|
•Agarwal, V. B., & Yochum, G. R. (1998). Tourism and advertising: Evidence from Virginia Beach. International Advances in Economic Research, 4(4), 384-397. •Alon, I., Qi, M., & Sadowski, R. J. (2001). Forecasting aggregate retail sales: A comparison of artificial neural networks and traditional methods. Journal of Retailing and Consumer Services, 8(3), 147-156. •Anonymous. (1997). Forecasting for tourism. Futurist, 31(3), 3. •Archer, B. H. (1976). Demand forecasting in tourism (Occasional paper No. 9). Bangor, Wales, UK.: University of Wales Press. •Archer, B. H. (1980). Forecasting demand: Quantitative and intuitive techniques. International Journal of Tourism Management, 1(1), 5-12. •Archer, B. H. (1994a). Chapter 10 - Demand forecasting and estimation. In J. R. B. Ritchie & C. R. Goeldner (Eds.), Travel, tourism, and hospitality research: A handbook for managers and researchers (2nd ed., pp. 105-114). New York, NY: John Wiley & Sons, Inc. •Archer, B. H. (1994b). Trends in international tourism. In S. F. Witt & L. Moutinho (Eds.), Tourism marketing and management handbook. (2nd ed., pp. 93-98). Hertfordshire, UK: Prentice Hall International (UK) Ltd. •Athiyaman, A., & Robertson, R. W. (1992). Time series forecasting techniques: Short-term planning in tourism. International Journal of Contemporary Hospitality Management, 4(4), 8-11. •Au, N., & Law, R. (2000). The Application of rough sets to sightseeing expenditures. Journal of Travel Research, 39(1), 70-77. •Australian Tourist Commission. (2000, December 7). Australia must prepare for 10 million international tourists in 2010. Retrieved December 13, 2001, from http://www.atc.net.au/newscenter.asp?art=222 •Bar-On, R. R. (1979). Forecasting tourism - Theory and practice. Paper presented at the Tenth Travel and Tourism Research Association Conference, Salt Lake City, UT. •Bar-On, R. R. (1989). Chapter 5: The presentation, analysis and forecasting of time series. In Travel and tourism data: A comprehensive research handbook on the world travel industry (pp. 55-84). Phoenix, AZ: The Oryx Press. •Bar-On, R. R. V. (1989). Travel and tourism data: A comprehensive research handbook on the world travel industry. Phoenix, AZ: The Oryx Press. •Bargur, J., & Arbel, A. (1976). A comprehensive approach to the planning of the tourist industry. In C. E. Gearing, W. W. Swart & T. Var (Eds.), Planning for tourism development: Quantitative approaches. New York, NY: Praeger Publishers. •Baum, T. M., Ram. (1994). A Ricardian analysis of the fully inclusive tour industry. Service Industries Journal, 14(1), 85-93. •Blake, A., Durbarry, R., Sinclair, M. T., & Sugiyarto, G. (2001). Modelling tourism and travel using tourism satellite accounts and tourism policy and forecasting models (Discussion paper No. 2000/4). Nottingham, UK: Christel DeHaan Tourism and Travel Research Institute, Nottingham University. •Bloom, J. Z. (2005). Market segmentation: A neural network application. Annals of Tourism Research, 32(1), 93-111. •Bloom, J. Z., & Leibold, M. (1994). Challenges for the South African tourism industry to the year 2010 based upon a Delphi market research project. South African Journal of Business Management, 25(4), 127-136. •Bloom, J. Z., & Leibold, M. (1994). Demand forecasting approaches and practices in the South African tourism industry. Journal for Studies in Economics and Econometrics, 18(1), 73-89. •Brännäs, K., Hellström, J., & Nordström, J. (2002). A new approach to modelling and forecasting monthly guest nights in hotels. International Journal of Forecasting, 18(1), 19-30. •Burger, C. J. S. C., Dohnal, M., Kathrada, M., & Law, R. (2001). A practitioners guide to time-series methods for tourism demand forecasting - A case study of Durban, South Africa. Tourism Management, 22(4), 403-409. •Burkart, A. J., & Medlik, S. (1975). The Management of tourism a selection of readings. London: Heinemann. •Calantone, R. J., di Benesetto, C. A., & Bojanic, D. (1987). A comprehensive review of the tourism forecasting literature. Journal of Travel Research, 26(2), 28-39. •Carey, K. (1991). Estimation of Caribbean tourism demand: Issues in measurement and methodology. Atlantic Economic Journal, 19(3), 32-40. •Carraro, C., & Manente, M. (1995, May 30 - June 2). The TRIP and STREP forecasting models for Italy. Paper presented at the Second International Forum on Tourism Statistics, Venice, Italy. •Chan, Y.-M. (1993). Forecasting tourism: A sine wave time series regression approach. Journal of Travel Research, 32(2), 58-60. •Chan, Y.-M., Hui, T.-K., & Yuen, E. (1999). Modeling the impact of sudden environmental changes on visitor arrival forecasts: The case of the Gulf War. Journal of Travel Research, 37(4), 391-394. •Chau, P. (1985). Application of the Box-Jenkins transfer functions to forecasting domestic tourism in Canada. Ottawa, Canada: Tourism Canada. •Chen, J.-C. (2000). Forecasting method applications to recreation and tourism demand. Unpublished Ph.D. dissertation, North Carolina State University, Raleigh, NC. •Chen, R., & Fomby, T. B. (1999). Forecasting with stable seasonal pattern models with an application to Hawaiian tourism data. Journal of Business & Economic Statistics, 17(4), 497-504. •Cho, V. (2001). Tourism forecasting and its relationship with leading economic indicators. Journal of Hospitality & Tourism Research, 25(4), 399-420. •Cho, V. (2003). A comparison of three different approaches to tourist arrival forecasting. Tourism Management, 24(3), 323-330. •Choi, J.-G. (2003). Developing an economic indicator system (a forecasting technique) for the hotel industry. International Journal of Hospitality Management, 22(2), 147-159. •Choy, D. (1984). Forecasting tourism revisited. Tourism Management, 5, 171-176. •Chu, F.-L. (1998a). Forecasting tourism demand in Asian-Pacific countries. Annals of Tourism Research, 25(3), 597-615. •Chu, F.-L. (1998b). Forecasting tourism: A combined approach. Tourism Management, 19(6), 515-520. •Chu, F.-L. (1998c). Forecasting tourist arrivals: Nonlinear sine wave or ARIMA? Journal of Travel Research, 36(3), 79-84. •Chu, F.