近年來，受到全球經濟景氣衰退的影響，使得全球旅遊人次大幅下滑。然而，由於看好開放中國人士來台觀光帶來之效益，國內外企業紛紛投入興建觀光旅館，以爭食這塊市場大餅。面對競逐愈益加劇的變局，為使我國旅館業更具競爭力，探討台灣國際觀光旅館經營效率與生產力變動之情形，並分析管理當局所投入資源是否有效率，實為國際觀光旅館業者的首要課題。
本研究利用資料包絡分析法及其擴展模式分析國際觀光旅館當期效率，並利用Malmquist生產力指數探討台灣國際觀光旅館在2006年至2010 年生產力變動之情形，以檢視實際管理成效及所投入資源是否有效率，進而建構標竿學習路徑圖。其次，運用共同邊界模式來分析不同經營類型國際觀光旅館的經營效率，以建構技術落差比趨勢路徑。最後再以Tobit迴歸分析法探究影響經營效率差異的因素，使管理者能夠訂定有效的競爭策略。
在資料包絡分析法模式分析中，旅館總效率平均值為0.827，各旅館的無效率主要歸因於純粹技術效率的無效率。在所有旅館之中，大約有60％旅館處於規模報酬遞增階段， 23％旅館處於規模報酬遞減階段。其中，表現最佳的旅館為涵碧樓大飯店(H39)，可做為旅館營運標竿之參考。
在時間序列分析上，發現2010年相較於2009年生產力改善的旅館數目最多，而2009年相較於2008年衰退的旅館數目最多。綜合而言，近五年來，整體旅館業生產力已有所改善，並呈現效率進步的情況，但技術進步只呈現微幅成長的現象，應力求改進。
在共同邊界模式之分析結果中，可知連鎖類旅館的技術效率表現優於獨立經營類旅館，且這二類旅館的技術效率存在顯著差異。經由Tobit 迴歸模式分析得知，個別旅客比例與台北地區在5%顯著水準下對平均純粹技術效率值的影響為正向且顯著；風景區在10%顯著水準下對平均純粹技術效率值的影響為正向且顯著；而規模別與外籍旅客比例則未呈顯著差異。
本研究以橫斷面及緃斷面的效率分析模式評估國際觀光旅館的營運效率表現並建構管理決策路徑模式，由效率分析與標竿學習方向希望國際觀光旅館能以較少的資源達到最大的產出，並進而提升經營績效與競爭力，對於國際觀光旅館的發展與國家觀光旅館資源的運用可以更有幫助。

The global tourism industry has experienced a significant decline in the number of tourists in recent years because of the the global economic downturn. Nevertheless, in response to the business opportunities of catering to tourists from China, the number of international tourist hotels in Taiwan expanded. In the situation of fierce competition in the hotel market, the primary issue faced by international tourist hotel operators is to examine the efficiency and productivity changes of Taiwanese international tourist hotels.
This study used Data envelopment analysis (DEA) to investigate the operational efficiency and the Malmquist productivity index to examine the productivity changes of Taiwanese international tourist hotels from 2006 to 2010. Metafrontier model was used to compare the difference in technical efficiency between the different categories of international tourist hotels. The path diagrams of benchmarking and trend of technology gap ratio of the different categories of international tourist hotels were constructed based on the efficiency analysis results of various models. Tobit regression analysis is used to assess whether associated factors have a significant impact on the operating efficiency.
Several results are obtained. DEA analysis indicates that the average technical efficiency was 0.827 and the main factor influencing the total efficiency of hotels was inadequate pure technical efficiency. Among the hotels, approximately 60% of the hotels exhibited increasing returns to scale and 23％ of the hotels exhibited decreasing returns to scale. Above all, H39 is the benchmark hotel with the best operational efficiency.
The time series analysis found that the greatest growth in the change of productivity occurred between 2009 and 2010. In summary, the productivity of the overall hotel industry were improved with the growth of Technical Efficiency Change and Technique Change.
Metafrontier found that average technology gap of independent international tourist hotels was lower than that of chain international tourist hotels.In terms of the impact of environmental variables on efficiency, individual traveler and location did have a significant positive impact on the overall efficiency. Scale and guest nationality were not a significant factor.
This study used cross-sectional and longitudinal efficiency analysis models to analyze the efficiency and productivity changes of Taiwanese international tourist hotels and constructed managerial decision-making path models. It was hoped that international tourist hotels can yield the maximum output by using fewer resources, and their operational performance and competitiveness can be further improved from the perspectives of efficiency analysis and benchmarking, which may be more beneficial to the development of international tourist hotels and national investment in the tourist hotels resources.

