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Forecasting Air Travel Demand

Forecasting Air Travel Demand PDF Author: Yafei Zheng
Publisher: Routledge
ISBN: 1351215493
Category : Business & Economics
Languages : en
Pages : 156

Book Description
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.

Forecasting Air Travel Demand

Forecasting Air Travel Demand PDF Author: Yafei Zheng
Publisher: Routledge
ISBN: 1351215493
Category : Business & Economics
Languages : en
Pages : 156

Book Description
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.

Forecasting Air Travel Demand

Forecasting Air Travel Demand PDF Author: Yafei Zheng
Publisher: Routledge
ISBN: 1351215485
Category : Business & Economics
Languages : en
Pages : 232

Book Description
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.

A Model for Forecasting Future Air Travel Demand on the North Atlantic

A Model for Forecasting Future Air Travel Demand on the North Atlantic PDF Author:
Publisher:
ISBN:
Category : Aeronautics, Commercial
Languages : en
Pages : 196

Book Description
Introduction: One of the key problems in the analysis and planning of any transport properties and facilities is estimating the future volume of traffic that may be expected to use these properties and facilities. Estimates of this kind are now being made regularly as the transport system continues to expand. The future planning, implementation and operation of a successful transportation system requires accurate and realistic forecasts of traffic volumes. To achieve optimal policies, the planner needs to be able to predict the effect of alternate decisions. Although the planning process involves much more than a forecast of the future traffic statistics, these statistics provide the essential quantitative dimensions for the planning process. Forecasts of expected traffic are an essential prerequisite to long-range planning. The link between planning and forecasting lies in recognizing that in order to bring an expected situation under control, the planner must be provided with the entire spectrum of situations that could be anticipated and, hence, could be planned for. The reasonableness and reliability of these traffic statistics is, therefore, of vital importance to the planner. This study investigates the North Atlantic passenger travel demand. The final goal is to make a forecast of the passenger traffic on this route. It is believed that such a forecast would prove to be a critical tool for long-range planning of transport properties and facilities on both sides of the Atlantic. For this reason, it is important to be well informed about the technical and economic factors which will determine and limit the travel volume, especially for manufacturers of aircraft, domestic and international airlines, and the government. Governments, for example, must be provided with traffic forecasts if they are to provide adequate ground facilities and air traffic control systems.

Forecasting air travel demand between city pairs

Forecasting air travel demand between city pairs PDF Author: Richard Nelson Winter
Publisher:
ISBN:
Category : Aeronautics, Commercial
Languages : en
Pages : 124

Book Description


Travel Demand Forecasting: Parameters and Techniques

Travel Demand Forecasting: Parameters and Techniques PDF Author:
Publisher: Transportation Research Board
ISBN: 0309214009
Category : Traffic estimation
Languages : en
Pages : 170

Book Description
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.

Studies in Travel Demand

Studies in Travel Demand PDF Author: Ronald E. Miller
Publisher:
ISBN:
Category : Transportation
Languages : en
Pages : 206

Book Description


Forecasting (Aggregate) Demand for U.S. Commercial Air Travel

Forecasting (Aggregate) Demand for U.S. Commercial Air Travel PDF Author: Richard T. Carson
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

Book Description
We analyze whether it is better to forecast air travel demand using aggregate data at (say) a national level or whether one should aggregate forecasts derived for individual airports using airport-specific data. We compare the U.S. Federal Aviation Administration's (FAA) practice of predicting the total number of passengers using macro economic variables with an equivalently specified AIM (aggregating individual markets) approach. The AIM approach outperforms the aggregate forecasting approach in terms of its out-of-sample air travel demand predictions for different forecast horizons. Variants of AIM, where we restrict the coefficient estimates of some explanatory variables to be the same across individual airports, generally dominate both the aggregate and the AIM approaches. The superior out-of-sample performance of these so-called quasi-AIM approaches depend on the trade-off between heterogeneity and estimation uncertainty. We argue that the quasi-AIM approaches efficiently exploit the heterogeneity across individual airports without suffering from as much estimation uncertainty as the AIM approach.

Airline Traffic Forecasting

Airline Traffic Forecasting PDF Author: Nawal K. Taneja
Publisher: Free Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 264

Book Description


The Oxford Handbook of Economic Forecasting

The Oxford Handbook of Economic Forecasting PDF Author: Michael P. Clements
Publisher: OUP USA
ISBN: 0195398645
Category : Business & Economics
Languages : en
Pages : 732

Book Description
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.

