This book provides an updated, concise summary of forecasting air travel demand methodology. It looks at air travel demand forecasting research and attempts to outline the whole intellectual landscape of demand forecasting. It helps readers to understand the basic idea of [email protected] methodology used in forecasting air travel demand and how it is used in developing air travel demand forecasting methods. The book also discusses what to do when facing different forecasting problems making it a useful reference for business practitioners in the industry.
2. Existing Research
3. Theoretical Basis – [email protected] Methodology
4. Scientometric Analysis of Demand Forecasting (1975-2015): A Visual Description
5. An Integrated Short-term Forecasting Framework with Empirical Mode Decomposition Method
6. A Novel Seasonal Decomposition-based Short-term Forecasting Framework with Google Trends Data
7. A Medium-term Demand Forecasting Method Based on Stochastic Frontier Analysis and Model Average
8. Long-term Air Travel Demand Forecasting: An Integrated Method with ARDL Bounds Testing Approach and Scenario Planning
9. Conclusion and Future Research
Risk management is one of the most important, most urgent and most difficult topics for not only top managers of every enterprise and top officials of every governmental department, but also for scientists in the fields of economics, finance, engineering, social science and earth science.
The book series places emphasis on the main problems of risk management in the changing new environments of operational and systems management. It invites quality works covering analysis, modeling, empirical studies and case analysis so as to offer solutions to the emerging new challenges.
It aims to publish new theories of risk management, new methods for risk management and new successful applications in risk management to promote research and development of risk management in many industries and many disciplines; to provide a bridge for exchange of academic researchers and practical risk managers to help academic researchers’ better understanding of risk and risk management and to help managers and officials to learn new methods, techniques and tools which might be efficient in risk identification, risk analysis, risk control and risk management.