參考文獻
一、 中文部份
1. 王媛慧、李文福與翁竹君（2007），“台灣國際觀光旅館業生產力與效率分析：隨機邊界距離函數之應用”，經濟論文叢刊，35，55-86。
2. 王斐青、洪維廷與尚瑞國（2005），“台灣地區國際觀光旅業生產力變動之研究”，亞太經濟管理評論，9，129-160。
3. 交通部觀光局（2006-2010），中華民國95-99年台灣地區國際觀光旅館營運分析報告，交通部觀光局。
4. 交通部觀光局（1991-2010），觀光統計年報，交通部觀光局。
5. 吳勉勤（2003），旅館管理－理論與實務，華立，61。
6. 林億明、孔維新與張晉綸（2010），“準固定要素與台灣國際觀光旅業生產力之變動”，應用經濟論叢， 生產力與效率特刊，191-225。
7. 黃珩青（2009），“觀光旅館業基本資料”，台灣經濟研究院產經資料庫。
8. 楊世華（2007），“台灣農田水利會經營效率之比較研究－三階段資料包絡分析法及meta-frontier模型之應用”，台灣大學農業經濟研究所博士論文。
9. 鄭雅穗、盧以詮與鍾仁宗（2009），“臺灣地區國際觀光旅館營運績效標竿分析－差額分析情境相依資料包絡分析法之應用”，管理評論，28(1)， 61-74。
10. 劉育昇（2009），“醫院集團之經濟分析研究”，中央大學產業經濟研究所博士論文。
11. 盧文民（2006），“整合財務資訊之績效標竿分析-國際觀光旅館產業之應用”，國立交通大學經營管理研究所博士論文。
12. 顏晃平、張靜文與吳榮杰（2008），“台灣農會信用部成本效率之研究－共同邊界函數應用”， 應用經濟論叢， 84，159-193。
13. 魏慶國（2011），“醫學中心營運標竿分析與管理決策路徑模式之建構”， 國立臺灣大學健康政策與管理研究所博士論文。
二、英文部份
1. Anderson, R.I., R. Fok, and J. Scott (2000), “Hotel industry efficiency: an advanced linear programming examination,” American Business Review, 18(1), 40-48.
2. Baker, M. and M. Riley (1994), “New Perspectives on Productivity in Hotels：Some Advances and New Directions,” International Journal of Hospitality Management, 13(4), 297-311.
3. Banker, D. Rajiv, A. Charnes and R. Clarke (1989), “Constrained Game Formulations and Interpretations for Data Envelopment Analysis,” European Journal of Operational Research, 40(3), 299-308.
4. Banker, R.D., A. Charnes, and W.W. Cooper (1984), “Some models for estimating technology and scale inefficiencies in data envelopment analysis,” Management Science, 30(9), 1078-92.
5. Barros, C. P. (2005), “Evaluating the efficiency of a small hotel chain with a Malmquist productivity index,” International Journal of Tourism Research. 7(3), 173-184.
6. Barros, C. P. (2005), “Measuring efficiency in the hotel sector,” Annals of Tourism Research, 32 (2), 456-477.
7. Barros, C.P., and F.P. Alves (2004), “Productivity in the Tourism Industry,” International Advances in Economic Research, 10(3), 215-225.
8. Barros, C. P., and C. A. Santos (2006), “The measurement of efficiency in Protuguese hotels using data envelopment analysis,” Journal of Hospitality & Tourism Research, 30 (3), 378-400.
9. Barros, C.P. and U.C. Dieke (2008), “Technical efficiency of African hotels,” International Journal of Hospitality Management, 27, 438–447.
10. Battese, G. E. and D. S. P. Rao (2002), “Technology Gap, Efficiency, and a Stochastic Metafrontier Function”, International Journal of Business and Economics, 1(2), 87-93.
11. Battese, G. E., C. J. O’Donnell, and D. S. P. Rao (2004), “A Metafrontier Frameworks Production Function for Estimation of Technical Efficiency and Technology Gap for Firms Operating Under Different Technology,” Journal of Productivity Analysis, 21, 91-103.
12. Botti, L., W. Briec, and G. Cliquet (2007), “Plural forms versus franchise and company-owned systems: A DEA approach of hotel chain performance,” The International Journal of Management Science, 37, 566 – 578.
13. Caves, D. W, L. R. Christensen and W. E. Diewert (1982), “The Economic Theory of Index Number of the Measurement of Input, Output and Productivity,” Econometrica, 50(6), 393-1414.
14. Charnes, A., W. W. Cooper, and E. Rhodes (1978), “Measuring the efficiency of decision making units,” European Journal of Operational Research, 2(6), 429-44.
15. Chen, C. F. (2006), “Applying the stochastic frontier approach to measure hotel managerial efficiency in Taiwan,” Tourism management, 28, 696-702.
16. Farrell, M.J. (1957), “The Measurement of Productive Efficiency,” Journal of the Royal Statistical Society, Series A, 120, 253-290.
17. Gleason, J.M. and D.T. Barnum (1982), “Toward Valid Measures of Public Sector Productivity: Performance Measures in Urban Transit,” Management Science, 28(4), 379-386.
