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 TEI@I 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.

Introduction: One of the axioms in the air transportation industry is that advances in technology have led to a greater amount of passenger travel by air. Improvements in airframe and engine design have increased range, speed and payload and have decreased seat-mile costs (in constant dollars), while simultaneously introducing more comfortable and safer travel. The resultant lower ticket prices have made pleasure travel steadily more attractive in the competition for the consumer's disposable income, while the availability of comfortable, high speed travel has increased the air mode's share of business travel. However, it has not been a trivial matter to determine the magnitude of travel that can be attributed to advanced aircraft technology. NASA, as the U.S. government agency responsible for research and technology in commercial aviation, has a natural interest in the applications of the technological improvements it has helped to create. Thus NASA has sponsored research analyzing the economic and operational impact of technological innovations; some of these studies have attempted to quantify the demand for air transportation that improvements in technology have brought about. This report presents the final results of an econometric demand model developed by the MIT Flight Transportation Laboratory under NASA sponsorship over the course of the last three years. During the first two years the conceptual framework for the model was developed and the initial calibration was undertaken.* Preliminary results were encouraging and validation and refinement of the model continued under Langley sponsorship during 1978. The model that was finally developed is useful for analyzing long haul domestic passenger markets in the United States. Specifically, it was used to show the sensitivities of passenger demand to changes in fares and speed reflecting technology through more efficient designs of aircraft; and to analyze, through the year 2000, the impact of selected changes in fares, speeds, and frequencies on passenger demand.

Capacities, Capacity Constraints and Capacity Reserves of Airports, Today and in the Future analyzes airport capacity constraints with empirical methods that forecast future capacities and their capacity shortfalls. When predicting the future of air traffic development, it is imperative for researchers and planners to possess the most accurate data for airport capacity constraints. The book discusses in detail the importance of airport capacity constraints on air traffic development, especially for international hubs, along with mitigation strategies for already packed airports. The book analyzes cross-sectional time-series data to provide greater insight into the problems of airport crowding and over-capacity. The authors go beyond mere strategies to derive capacity, adding estimates for comparable capacities and capacity constraints of airports worldwide. As expanding current airports becomes increasingly difficult, and time consuming-especially for hub-the study of current and future airport capacity constraints becomes ever more needed. Large international airports are especially essential to the global air transport network. The book provides insight into correctly assessing and quantifying the problem of limited airport capacity, while offering strategies for overcoming these issues for a healthy global air traffic network. Focuses on airport capacity constraints in the global air traffic network and their implications for the future of air traffic development Features empirical and model-based approaches that forecast airport capacities and capacity shortcomings Provides over capacity mitigation strategies based on sound and reliable data and methodology Addresses capacity constraints at hub airports, providing insight into correctly assessing and quantifying limited capacity for these important players in the global air transportation network Applies econometric models for the implication of restraining factors on the future volume and structure of air traffic