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.
Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
TRB’s National Cooperative Highway Research Program (NCHRP) Report 716: Travel Demand Forecasting: Parameters and Techniques provides guidelines on travel demand forecasting procedures and their application for helping to solve common transportation problems.
Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers assess the validity and accuracy of demand forecasts. Forecasting and evaluating transport demand is an essential task of transport professionals and researchers that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand forecasts are necessary for companies and government entities when planning future fleet size, human resource needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport Demand help readers solve the problems they face on a daily basis. Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most suitable solution for all types of transport applications. - Presents the most recent and relevant findings and research - both at theoretical and practical levels - of transport demand - Provides a theoretical analysis and formulations that are clearly presented for ease of understanding - Covers analysis for all modes of transportation - Includes case studies that present the most appropriate formulas and methods for finding solutions and evaluating results
Modeling Applications in the Airline Industry explains the different functions and tactics performed by airlines during their planning and operation phases. Each function receives a full explanation of the challenges it brings and a solution methodology is presented, supported by numerical illustrative examples wherever possible. The book also highlights the main limitations of current practice and provides a brief description of future work related to each function. The authors have filtered the rich literature of airline management to include only the research that has actually been adopted by the airlines, giving a genuinely accurate representation of real airline management and its continuing development of solution methodologies. The book consists of 20 chapters divided into 4 sections: - Demand Modeling and Forecasting - Scheduling of Resources - Revenue Management - Irregular Operations Management. The book will be a valuable source or a handbook for individuals seeking a career in airline management. Written by experts with significant working experience within the industry, it offers readers insights to the real practice of operations modelling. In particular the book makes accessible the complexities of the key airline functions and explains the interrelation between them.
When predicting the future of air traffic development, it is imperative for researchers and planners tohave the most accurate information about airport capacity constraints. Airport capacity constraintsand strategies for mitigation: A global perspective analyses airport capacity constraints with empiricalmethods that forecast future capacities and capacity shortfalls.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 congested airports. It analysesempirical data to provide greater insight into the problems of airport congestion and capacity shortage.The authors present detailed global traffic forecasts for the years 2030 and 2040, and mitigation strategiesfor overcoming the problem of limited airport capacity.As expanding current airports becomes increasingly difficult, and time consuming - especially for hubs- the study of current and future airport capacity constraints becomes ever more needed. This bookprovides detailed information about how to correctly assess and quantify the problem of limited airportcapacity, while offering strategies for overcoming these issues for a healthy global air traffic network.
"This is a premier text by leading technical professionals, known worldwide for their expertise in the planning, design, and management of airports"--Provided by publisher.
'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.
In recent years, airline practitioners and academics have started to explore new ways to model airline passenger demand using discrete choice methods. This book provides an introduction to discrete choice models and uses extensive examples to illustrate how these models have been used in the airline industry. These examples span network planning, revenue management, and pricing applications. Numerous examples of fundamental logit modeling concepts are covered in the text, including probability calculations, value of time calculations, elasticity calculations, nested and non-nested likelihood ratio tests, etc. The core chapters of the book are written at a level appropriate for airline practitioners and graduate students with operations research or travel demand modeling backgrounds. Given the majority of discrete choice modeling advancements in transportation evolved from urban travel demand studies, the introduction first orients readers from different backgrounds by highlighting major distinctions between aviation and urban travel demand studies. This is followed by an in-depth treatment of two of the most common discrete choice models, namely the multinomial and nested logit models. More advanced discrete choice models are covered, including mixed logit models and generalized extreme value models that belong to the generalized nested logit class and/or the network generalized extreme value class. An emphasis is placed on highlighting open research questions associated with these models that will be of particular interest to operations research students. Practical modeling issues related to data and estimation software are also addressed, and an extensive modeling exercise focused on the interpretation and application of statistical tests used to guide the selection of a preferred model specification is included; the modeling exercise uses itinerary choice data from a major airline. The text concludes with a discussion of on-going customer modeling research in aviation. Discrete Choice Modelling and Air Travel Demand is enriched by a comprehensive set of technical appendices that will be of particular interest to advanced students of discrete choice modeling theory. The appendices also include detailed proofs of the multinomial and nested logit models and derivations of measures used to represent competition among alternatives, namely correlation, direct-elasticities, and cross-elasticities.
