Wadud, Z (2014) Simultaneous modeling of passenger and cargo demand at an airport. Transportation Research Record: Journal of the Transportation Research Board (2336). 63 - 74. ISSN 0361-1981
Abstract
Forecasts for passenger and cargo demands are important parameters for airport planners. Although there are a number of studies for passenger demand in an airport, the number of studies for air cargo is much smaller. Also, these two entities are often dealt with separately in the literature. However, there can be advantages in modeling them simultaneously, especially when time series data are used for estimating the demand models. A seemingly unrelated regression (SUR) framework is followed to jointly model passenger and cargo demand at the Shahjalal International Airport at Dhaka, Bangladesh. Allowing for contemporaneous correlation between the air passenger and air cargo demand models in the SUR approach allows a more efficient and reliable estimate than ordinary least squares and individual cointegration methods. Results of the simultaneous demand modeling are used to forecast passenger and cargo demand at the airport up to 2030.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014, Transportation Research Board of the National Academies. This is an author produced version of a paper published in Transportation Research Record: Journal of the Transportation Research Board. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) > Energy Research Institute (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Jun 2014 10:20 |
Last Modified: | 16 Nov 2016 00:02 |
Published Version: | http://dx.doi.org/10.3141/2336-08 |
Status: | Published |
Publisher: | Transportation Research Board of the National Academies |
Refereed: | Yes |
Identification Number: | 10.3141/2336-08 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:78977 |