New Directions for Forecasting Air Travel Passenger Demand

New Directions for Forecasting Air Travel Passenger Demand PDF Author: Donald Stephen Garvett
Publisher:
ISBN:
Category : Aeronautics, Commercial
Languages : en
Pages : 163

Book Description
While few will disagree that sound forecasts are an essential prerequisite to rational transportation planning and analysis, the making of these forecasts has become a complex problem with the broadening of the scope and variety of transportation decisions. Until recently, the forecasting methods available addressed the issues which were important a couple of decades ago. These methods attempted to predict the amount and in some cases character of travel to be used in designing major highways, transit facilities, seaport facilities, and airports. However, today's issues to be addressed in transportation are much broader and more complex. For example, in the modern process of transportation planning, the decision-maker is concerned with the broad range of social, economic and environmental effects, equity issues, wider range of options including not building major facilities, resource constraints such as energy, and increased public participation in the planning process in general. The complexity of the problem has necessitated the planner's developing improved methods of forecasting the demand for transportation at all levels and by all modes. While significant contributions have been made recently to the development of improved methods in forecasting, we are still a long way from possessing tools which provide our decision-makers with more effective, that is, more useful, accurate and timely information. The purpose of this report is to present a very brief overview of the current and emerging air transportation forecasting methods with the aim of identifying areas which need further research. Throughout the report, the object is to indicate future directions for research into transportation forecasting methods which are more responsive to today's issues. For example, it is clear from reviewing the literature that tremendous improvements in travel forecasting methods can be achieved through deeper understanding of the traveler's behavior, under a range of conditions, development of models which are more policy-responsive and development of improved data bases. Peculiarities of the airline industry and aviation in general cause many standard techniques of economic and managerial analyses to break down. Air travel demand is unique in that even the sophisticated techniques developed by urban transportation analysts are often not directly applicable to modelling the demand for air transportation. Econometricians usually do not have specific training in air transportation. Airline managers, on the other hand, quite often do not have the technical background necessary to fully understand many highly detailed and complex models. In order to develop sophisticated yet user-oriented models, an analyst must have background in several areas. It is hoped that the material presented in this report will help bridge the gap between managerial and technical personnel and provide some new directions for air travel demand modelling. Generally speaking, there are two broad categories of forecasting methods. The quantitative group is composed of techniques which rely on the existence of historical data, and which assume that the historical trend will be expected to continue in the future. This group is further divided into two classes, time-series methods and causal methods. The quantitative techniques are by far the most widely used and contain such popular methodologies as moving averages, classical decomposition analysis, spectral analysis, adaptive filtering and Box-Jenkins methods under the category of time-series analysis. The causal methods contain such favorites as modelling classical consumer behavior through regression models and more recent applications in transportation demand analysis of Bayesian analysis, Markov chains, input-output analysis, simulation methods and control theory models. The second group of forecasting methods is qualitative in nature. The techniques in this group are used when none or very little historical data exists, or when the underlying trend of the historical data is expected to change. Qualitative techniques have in general been applied to project future technological developments and their impacts are described in literature as "technological forecasting methods." The group is further divided into two classes, exploratory and normative methods. The exploratory methods start with today's knowledge and its orientation and trends and seek to predict what will happen in the future and when. On the other hand, normative methods seek first to assess the organization's goals and objectives and then work backwards to identify new developments which will most likely lead to the achievement of these goals. Familiar examples of exploratory methods are the envelope, logistic or S-curve, the Delphi technique and morphological analysis. Examples of methods used to perform normative forecasting are relevance trees and cross impact analysis. Although this classification scheme is consistent with the way that many forecasters might differentiate models, it is by no means unique. Other and perhaps better classification schemes exist. For the purposes of this report we will not attempt to define a particular classification but present five broad areas which show the greatest potential for improving our capabilities of modelling the demand for air transportation. These areas are: technological forecasting, time-series models, control theory models, econometric models and simulation models. Each of the general techniques are reviewed, and specific examples are presented where relevant. Excessive mathematical detail was avoided in order to make this work easily understandable by managers and others who might not have a rigorous analytical background. Since a number of models discussed in the report require extensive computer modelling, we have included a few computer programs in the appendices to make the report more user-oriented.