-L. (2004). Forecasting tourism demand: A cubic polynomial approach. Tourism Management, 25(2), 209-218. •Clarke, H. (2001). Book review: The economics of tourism. Economic Record, 77(239), 407-409. •Clewer, A., Pack, A., & Sinclair, M. T. (1990). Forecasting models for tourism demand in city dominated and coastal areas. Papers of The Regional Science Association, 69, 31-42. •Cline, R. S. (1975). Measuring travel volumes and itineraries and forecasting future travel growth to individual pacific destinations. In S. P. Ladany (Ed.), Management science applications to leisure-time operations. (pp. 134-145). New York, NY: North-Holland Publishing Company. •Coshall, J. (2000). Spectral analysis of international tourism flows. Annals of Tourism Research, 27(3), 577-589. •Crampon, L. J., & Tan, K. T. (1973). A model of tourism flow into the Pacific. Revue de Tourisme (Tourist Review), 28, 98-104. •Crouch, G. I. (1992). Effect of income and price on international tourism. Annals of Tourism Research, 19(4), 643-664. •Crouch, G. I. (1993). Currency exchange rates and the demand for international tourism. Journal of Tourism Studies, 4(2), 45-53. •Crouch, G. I. (1994a). The study of international tourism demand: A review of findings. Journal of Travel Research, 33(1), 12-23. •Crouch, G. I. (1994b). The study of international tourism demand: A survey of practice. Journal of Travel Research, 32(4), 41-57. •Crouch, G. I., Schultz, L., & Valerio, P. (1991). Marketing international tourism to Australia: A regression analysis (Management paper). Clayton, Victoria, Australia: Graduate School of Management, Monash University. •Crouch, G. I., Schultz, L., & Valerio, P. (1992). Marketing international tourism to Australia: A regression analysis. Tourism Management, 13(2), 196-208. •Darnell, A. C., & Johnson, P. S. (2001). Repeat visits to attractions: A preliminary economic analysis. Tourism Management, 22(2), 119-126. •de Carvalho, M. C. M., Dougherty, M. S., Fowkes, A. S., & Wardman, M. R. (1998). Forecasting travel demand: A comparison of logit and artificial neural network methods. Journal of the Operational Research Society, 49(7), 717-722. •Dharmaratne, G. S. (1995). Forecasting tourist arrivals in Barbados. Annals of Tourism Research, 22(4), 804-818. •di Matteo, L. (1999). Using alternative methods to estimate the determinants of cross-border trips. Applied Economics, 31(1), 77-88. •Divisekera, S. (2003). A model of demand for international tourism. Annals of Tourism Research, 30(1), 31-49. •Downward, P., & Lumsdon, L. (2001). The demand for day-visits: An analysis of visitor spending. Tourism Economics, 6(3), 251-261. •DRI•WEFA. (2001). Global tourism navigator: A powerful resource for analyzing global travel & tourism. Retrieved December 16, 2001, from http://www.dri-wefa.com/products_services/content.cfm?ps_id=37&type=sub •Economics Research Associates, Santa Barbara (Calif.), & EIP Associates. (1986). Santa Barbara economic forecast and hotel/tourism study. San Francisco, CA: Economics Research Associates. •Economist Intelligence Unit. (1995). Real exchange rates and international tourism demand. Travel & Tourism Analyst(4), 66-92. •Edgell, D. L., & Seely, R. L. (1980). A multi-stage model for the development of international forecasts for states regions. In D. E. Hawkins, E. L. Shafer & J. M. Rovelstad (Eds.), Tourism planning and development issues (pp. 407-410). Washington, DC: George Washington University. •Edgell, D. L., & Smith, G. (1993). Tourism milestones for the millennium: Projections and implications of international tourism for the United States through the year 2000. Journal of Travel Research, 32(1), 42-47. •Edgell, D. L., & United States Travel and Tourism Administration. (1993). World tourism at the millennium: An agenda for industry, government, and education. Washington, DC: United States Travel and Tourism Administration (USTTA). •Edwards, A. D. (1979). International tourism development forecasts to 1990 (Travel and tourism special report No. No. 62). London, UK: Economist Intelligence Unit. •Edwards, A. D. (1985a). International tourism development forecasts to 1995 (Travel and tourism special report No. No. 188). London, UK: Economist Intelligence Unit. •Edwards, A. D. (1985b). International tourism forecasts to 1995. London, UK: Economist Intelligence Unit. •Edwards, A. D. (1988). International tourism forecasts to 1999. London, U.K.: Economist Intelligence Unit. •Edwards, A. D. (1992). International tourism forecasts to 2005. London, UK: Economist Intelligence Unit. •Edwards, A. D., & Graham, A. (1997a). International tourism forecasts to 2010. London, UK: Lebhar-Friedman, Inc. •Edwards, A. D., & Graham, A. (1997b). International tourism forecasts to 2010. (Research report No. R469). London, UK: Travel & Tourism Intelligence (TTI). •Enders, W., & Sandler, T. (1992). An econometric analysis of the impact of the terrorism on tourism. Kyklos, 45(4), 531-554. •Faulkner, B. (2000). Professorial lecture: "The future ain’t what it used to be" - Coping with change, turbulence and disasters in tourism research and destination management. Gold Coast, Queensland, Australia: Griffith University. •Faulkner, B. (2003). Progressing tourism research. Clevedon, UK: Channel View Publications. •Faulkner, B., & Valerio, P. (1995). An integrative approach to tourism demand forecasting. Tourism Management, 16(1), 29-37. •Faulkner, B., & Valerio, P. (2000). Chapter 3: An integrative approach to tourism demand forecasting. In C. Ryan & S. Page (Eds.), Tourism management: Toward the new millennium. (pp. 45-58). Oxford, UK: Pergamon, Elsevier Science Ltd. •Frechtling, D. C. (1992). The US tourism industry's view Of EC '92. Tourism Management, 13(1), 37-40. •Frechtling, D. C. (1996). Practical tourism forecasting. Boston, MA: Butterworth-Heinemann. •Frechtling, D. C. (2001). Forecasting tourism demand: Methods and strategies. Oxford, UK: Butterworth-Heinemann. •Frechtling, D. C. (2003). Tourism demand modelling and forecasting: Modern econometric approaches. Journal of Travel Research, 41(3), 332-334. •Fritz, R. G., Brandon, C., & Xander, J. A. (1984). Combining time-series and econometric forecasts of tourism activity. Annals of Tourism Research, 11, 219-230. •Fujii, E. T., & Mak, J. (1980). Forecasting travel demand when the explanatory variables are highly correlated. Journal of Travel Research, 18(4), 31-34. •Fujii, E. T., & Mak, J. (1981). Forecasting tourism demand: Some methodological issues. Annals of Regional Science, 15(2), 72-82. •Gallet, C. A., & Braun, B. M. (2001). Gradual switching regression estimates of tourism demand. Annals of Tourism Research, 28(2), 503-508. •García-Ferrer, A., & Queralt, R. A. (1997). A note on forecasting international tourism demand in Spain. International Journal of Forecasting, 13(4), 539-549. •Garin-Munoz, T., & Amaral, T. P. (2000). An econometric model for international tourism flows to Spain. Applied Economics Letters, 7(8), 525-529. •Gee, C. Y., & Fayos-Solá, E. (1997). International tourism: A global perspective. Madrid, Spain: World Tourism Organization. •Gibson, J. G. (1980). Tourism and the business cycle: Econometric models for the purpose of analysis and forecasting of short-term changes in the demand for tourism by Stephen Schulmeister. Journal of the Royal Statistical Society, Series A, 143(1), 85-86. •Goh, C., & Law, R. (2002). Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention. Tourism Management, 23(5), 499-510. •Goh, C., & Law, R. (2003). Incorporating the rough sets theory into travel demand analysis. Tourism Management, 24(5), 511-517. •Gonzalez, P., & Moral, P. (1995). An analysis of the international tourism demand in Spain. International Journal of Forecasting, 11(2), 233-251. •Gonzalez, P., & Moral, P. (1996). Analysis of tourism trends in Spain. Annals of Tourism Research, 23(4), 739-754. •Green, S., & Nichols, J. L. (1979). Forecasting travel and tourism an annotated bibliography: A reference guide to forecasting studies in travel and tourism. Washington: U.S. Travel Data Center (USTDC). •Greenidge, K. (2001). Forecasting tourism demand: An STM approach. Annals of Tourism Research, 28(1), 98-112. •Grubb, H., & Mason, A. (2001). Long lead-time forecasting of UK air passengers by Holt-Winters methods with damped trend. International Journal of Forecasting, 17(1), 71-82. •Gunadhi, H., & Boey, C. K. (1986). Demand elasticities of tourism in Singapore. Tourism Management, 7(4), 239-253. •Gustavsson, P., & Nordström, J. (2001). The impact of seasonal unit roots and vector ARMA modelling on forecasting monthly tourism flows. Tourism Economics, 7(2), 117-133. •Hamal, K. (1996-1997). Modeling domestic holiday tourism demand in Australia: Problems and solutions. Asia Pacific Journal of Tourism Research, 1(2), 35-46. •Harrington, T. C. (2001). Module two notes: "Forecasting". Retrieved December 21, 2001, from http://ruby.fgcu.edu/courses/tharring/10183/m2_notes.htm •Hellström, J. (2002). Count data modelling and tourism demand (Scandinavian working papers in Economics No. 584). Stockholm, Sweden: Stockholm School of Economics. •Hernández-López, M. (2004). Future tourists' characteristics and decisions: The use of genetic algorithms as a forecasting method. Tourism Economics, 10(3), 245-262. •Horsburgh, S. (1998). No money, won't travel. Time South Pacific(27), 49. •Hu, C. (1996, August 7-10). From expert system to artificial neural networks: A new technology for the hospitality industry. Paper presented at the 1996 International CHRIE (Council on Hotel, Restaurant & Institutional Education) Annual Conference, Washington, DC. •Ismail, J. A., Iverson, T. J., & Cai, L. A. (2000). Forecasting Japanese arrivals to Guam: An empirical model. Journal of Hospitality & Leisure Marketing, 7(2), 51-63. •Jang, S. S., Bai, B., Hong, G.-S., & O'Leary, J. T. (2004). Understanding travel expenditure patterns: A study of Japanese pleasure travelers to the United States by income level. Tourism Management, 25(3), 331-341. •Janke, J. (1996). How Australia is adapting to changing markets. Insight, 5(2), 3. •Johnson, P., & Thomas, R. B. (1992). Choice and demand in tourism. New York, NY: Mansell. •Kandampully, J. (2000). The impact of demand fluctuation on the quality of service: A tourism industry example. Managing Service Quality, 10(1), 10. •Kaynak, E., Bloom, J., & Leibold, M. (1994). Using the Delphi technique to predict future tourism potential. Marketing Intelligence & Planning, 12(7), 18-29. •Kim, J. H. (1999). Forecasting monthly tourist departures from Australia. Tourism Economics, 5(3), 277-291. •Kim, J. H., & Moosa, I. A. (2001). Seasonal behaviour of monthly international tourist flows: Specification and implications for forecasting models. Tourism Economics, 7(4), 381-396. •Kim, J. H., & Ngo, M. T. (2001). Modelling and forecasting monthly airline passenger flows among three major Australian cities. Tourism Economics, 7(4), 397-412. •Kim, J. M. (2000). Report - A study of tourist demand and accommodation in the Mt. Paekdusan/Changbaishan area. Tourism Economics, 6(1), 73-83. •Kulendran, N. (1996). Modeling quarterly tourist flows to Australia using cointegration analysis. Tourism Economics, 2(3), 203-222. •Kulendran, N., & King, M. L. (1997). Forecasting international quarterly tourist flows using error-correction and time series models. International Journal of Forecasting, 13(3), 319-327. •Kulendran, N., & Witt, S. F. (2001). Cointegration versus least squares regression. Annals of Tourism Research, 28(2), 291-311. •Kulendran, N., & Witt, S. F. (2003a). Forecasting the demand for international business tourism. Journal of Travel Research, 41(3), 265-271. •Kulendran, N., & Witt, S. F. (2003b). Leading indicator tourism forecasts. Tourism Management, 24(5), 503-510. •Lagos, D. G. (1999). Exploratory forecasting methodologies for tourism demand. Ekistics, 66(394-396), 143154. •Latham, J. (1993). Modeling and forecasting demand in tourism. Service Industries Journal, 13(3), 150-151. •Lathiras, P., & Siriopoulos, C. (1998). The demand for tourism to Greece: A cointegration approach. Tourism Economics, 4(2), 171-185. •Law, R. (1998). Room occupancy rate forecasting: A neural network approach. International Journal of Contemporary Hospitality Management, 10(6), 234-239. •Law, R. (2000). Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting. Tourism Management, 21(4), 331-340. •Law, R., & Au, N. (1999). A neural network model to forecast Japanese demand for travel to Hong Kong. Tourism Management, 20(1), 89-97. •Law, R., & Cheung, C. (1998). Prospects of the Hong Kong tourism industry. FIU Hospitality Review, 16(2), 39-51. •Lego, R. (1989). A demand forecasting model for regional tourism in Victoria. Unpublished MBA Thesis, Monash University, Clayton, Victoria, Australia. •Leslie, D. (1999). Terrorism and tourism: The Northern Ireland situation - a look behind the veil of certainty. Journal of Travel Research, 38(1), 37-40. •Lim, C. (1997). An econometric classification and review of international tourism demand models. Tourism Economics, 3(1), 69-81. •Lim, C., & McAleer, M. (2000). A seasonal analysis of Asian tourist arrivals to Australia. Applied Economics, 32(4), 499-509. •Lim, C., & McAleer, M. (2001a). Forecasting tourist arrivals. Annals of Tourism Research, 28(4), 965-977. •Lim, C., & McAleer, M. (2001b). Monthly seasonal variations: Asian tourism to Australia. Annals of Tourism Research, 28(1), 68-82. •Lim, C., & McAleer, M. (2001c). Time series forecasting of international tourism demand for Australia (Discussion paper No. 533). Osaka, Japan: Institute of Social and Economic Research, Osaka University. •Lim, C., & McAleer, M. (2002). Time series forecasts of international travel demand for Australia. Tourism Management, 23(4), 389-396. •Lim, C., & McAleer, M. (2005). Analyzing the behavioral trends in tourist arrivals from Japan to Australia. Journal of Travel Research, 43(4), 414-421. •Liu, J. C. (1988). Hawaii tourism to the year 2000: A Delphi forecast. Tourism Management, 9(4), 279-290. •Lorde, C. E. (1995). International and Caribbean tourism management through forecasting techniques. Unpublished Ph.D. dissertation, Walden University, Minneapolis, MN. •Lundberg, D. E., Krishnamoorthy, M., & Stavenga, M. H. (1995). Tourism economics. New York, NY: John Wiley & Sons, Inc. •Martin, C. A. (1987). International tourism demand forecasting a comparison of the accuracy of various quantitative forecasting techniques as applied to the main outward tourism flows from the German Federal Republic, France, the UK and the USA. Unpublished Ph.D. dissertation, University Of Bradford, UK. •Martin, C. A., & Witt, S. F. (1987). Tourism demand forecasting models: Choice of appropriate variables to represent tourists' cost of living. Tourism Management, 8(3), 233-246. •Martin, C. A., & Witt, S. F. (1988). Substitute prices in models of tourism demand. Annals of Tourism Research, 15(2), 255-268. •Martin, C. A., & Witt, S. F. (1989a). Accuracy of econometric forecasts of tourism. Annals of Tourism Research, 16(3), 407-428. •Martin, C. A., & Witt, S. F. (1989b). Forecasting tourism demand: A comparison of the accuracy of several quantitative methods. International Journal of Forecasting, 5(1), 7-19. •Moeller, G. H., & Shafer, E. L., Jr. (1994). Chapter 39 - The Delphi technique: A tool for long-range travel and tourism planning. In J. R. B. Ritchie & C. R. Goeldner (Eds.), Travel, tourism, and hospitality research: A handbook for managers and researchers (2nd ed., pp. 473-480). New York, NY: John Wiley & Sons, Inc. •Morley, C. L. (1993). Forecasting tourism demand using extrapolative time series methods. Journal of Tourism Studies, 4(1), 19-25. •Morley, C. L. (1994). Discrete choice analysis of the impact of tourism prices. Journal of Travel Research, 33(2), 8-14. •Morley, C. L. (1997). An evaluation of the use of ordinary least squares for estimating tourism demand model. Journal of Travel Research, 35(4), 69-73. •Morley, C. L. (1999). Estimating integrated time series and other problems in modeling tourism demand. (Working paper No. 99/3). Melbourne, Victoria, Australia: Research Development Unit, RMIT (Royal Melbourne Institute of Technology) Business. •Morley, C. L. (2000). Demand modeling methodologies: Integration and other issues. Tourism Economics, 6(1), 5-19. •Morris, A., Wilson, K., & Bakalis, S. (1995). Modelling tourism flows from Europe to Australia. Tourism Economics, 1(2), 147-167. •Moutinho, L., & Witt, S. F. (1995). Forecasting the tourism environment using a consensus approach. Journal of Travel Research, 33(4), 46-50. •Ngai, E. W. T., & Wat, F. K. T. (2003). Design and development of a fuzzy expert system for hotel selection. Omega: The International Journal of Management Science, 31(4), 275-286. •Noval, S. (1975). The demand for international tourism and travel theory and measurement. Unpublished Ph.D. Thesis, Princeton University, Princeton, NJ. •Oh, C.-O., & Morzuch, B. J. (2005). Evaluating time-series models to forecast the demand for tourism in Singapore. Journal of Travel Research, 43(4), 404-413. •Okere, V. O. (1987). A preliminary economic impact forecasting model for short-term tourism events: A preliminary framework (Rhode Island). Unpublished Ph.D. dissertation, University of Rhode Island, Providence, RI. •Paci, E. (1993, December 10-11). Global tourism forecasts to the year 2000 and beyond. Paper presented at the Forecasting toursim demand: Theory and the case of Italy, Venice, Italy. •Paci, E. (1994). Global tourism forecasts to the year 2000 and beyond. Quaderni CISET - Venezia: Centro Internazionale di Studi sull'Economia Turistica, 8.1, 71-99. •Page, S. (1999). Chapter 4 - Analysing the demand for tourist travel. In Transport and tourism. (pp. 109-150). Essex, UK: Addison Wesley Longman Limited. •Pan, S. Q., Vega, M., Vella, A. J., Archer, B. H., & Parlett, G. R. (1996). Mini-Delphi approach: An improvement on single round techniques. Progress in Tourism and Hospitality Research, 2(1), 27-39. •Papatheodorou, A. (1999). The demand for international tourism in the Mediterranean region. Applied Economics, 31(5), 619-630. •Pattie, D. C., & Snyder, J. (1996). Using a neural network to forecast visitor behavior. Annals of Tourism Research, 23(1), 151-164. •Peters, M. (1969). Chapter 3 - Indications for the future. In International tourism: The economics and development of the international tourist trade. (pp. 114-146). London, UK: Hutchinson & Co. (Publishers), Ltd. •Pizam, A. (1999). Life and tourism in the year 2050. International Journal of Hospitality Management, 18, 331-343. •Poole, M. (1988). Forecasting methodology (BTR Occasional paper No. 3). Canberra City, Australia: Bureau of Tourism Research. •Poukliakova, S. I. (2001). Book review - Tourism demand modelling and forecasting: Modern econometric approaches. Journal of Retailing and Consumer Services, 9(1), 54-55. •Pyo, S. S. (1989). U.S. tourism demand: Seemingly unrelated regression