A textbook for a graduate or final-year undergraduate course in tourism studies that might also find interest among researchers and practitioners who want to apply recent developments in econometric modeling and forecasting to tourism demand analysis. Song and Witt (both management in the service sector, U. of Surrey, Britain) begin with the fundamentals of tourism demand analysis, and the problems of traditional modeling and forecasting. Then they explore the general- to-specific approach, the time-varying parameter model, and the panel- data approach. Annotation copyrighted by Book News, Inc., Portland, OR

'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 results Ideal 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.

This comprehensive textbook has, at its core, the importance of linking strategic thinking with action in the management of tourism. It provides an analytical evaluation of the most important global trends, as well as an analysis of the impact of crucial environmental issues and their implications. Now in its third edition, and reviewing the major factors affecting international tourism management, this well-established student resource provides an essential overview of strategic management for students and professionals in the tourism sector.

Stay up to date with the most effective practices in tourism demand forecasting! Tourism Forecasting and Marketing presents vital, up-to-date research on the latest practice and applications of tourism demand modeling and forecasting. The book addresses both econometric and time series approaches to forecasting, focusing on the concepts, model specification, data analysis, and methodologies used in day-to-day tourism planning. An international panel of practitioners and academics call on a diverse range of empirical research findings to discuss commonly used theoretical frameworks for forecasting and future directions tourism demand is likely to take. Tourism Forecasting and Marketing presents research findings from the United States, the United Kingdom, Asia, and Australia that are invaluable for guiding government and private sector tourism investment and development decisions. The book addresses traditional versus modern forecasting techniques; evaluations of current and past forecasting methods; modeling and forecasting destination choice; and the impact of forecasting and marketing on tourism demand. Topics include: using time series models to forecast inbound tourism demand for China and Greece determining the economic factors that influence tourism demand in Hong Kong, Indonesia, and Malaysia examining domestic travel expenditures in South Korea developing a model to forecast ski tourism using the Palmore cohort analysis for tourism forecasting and much more! Tourism Forecasting and Marketing is an important textbook for educators and students working in tourism policy planning and management, and tourism marketing. The book is equally effective as a reference for travel and tourism researchers, and for professionals dealing with tourism demand analysis and forecasting.

The phenomenal growth of both the world-wide tourism industry and academic interest in tourism over the last thirty years has generated great interest in tourism demand modelling and forecasting from both sectors. However, the tendency for researchers and practitioners engaged in quantitative causal tourism modelling and forecasting to run many regression equations and try to choose the 'best' model based on various parametric and non-parametric criteria has been widely criticised as failing to provide credible results. The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications. The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data. The book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions.

The phenomenal growth of both the world-wide tourism industry and academic interest in tourism over the last thirty years has generated great interest in tourism demand modelling and forecasting from both sectors. However, the tendency for researchers and practitioners engaged in quantitative causal tourism modelling and forecasting to run many regression equations and try to choose the 'best' model based on various parametric and non-parametric criteria has been widely criticised as failing to provide credible results. The aim of this book is to present the recent advances in econometric modelling methodology within the context of tourism demand analysis at a level that is accessible to non-specialists, and to illustrate these new developments with actual tourism applications. The book begins with an introduction to the fundamentals of tourism demand analysis, before addressing the problems of traditional tourism demand modelling and forecasting, i.e. data mining and spurious regression due to common trends in the time series. Three chapters explore the general-to-specific approach to tourism demand modelling and forecasting, including the use of autoregressive distributed lag processes, cointegration analysis and error correction models. The time varying parameter model together with the use of the Kalman filter as an estimation method is a useful tool for examining the effects of regime shifts on tourism demand elasticities: this is explored next. The panel data approach is introduced as a way of overcoming the problem of estimation and forecasting biases caused by insufficient time series data. The book concludes by evaluating the empirical forecasting performance of the various models and putting forward some general conclusions.

Tourism demand is the foundation on which all tourism-related business decisions ultimately rest. This book introduces students, researchers and practitioners to the modern developments in advanced econometric methodology within the context of tourism demand analysis and illustrates these developments with actual tourism applications.

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Tourism Economics and Policy combines a comprehensive treatment of economic concepts and applications in tourism contexts. Topics include tourism demand and forecasting, tourism supply and pricing, measuring the impacts and benefits of changes in tourism demand, tourism investment and infrastructure, tourism taxation, aviation, tourism and the environment (including climate change) and destination competitiveness. The text provides an excellent basis for students to appreciate the relevance of economic analysis to the solution of real life tourism issues and as an input into tourism policy formulation.

Forecasting is one of the most important activities that form the basis for strategic, tactical, and operational decisions in all business organizations. Recently, neural networks have emerged as an important tool for business forecasting. Neural Networks in Business Forecasting provides researchers and practitioners with some recent advances in applying neural networks to business forecasting. A number of case studies demonstrating the innovative or successful applications of neural networks to many areas of business as well as methods to improve neural network forecasting performance are presented.