18. Golany, B. and Y. Roll (1989), “An Application Procedure for DEA,” Omega, 7(3), 237-250.
19. Gunjan M. S. (2007), “Measuring efficiency of the hotel and restaurant sector: the case of India,” International Journal of Contemporary Hospitality Management, 19(5), 378-387.
20. Hu, J. L., C. N. Chiu, H. S. Shieh, and C. H. Huang (2010), “A Stochastic Cost Efficiency Analysis of International Tourist Hotels in Taiwan,” International Journal of Hospitality Management, 29, 99-107.
21. Hwang, S. N. and T. Y. Chang (2003), “Using data envelopment analysis to measure hotel managerial efficiency change in Taiwan,” Tourism Management, 24, 357-369.
22. Hayami, Y. (1969), “Sources of agricultural productivity gap among selected countries,” American Journal of Agricultural Economics, 51, 564-575.
23. Hayami, Y. and V.W. Ruttan (1971), “Agricultural development: An international perspective,” Baltimore and London: John Hopkins University Press.
24. Johnson, K. and S. Ball (1989), “Productivity Measurement in Hotels,” Tourism Marketing and Management Handbook, Englewood Cliffs：Prentice-Hall, 319-323.
25. Lewin, A. Y., R. C. Morey, and T. J. Cook (1986), “Evaluating the Administrative Efficiency of Court,” OMEGA, 10, 401-411.
26. Miranda C., F. Maria and N. Peter (2006), “Efficiency and Productivity of Italian Tourist Destinations: A Quantitative Estimation Based on Data Envelopment Analysis and the Malmqist method,” Advances in Modern Tourism Research, 325-343.
27. Morey, R. C. and D. A. Dittman (1995), “Evaluating a Hotel GM’s Performance,” Cornell Hotel and Restaurant Administration Quarterly, 36(2), 30-35.
28. Norman, M. and B. Stocker (1991), “Data Envelopment Analysis: the assessment of performance,” John Wiley and Sons, Chichester, UK.
29. O’Donnel, C. J., D. S. P. Rao, and G. E. Battese (2008), “Metafrontier frameworks for the study of firm-level efficiencies and technology ratios,” Empirical Economics, 34, 231-255.
30. Perrigot, R., G. Cliquet and I. Piot-Lepetit (2009), “Plural form Chain and Efficiency: Insights from the French hotel chains and the DEA methodology,” European Management Journal, 27 (4), 268-280.
31. Rao, D. S. P., C. J. O’Donnell and G. E. Battese (2003), “Metafrontier Functions for the Study of Inter-regional Productivity Differences,” CEPA Working Paper, No. 01/2003, Centre for Efficiency and Productivity Analysis, School of Economics, University of Queensland, Brisbane.
32. Reynolds, D. (2003), “Hospitality productivity assessment using data-envelopment analysis,” Cornell Hotel and Restaurant Administration Quarterly, 44(2), 130-137.
33. Shang, J. K., W. T. Hung and F. C. Wang (2008), “Service outsourcing and hotel performance: three-stage DEA analysis,” Applied Economics Letters, 15(13), 1053-1057.
34. Shephard, R. W. (1970), “Theory of Cost and Production Functions,” Princeton University Press, Princeton.
35. Sun, S. (2004), “Performance measurement in hotel service provision: the case of international tourist hotels in Taiwan”, paper presented at APPC2004 Conference Program, Centre for Efficiency and Productivity Analysis School of Economics, University of Queensland, Brisbane, Australia, July 14-16.
36. Sun, S. and W. M. Lu (2005), “Evaluating the Performance of the Taiwanese Hotel Industry Using a Weight Slacks-based Measure,” Asia-Pacific Journal of Operational Research, 22(4), 487-512.
37. Tobit, J. (1958), “Estimation of Relation of Relationships for Limited Dependent Variables,” Econnometrica, 26, 24-36.
38. Tsaur, S.H. and Tsai, C.W, (1999), “Cost Structure for international Tourist Hotel in Taiwan,” Asia Pacific Journal of Tourism Research, l4(1), 41-48.
39. Wang, F. C., J. K. Shang, and W. T. Hung (2006), “Productivity and Service Quality Changes of International Tourist Hotels in Taiwan,” Annals of Tourism Research, 33, 571-574.
40. Wang, F. C., W. T. Hung and J. K. Shang (2006), “Measuring Pure Managerial Efficiency of International Tourist Hotels in Taiwan,” The Service Industries Journal, 26(1), 59-71.
41. Wassenaar, D. J. and E. R. Stafford (1991), “The Lodging Index: An Economic Indicator for the Hotel/Model Industry,” Journal of Travel Research, 30(1), 18-21.
42. Wijeysinghe, B. S. (1993), “Breakeven occupancy for a hotel operation,” Management Accounting, 71(2), 32-33.
43. Yang, C. and W. M. Lu (2006), “Performance Benchmarking for Taiwan’s International Tourist Hotels,” INFOR, 44(3), 229-245.
44. World Travel & Tourism Council (2010), http://www.wttc.travel.