equation models. Unpublished Ph.D. dissertation, Clemson University, NC. •Qiu, H., & Zhang, J. (1995). Determinants of tourist arrivals and expenditures in Canada. Journal of Travel Research, 34(2), 43-49. •Qu, H., & Lam, S. (1997). A travel demand model for Mainland Chinese tourists to Hong Kong. Tourism Management, 18(8), 593-597. •Qu, H., & Zhang, H. Q. (1996). Projecting international tourist arrivals in East Asia and the Pacific to the year 2005. Journal of Travel Research, 35(1), 27-34. •Quandt, R. E. (Ed.). (1970). The demand for travel: Theory and measurement. Lexington, MA: Heath Lexington Books. •Raminhosa, M. M. C. (1997). Models of receipts from tourism in Portugal: Cointegration, dynamic specification and forecast. Retrieved June 8, 2002, from http://www2.dst.dk/internet/4thforum/docs/c1-8.pdf •Rao, C. P., & Ali, J. (2002). Neural network model for database marketing in the new global economy. Marketing Intelligence & Planning, 20(1), 35-43. •Ritchie, J. R. B., & Goeldner, C. R. (1994). Travel, tourism, and hospitality research: A handbook for managers and researchers (2nd ed.). New York, NY: John Wiley & Sons, Inc. •Rodrigues, P. M. M., & Gouveia, P. M. D. C. B. (2004). An application of PAR models for tourism forecasting. Tourism Economics, 10(3), 281-303. •Rossello-Nadal, J. (2001). Forecasting turning points in international visitor arrivals in the Balearic Islands. Tourism Economics, 7(4), 365-380. •Ryan, C. (2000). Part II - Introduction: Economic forecasting in tourism. In C. Ryan & S. Page (Eds.), Tourism management: Toward the new millennium. (pp. 37-44). Oxford, UK: Pergamon, Elsevier Science Ltd. •Ryan, C., & Page, S. J. (Eds.). (2000). Tourism management: Towards the new Millennium (Vol. 1). Amsterdam, Netherlands: Elsevier Science Ltd. •Ryu, K., & Sánchez, A. (2002). The evaluation of the forecasting methods in the institutional foodservice facilities. In A. DeFranco & J. A. Abbott (Eds.), Proceedings of the Seventh Annual Graduate Education and Graduate Students Research Conference in Hospitality and Tourism: Advances in hospitality and tourism research, January 3-5, Houston, TX (Vol. 7, pp. 491-493). Houston, TX: University of Houston. •Sánchez, A., & Miller, J. L. (1997). Foodservice forecasting using an artificial neural network. In K. Chon (Ed.), Proceedings of the Second Annual Graduate Education and Graduate Students Research Conference in Hospitality and Tourism: Advances in hospitality and tourism research, Houston, TX (Vol. 2, pp. 69-78). Houston, TX: University of Houston. •Saunders, P. R., Senter, H. F., & Jarvis, J. P. (1981). Forecasting recreation demand in the Upper Savannah River Basin. Annals of Tourism Research, 8, 236-259. •Schulmeister, S. (1979). Tourism and the business cycle: Econometric models for the purpose of analysis and forecasting of short-term changes in the demand for tourism. (K. Bayer, Trans.). Vienna, Austria: Austrian Institute for Economic Research. •Schwartz, Z. (1999). Monitoring the accuracy of multiple occupancy forecasts. FIU Hospitality Review, 17(1-2), 29-42. •Schwartz, Z., & Hiemstra, S. J. (1997). Improving the accuracy of hotel reservations forecasting: Curves similarity approach. Journal of Travel Research, 36(1), 3-14. •Scott, J. (Ed.). (1984). Travel industry world yearbook - The big picture 1983 (Vol. 27). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1985). Travel industry world yearbook - The big picture 1984 (Vol. 28). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1986). Travel industry world yearbook - The big picture 1985 (Vol. 29). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1987). Travel industry world yearbook - The big picture 1986 (Vol. 30). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1988). Travel industry world yearbook - The big picture 1987 (Vol. 31). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1989). Travel industry world yearbook - The big picture 1988 (Vol. 32). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1990). Travel industry world yearbook - The big picture 1989 (Vol. 33). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1991). Travel industry world yearbook - The big picture 1990 (Vol. 34). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1992). Travel industry world yearbook - The big picture 1991 (Vol. 35). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1993). Travel industry world yearbook - The big picture 1992 (Vol. 36). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1994). Travel industry world yearbook - The big picture 1993-1994 (Vol. 37). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1995). Travel industry world yearbook - The big picture 1994-1995 (Vol. 38). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1996). Travel industry world yearbook - The big picture 1995-1996 (Vol. 39). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1997). Travel industry world yearbook - The big picture 1996-1997 (Vol. 40). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1998). Travel industry world yearbook - The big picture 1997-1998 (Vol. 41). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (1999). Travel industry world yearbook - The big picture 1998-1999 (Vol. 42). Spencertown, NY: Travel Industry Publishing Company, Inc. •Scott, J. (Ed.). (2000). Travel industry world yearbook - The big picture 2000 (Vol. 43). Spencertown, NY: Travel Industry Publishing Company, Inc. •Seddighi, H. R., & Shearing, D. F. (1997). The demand for tourism in North East England with special reference to Northumbria: An empirical analysis. Tourism Management, 18(8), 499-511. •Seely, R. L., Iglarsh, H. J., & Edgell, D. L. (1980). Utilizing the Delphi technique at international conferences: A method for forecasting international tourism conditions. Travel Research Journal, 1(1), 30-36. •Seely, R. L., Iglarsh, H. J., & Edgell, D. L. (1994). Delphi forecasting of international tourism conditions. Paper presented at the Proceedings of the American Institute for Decision Sciences Ninth Annual Meeting Western Regional Conference., Atlanta, GA, USA. •Shan, J., & Wilson, K. (2001). Causality between trade and tourism: Empirical evidence from China. Applied Economics Letters, 8(4), 279-283. •Sheehan, D. (1999). Australia finds that the