, B. and Y. Roll (1989) An Application Procedure for DEA. OMEGA 17 (3): 237-250.

Goodrich, J.N. (2001). September 11, 2001 attack on America: a record of the immediate impacts and reactions in the USA travel and tourism industry. Tourism Management 23:573-580

Hanks, R.D. (1998). Strategic Pricing and Revenue Management for Hotels. Professional Development Program. Hotel School of Cornell University, Summer Seminar.

Huan, T.C., Beaman, J., and Shelby, L. (2004). No-Escape Natural Disaster—Mitigating Impacts on Tourism. Annals of Tourism Research 31(2): 255-273.
Huang, J.H. and Min, J.C.H. (2002). Earthquake Devastation and Recovery in Tourism: the Taiwan Case. Tourism Management 23:145-154.

Hwang, S.N. and Chang, T.Y. (2003). Using Data Envelopment Analysis to Measure Hotel Managerial Efficiency Change in Taiwan. Tourism Management 24:357-369.

Ismail, A. (2002). Front Office – Operations and Management. Thomas Delmar: Albany, NY.

Ismail, J.A., Dalbor, M.C., & Mills, J.E. (2002). Using RevPAR To Analyze Lodging- Segment Variability. Cornell Hotel and Restaurant Administration Quarterly 43(5): 73-80.

Jurow, S. (1993) Tools for Measuring and Improving Performance. Journal of Library Administration 18:113-126

Kao, C. and Y. C. Yang (1992) Reorganization of Forest Districts via Efficiency Measurement. European Journal of Operational Research 58(3): 356-362

Kao, C. (1994) Evaluation of Junior Colleges of Technology: The Taiwan Case. European Journal of Operational Research 73: 487-494.

Koening, N. and Bischoff, E. E. (2004). Analyzing Seasonality in Welsh Room Occupancy Data. Annals of Tourism Research 31(2): 374-392

Kerstens, K. (1996) Technical Efficiency Measurement and Explanation of French Urban Transit Companies. Transportation Research Part A: Policy and Practice 30(6):431-452

Lewin, A. Y., and J.W. Minton (1986) Determining Organizational Effectiveness: Another Look, and an Agenda for Research. Management Science 32(5): 514-536.

Lim, C. and McAleer, M. (2002). Time Series Forecasts of International Travel Demand for Australia. Tourism Management 23:389-396

Lothgren, M., and M. Tambour (1999). Productivity and Customer Satisfaction in Swedish Pharmacies: A DEA Network Model. European Journal of Operational Research 15: 449-458.

National Fire Administration (1999). Statistics of September 21st Earthquake. Republic of China: Ministry of Interior.

Schaffnit, C., D. Rosen, and J.C. Paradi (1997). Best Practice Analysis of Bank Branches: An Application of DEA in a Large Canadian Bank. European Journal of Operational Research 98(2):269-289

Schefczyk, M. (1993).Traditional Performance of Airlines: An Extension of Traditional Measurement Paradigms. Strategic Management Journal 14(4): 301-317.

Sherman, H. D., and F. Gold (1985).Bank Branch Operating Efficiency: Evaluation with Data Envelopment Analysis. Journal of Banking and Finance 9(2): 297-315

Shiskin, J., Young, A. H., and Musgrave, J.C. (1967). The X-11 Variant of the Census Method II Seasonal Adjustment Program. Technical Paper No. 15, U.S. Department of Commerce, Bureau of Census.

Sonmez, S.F., Apostolopoulos, Y., and Tarlow, P. (1999). Tourism in Crisis: Managing the Effects of Terrorism. Journal of Travel Research 38:13-18.
Taiwan Economic News (2003) Leading Hotels Provide Instant Offices for SARS-wary Execs, May 16.

Taiwan News (2003). Tourism Bureau Launches Campaigns, June 12.
Tan, S. (2001). Hotels Hope Tourist Drought End Soon. Nationwide Losses Could Reach $2B. Miami Herald, September 28.

Thanassoulis, E. and Dunstan P. (1994).Guiding Schools to Improved Performance Using Data Envelopment Analysis: An Illustration with Data from a Local Education Authority. Journal of the Operational Research Society 45(11): 1247-1262.

Tourism Bureau (2000~2004). Annual Report on Tourism, Republic of China. Taipei: Tourism Bureau.

Tourism Bureau (1999~2004). Hotel Operation Report. Available at

Tsaur, S. H. (2000). The Operating Efficiency of International Tourist Hotels in Taiwan. Asia Pacific Journal of Tourism Research 6(1):29-37.

Vallen, G.., and J. Vallen (2000). Check in Check out. Englewood, NJ: Prentice Hall.

Walker, J. R. (2002). Introduction to Hospitality, 3/e. Englewood, NJ: Prentice Hall.

Weissinger, S. S. (2000). Hotel/Motel Operations—An overview. Delmar: Canada

WHO (2004). Summary of Probable SARS Cases with Onset of Illness from 1 November 2002 to 31 July 2003

Wolchuk, S. and Scoviak, M. (2004). Hotels’ 325. Hotels Magazine, July. 38-40. also available at

World Travel & Tourism Council (2004). The 2004 Travel & Tourism Economic Research.
 
 
 
 
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