Forecasting Tourism Demand

Douglas Frechtling

• Publisher: Routledge
• Year: 2012
• eBook ISBN: 9781136402418
• Edition: 1
• Topic: Business
• Subtopic: Hospitality, Travel & Tourism Industry
• Index: Business

'Forecasting tourism demand' is a text that no tourism professional can afford to be without. The tourism industry has experienced an overwhelming boom over recent years, and being able to predict future trends as accurately as possible is vital in the struggle to stay one step ahead of the competition.Building on the success of 'Practical Tourism Forecasting' this text looks at 13 methods of forecasting and with a user friendly style, 'Forecasting Tourism Demand' guides the reader through each method, highlighting its strengths and weaknesses and explaining how it can be applied to the tourism industry.'Forecasting Tourism Demand' employs charts and tables to explain how to: * plan a forecasting project* analyse time series and other information* select the appropriate forecasting model* use the model for forecasting and evaluate its resultsIdeal for marketing managers and strategic planners in business, transportation planners and economic policy makers in government who must project demand for their products among tourists. Executives who rely on forecasts prepared by others will find it invaluable in assisting them to evaluate the validity and reliability of predictions and forecasts. Those engaged in analysing business trends will find it useful in surveying the future of what has been called the largest industry in the world.

Table of contents

• Front Cover
• Half Title
• Title Page
• Copyright
• Contents
• List of Figures
• List of Tables
• Foreword
• Preface
• Acknowledgements
• 1 Introduction
• 2 Alternative forecasting methods and evaluation
• 3 The tourism forecasting process
• 4 Basic extrapolative models and decomposition
• 5 Intermediate extrapolative methods
• 6 An advanced extrapolative method
• 7 Causal methods: regression analysis
• 8 Causal methods: structural econometric models
• 9 Qualitative forecasting methods
• 10 Conclusion
• Appendix 1 Hotel/motel room demand in the Washington, D.C., metropolitan area, 1987–99
• Appendix 2 Dealing with super-annual events
• Appendix 3 Splicing a forecast to a time series
• Glossary and abbreviations
• Select bibliography
• Index