Olympics already is luring foreign tourists. Asian Wall Street Journal, 21(5), 12. •Sheldon, P. J. (1982). Tourism forecasting the state-of-the-art. (Working paper No. 82-03-04). Burnaby, British Columbia, Canada: Faculty of Business Administration, Simon Fraser University. •Sheldon, P. J. (1993). Forecasting tourism: Expenditure versus arrivals. Journal of Travel Research, 32(1), 13-20. •Sheldon, P. J., & Var, T. (1985). Tourism forecasting: A review of empirical research. Journal of Forecasting, 4(2), 183-195. •Shimizu, J. K. (1988). Tourism forecasting and the Delphi technique a case study. Unpublished M.A. Thesis, University of Waterloo, Waterloo, ON, Canada. •Sinclair, M. T., & Stabler, M. (1997). Chapter 3: Empirical studies of tourism demand. In The economics of tourism (Vol. 3, pp. 35-57). London, UK: Routledge. •Smeral, E. (1992). Long-term forecasts for tourism industries: The case of Austria and Switzerland. Service Industries Journal, 12(1), 60. •Smeral, E. (1993, December 10-11). A general model approach for forecasting demand flows in world tourism. Paper presented at the Forecasting toursim demand: Theory and the case of Italy, Venice, Italy. •Smeral, E. (1994a). Economic models. In S. F. Witt & L. Moutinho (Eds.), Tourism marketing and management handbook. (2nd ed., pp. 497-502). New York, NY: Prentice Hall. •Smeral, E. (1994b). A general model approach for forecasting demand flows in world tourism. Quaderni CISET - Venezia: Centro Internazionale di Studi sull'Economia Turistica, 8.1, 11-31. •Smeral, E. (1995, 23-24 November). Forecast of tourism demand and perspectives for employment until the year 2005: A cross country scenario. Paper presented at the OECD seminar on perspectives and challenges of employment in the tourism industry., Vienna, Austria. •Smeral, E. (1999). Euro – Implications for tourism. Retrieved June 5, 2002, from http://www.wifo.ac.at/Egon.Smeral/TRC_Vienna_03_1999.htm •Smeral, E., & Weber, A. (2000). Forecasting international tourism trends to 2010. Annals of Tourism Research, 27(4), 982-1006. •Smeral, E., & Witt, S. F. (1992). The impacts of Eastern Europe and 1992 on international tourism demand. Tourism Management, 13(4), 368-376. •Smeral, E., & Witt, S. F. (1996). Econometric forecasts of tourism demand to 2005. Annals of Tourism Research, 23(4), 891-907. •Smeral, E., Witt, S. F., & Witt, C. A. (1992). Econometric forecasts: Tourism trends to 2000. Annals of Tourism Research, 19(3), 450-466. •Smith, S. L. J. (1995). Tourism analysis: A handbook. (2nd ed.). Harlow, Essex, UK: Longman Group Limited. •Song, H., Romilly, P., & Liu, X. (2000). An empirical study of outbound tourism demand in the UK. Applied Economics, 32(5), 611-624. •Song, H., & Witt, S. F. (2000). Tourism demand modelling and forecasting: Modern econometric approaches. New York, NY: Pergamon. •Song, H., & Witt, S. F. (2003). Tourism forecasting: The general-to-specific approach. Journal of Travel Research, 42(1), 65-74. •Song, H., Witt, S. F., & Jensen, T. C. (2003). Tourism forecasting: Accuracy of alternative econometric models. International Journal of Forecasting, 19(1), 123-141. •Song, H., Witt, S. F., & Li, G. (2003). Modelling and forecasting the demand for Thai tourism. Tourism Economics, 9(4), 363-387. •Song, H., & Wong, K. K. F. (2003). Tourism demand modeling: A time-varying parameter approach. Journal of Travel Research, 42(1), 57-64. •Stoddard, J. E., Dave, D. S., & Evans, M. R. (2001). Estimating demand for services in the nonprofit tourism industry. Services Marketing Quarterly, 22(1), 71-82. •Stopher, P., & Lee-Gosselin, M. (Eds.). (1997). Understanding travel behaviour in an era of change. Oxford, UK: Elsevier Science Ltd. •Summary, R. (1987). Estimation of tourism demand by multivariable regression analysis: Evidence from Kenya. Tourism Management, 8(4), 317-322. •Sunday, A. A. (1978). Foreign travel and tourism prices and demand. Annals of Tourism Research, 5(2), 268-273. •Swart, W. W., Gearing, C., & Var, T. (1978). Operations research applications to tourism. Annals of Tourism Research, 5, 414-428. •Taplin, J. H. E., & Min, Q. (1997). Car trip attraction and route choice in Australia. Annals of Tourism Research, 24(3), 624-637. •Taylor, R. E., & Judd, L. L. (1994). Delphi forecasting. In S. F. Witt & L. Moutinho (Eds.), Tourism marketing and management handbook. (2nd ed., pp. 535-539). Hertfordshire, UK: Prentice Hall International (UK) Ltd. •Teigland, J. (1999). Mega-events and impacts on tourism: The predictions and realities of the Lillehammer Olympics. Impact Assessment and Project Appraisal, 17(4), 305-317. •Tideswell, C., Mules, T., & Faulkner, B. (2001). An integrative approach to tourism forecasting: A glance in the rearview mirror. Journal of Travel Research, 40(2), 162-171. •Tisdell, C. A. (Ed.). (2000). The economics of tourism. Cheltenham, UK: Edward Elgar Publishing, Ltd. •Tonini, G. (1994). Modelli stocastici e previsioni a breve termine della domanda turistica. Il caso italiano dagli anni Ottanta in poi. (Modeling and short-term forecasting of tourism demand. A case study: Italy from 1980 forward.). Giornale degli Economisti e Annali di Economia, 53(10-12), 525-546. •Tourism Forecasting Council. (1997). Short, sharp shock or lower growth outlook? the potential impact of emerging economic difficulties in Asia on inbound tourism to Australia (Research report No. 1). Canberra, Australia: Tourism Forecasting Council. •Tourism Forecasting Council. (1998). Inbound tourism short-term scenarios. (Research report No. 2). Canberra, Australia: Tourism Forecasting Council. •Tourism Forecasting Council, KPMG Management Consulting, Griffith University, Tourism Task Force (Australia), & Tourism New South Wales. (1998). The Olympic effect a report on the potential tourism impacts of the Sydney 2000 Games. (Consulting report). Canberra, Australia: Tourism Forecasting Council. •Tribe, J. (1999). The economics of leisure and tourism. (2nd ed.). Oxford, UK: Butterworth-Heinemann. •Tsaur, S.-H., Chiu, Y.-C., & Huang, C.-H. (2002). Determinants of guest loyalty to international tourist hotels - A neural network approach. Tourism Management, 23(4), 397-405. •Turner, L. (2001). Book review: Tourism demand modeling and forecasting by H. Song and S. F. Witt; Pergamon, Oxford, 2000, 178 pages, US$75 hard cover, ISBN 0-08-043673-0. Tourism Management, 22(5), 578-579. •Turner, L. W., & Kulendran, N. (1993). International tourism arrivals to Australia and the use of modern forecasting methodology. Regional Journal of Social Issues, 24, 33-63. •Turner, L. W., Kulendran, N., & Fernando, H. (1997). The use of composite national indicators for tourism forecasting. Tourism Economics, 3(4), 309-317. •Turner, L. W., Kulendran, N., & Pergat, V. (1995). Forecasting New Zealand tourism demand with disaggregated data. Tourism Economics, 1(1), 51-69. •Turner, L. W., Reisinger, Y., & Witt, S. F. (1998). Tourism demand analysis using structural equation modeling. Tourism Economics, 4(4), 301-323. •Turner, L. W., & Witt, S. F. (2000). Asia Pacific tourism forecasts. London, UK: Lebhar-Friedman, Inc. •Turner, L. W., & Witt, S. F. (2001a). Factors influencing demand for international tourism: Tourism demand analysis using structural equation modeling, revisited. Tourism Economics, 7(1), 21-38. •Turner, L. W., & Witt, S. F. (2001b). Forecasting tourism using univariate and multivariate structural time series models. Tourism Economics, 7(2), 135-147. •Turner, L. W., & Witt, S. F. (2001c, April 23-25). Travel & tourism outlook: Forecasting of travel to Europe for 2001, 2002 and 2005. Paper presented at the 2001 European Conference of the Travel and Tourism Research Association - Creating and managing growth in travel and tourism., Stockholm, Sweden. •Turner, L. W., & Witt, S. F. (2002). Pacific Asia tourism forecasts 2002-2004. Bangkok, Thailand: Pacific Asia Travel Association. •United Nations Office For the Coordination of Humanitarian Affairs. (n.d.). Tourism, natural disasters and safe destinations. Retrieved December 14, 2001, from http://www.reliefweb.int/ocha_ol/programs/idndr/presskit/tourism.html •Uysal, M. S., & Crompton, J. L. (1984). Identification of key variables explaining international tourist flows to Turkey and suggested policy implications. Journal of Turkish Economy and Tourism, 2(4), 7-15. •Uysal, M. S., & Crompton, J. L. (1985a). Deriving a relative price index for inclusion in international tourism demand. Journal of Travel Research, 24(1), 32-34. •Uysal, M. S., & Crompton, J. L. (1985b). An overview of approaches used to forecast tourism demand. Journal of Travel Research, 23(4), 7-15. •Uysal, M. S., & Crompton, J. L. (1987). Deriving a relative price index for inclusion in international tourism demand. [Reaction to the reaction of Witt and Martin]. Journal of Travel Research, 25(3), 40. •Uysal, M. S., & El Roubi, M. S. (1999). Artificial neural networks versus multiple regression in tourism demand analysis. Journal of Travel Research, 38(2), 111-118. •van Dijk, H. (1993, December 10-11). A jigsaw of tourism: Integration of methods and data. Paper presented at the Forecasting toursim demand: Theory and the case of Italy, Venice, Italy. •van Doorn, J. W. M. (1984a). Tourism forecasting and the policy-maker: Criteria and usefulness. Tourism Management, 5(1), 24-39. •van Doorn, J. W. M. (1984b). Tourism forecasting techniques: A brief overview. In J. W. M. van Doorn (Ed.), Problems of tourism (Vol. 3, pp. 7-15). •van Limburg, B. (1997). Overnight tourism in Amsterdam 1982-1993 - A forecasting approach. Tourism Management, 18(7), 465-468. •Vanegas, M., Sr., & Croes, R. R. (2000). Evaluation of demand: US tourists to Aruba. Annals of Tourism Research, 27(4), 946-963. •Vanhove, N. (1980). Forecasting in tourism. Revue de Tourisme (Tourist Review), 3, 2-7. •Var, T., & Lee, C. K. (1993). Part 3 - Chapter 12: Tourism forecasting: State-of-the-art techniques. In M. Khan, M. Olsen & T. Var (Eds.), VNR's encyclopedia of hospitality and tourism (pp. 679-696). New York, NY: Van Nostrand Reinhold. •Veloce, W. (2004). Forecasting inbound Canadian tourism: An evaluation of Error Corrections Model forecasts. Tourism Economics, 10(3), 263-280. •Velthuijsen, J. W., & Verhagen, M. (1994). A simulation model of the Dutch tourism market. Annals of Tourism Research, 21(4), 812-827. •Vermeiren, J. C. (1989, November 6-8). Natural disasters: Linking economics and the environment with a vengeance. Paper presented at the Conference on Economics and the Environment, Barbados. •Wandner, S. A., & van Erden, J. D. (1980). Estimating the demand for international tourism using time series analysis. In D. E. Hawkins, E. L. Shafer & J. M. Rovelstad (Eds.), Tourism planning and development issues (pp. 381-392). Washington, DC: George Washington University. •Wang, C.-H. (2004). Predicting tourism demand using fuzzy time series and hybrid grey theory. Tourism Management, 25(3), 367-374. •Wang, P., & Godbey, G. (1994). A normative approach to tourism growth to the year 2000. Journal of Travel Research, 33(1), 32-37. •Webber, A. G. (2001). Exchange rate volatility and cointegration in tourism demand. Journal of Travel Research, 39(4), 398-405. •Winklhofer, H. M., & Diamantopoulos, A. (2002). Managerial evaluation of sales forecasting effectiveness: A MIMIC modeling approach. International Journal of Research in Marketing, 19(2), 151-166. •Witt, C. A., & Witt, S. F. (1989). Measures of forecasting accuracy - Turning point error vs. size of error. Tourism Management, 10(3), 255-260. •Witt, C. A., & Witt, S. F. (1990). Appraising an econometric forecasting model. Journal of Travel Research, 28(3), 30-34. •Witt, C. A., & Witt, S. F. (1994). Demand elasticities. In S. F. Witt & L. Moutinho (Eds.), Tourism marketing and management handbook. (2nd ed., pp. 521-529). Hertfordshire, UK: Prentice Hall International (UK) Ltd. •Witt, C. A., & Witt, S. F. (2000). Chapter 4: Measures of forecasting accuracy - turning point error vs. size of error. In C. Ryan & S. Page (Eds.), Tourism management: Toward the new millennium. (pp. 59-69). Oxford, UK: Pergamon, Elsevier Science Ltd. •Witt, C. A., Witt, S. F., & Wilson, N. (1994). Forecasting international tourist flows. Annals of Tourism Research, 21(3), 596-611. •Witt, S. F. (1991, Jane 9-13). Assessing the accuracy of published econometric forecasts of international tourism demand. Paper presented at the Travel and Tourism Research Association Twenty-Second Annual Conference - Tourism: Building credibility for a credible industry, Long Beach, CA. •Witt, S. F. (1992a). Tourism forecasting: How well do private and public sector organizations perform? Tourism Management, 13(1), 79-84. •Witt, S. F. (1992b). The track records of tourism forecasting services. In P. Johnson & R. B. Thomas (Eds.), Choice and demand in tourism. (pp. 209-220). London, U.K.: Mansell Publishing Limited. •Witt, S. F. (1993, December 10-11). Determinants of international tourism demand. Paper presented at the Forecasting toursim demand: Theory and the case of Italy, Venice, Italy. •Witt, S. F. (1994a). Econometric demand forecasting. In S. F. Witt & L. Moutinho (Eds.), Tourism marketing and management handbook. (2nd ed., pp. 516-520). Hertfordshire, UK: Prentice Hall International (UK) Ltd. •Witt, S. F. (1994b). Univariate time series demand forecasting. In S. F. Witt & L. Moutinho (Eds.), Tourism marketing and management handbook. (2nd ed., pp. 530-534). Hertfordshire, UK: Prentice Hall International (UK) Ltd. •Witt, S. F. (1998, June 17-19). Tourism forecasting: What do we know? Paper presented at the Fourth International Forum on Tourism Statistics, Copenhagen, Denmark. •Witt, S. F. (2000). Chapter 5: Tourism forecasting: How well do private and public sector organizations perform? In C. Ryan & S. Page (Eds.), Tourism management: Toward the new millennium. (pp. 70-79). Oxford, UK: Pergamon, Elsevier Science Ltd. •Witt, S. F., Brooke, M. Z., & Buckley, P. J. (1995). The management of international tourism (2nd ed.). London, UK: Routledge. •Witt, S. F., & Martin, C. A. (1985). Forecasting future trends in European tourist demand. Tourist Review, 40(4), 12-20. •Witt, S. F., & Martin, C. A. (1987a). Econometric models for forecasting international tourism demand. Journal of Travel Research, 25(3), 23-30. •Witt, S. F., & Martin, C. A. (1987b). International tourism-demand models - inclusion of marketing variables. Tourism Management, 8(1), 33-40. •Witt, S. F., & Moutinho, L. (Eds.). (1989). Tourism marketing and management handbook. Upper Saddle River, NJ: Prentice Hall, Inc. •Witt, S. F., & Moutinho, L. (Eds.). (1994). Tourism marketing and management handbook (2nd ed.). Upper Saddle River, NJ: Prentice Hall, Inc. •Witt, S. F., & Moutinho, L. A. (2000). Chapter 12 - Demand modelling and forecasting. In L. A. Moutinho (Ed.), Strategic management in tourism (pp. 293-314). Oxon, UK: CABI Publishing. •Witt, S. F., Newbould, G. D., & Watkins, A. J. (1992). Forecasting domestic tourism demand: Application to Las Vegas arrivals data. Journal of Travel Research, 31(1), 36-41. •Witt, S. F., & Song, H. (2001). Chapter 9: Forecasting future tourism flows. In A. Lockwood & S. Medlik (Eds.), Tourism and hospitality in the 21st century (pp. 106-118). Oxford, UK: Butterworth-Heinemann. •Witt, S. F., Song, H., & Louvieris, P. (2003). Statistical testing in forecasting model selection. Journal of Travel Research, 42(2), 151-158. •Witt, S. F., Song, H., & Wanhill, S. (2004). Forecasting tourism-generated employment: The case of Denmark. Tourism Economics, 10(2), 167-176. •Witt, S. F., Sykes, A. M., & Dartus, M. (1995). Forecasting international conference attendance. Tourism Management, 16(8), 559-570. •Witt, S. F., & Witt, C. A. (1989, June 11-15). An empirical assessment of relative forecasting performance based on directional accuracy. Paper presented at the Travel and Tourism Research Association Twentieth Annual Conference - Globalization, the Pacific Rim and beyond: 20 years of travel and marketing research revisited, Honolulu, HI. •Witt, S. F., & Witt, C. A. (1991a). Modelling and forecasting demand in tourism. London, UK: Academic Press. •Witt, S. F., & Witt, C. A. (1991b). Tourism forecasting: Error magnitude, direction of change error, and trend change error. Journal of Travel Research, 30(2), 26-33. •Witt, S. F., & Witt, C. A. (1992). Modeling and forecasting demand in tourism. London: Academic Press. •Witt, S. F., & Witt, C. A. (1994). Assessing forecasting performance. In S. F. Witt & L. A. Moutinho (Eds.), Tourism marketing and management handbook (2nd ed., pp. 540-543). Hertfordshire, UK: Prentice Hall International (UK) Ltd. •Witt, S. F., & Witt, C. A. (1995). Forecasting tourism demand: A review of empirical research. International Journal of Forecasting, 11(3), 447-475. •Witt, S. F., & Witt, C. A. (2000). Forecasting tourism demand: A review of empirical research. In C. A. Tisdell (Ed.), The economics of tourism (Vol. 1, pp. 141-169). Cheltenham, UK: Edward Elgar Publishing, Ltd. •Wong, K. K. F. (1997). The relevance of business cycles in forecasting international tourist arrivals. Tourism Management, 18(8), 581-586. •Wong, K. K. F. (2000). Tourism demand modelling and forecasting: Modern econometric approaches. Asia Pacific Journal of Tourism Research, 5(2), 85-87. •World Tourism Organization. (1982). Tourism forecasting. Madrid, Spain: World Tourism Organization. •World Tourism Organization. (1994). Global tourism forecasts to the year 2000 and beyond. Madrid, Spain: World Tourism Organization. •World Tourism Organization. (2000). Data collection & analysis for tourism management, marketing & planning: A manual for managers & anaysts. Madrid, Spain: World Tourism Organization (WTO). •World Tourism Organization. (2001). Long term forecast Tourism 2020 Vision. Retrieved September 29, 2001, from http://www.world-tourism.org/market_research/data/forecast.html •World Tourism Organization. (1994). Global tourism forecasts to the year 2000 and beyond. Madrid, Spain: World Tourism Organization. •Yee, J. G. (1991). Travel & tourism forecasting models bibliography. San Francisco, CA: Intelligence Center, Pacific Asia Travel Association. •Yong, Y. W., Keng, K. A., & Leng, T. L. (1989). A Delphi forecast for the Singapore tourism industry: Future scenario and marketing implications. International Marketing Review, 6(3), 35-46. •Young, P., & Pedregal, D. (1997). Comments on "An analysis of the international tourism demand in Spain." International Journal of Forecasting, 13(4), 551-556. •Zhang, H. Q. (1998). The importance of income, the exchange rate, and the crime rate in influencing demand for Hong Kong as an international tourist destination. Australian Journal of Hospitality Management, 5(1), 1-8.
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