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Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach

Overview of attention for article published in SpringerPlus, July 2016
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Title
Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach
Published in
SpringerPlus, July 2016
DOI 10.1186/s40064-016-2623-5
Pubmed ID
Authors

Ronald Wesonga, Fabian Nabugoomu

Abstract

The study derives a framework for assessing airport efficiency through evaluating optimal arrival and departure delay thresholds. Assumptions of airport efficiency measurements, though based upon minimum numeric values such as 15 min of turnaround time, cannot be extrapolated to determine proportions of delay-days of an airport. This study explored the concept of delay threshold to determine the proportion of delay-days as an expansion of the theory of delay and our previous work. Data-driven approach using statistical modelling was employed to a limited set of determinants of daily delay at an airport. For the purpose of testing the efficacy of the threshold levels, operational data for Entebbe International Airport were used as a case study. Findings show differences in the proportions of delay at departure (μ = 0.499; 95 % CI = 0.023) and arrival (μ = 0.363; 95 % CI = 0.022). Multivariate logistic model confirmed an optimal daily departure and arrival delay threshold of 60 % for the airport given the four probable thresholds {50, 60, 70, 80}. The decision for the threshold value was based on the number of significant determinants, the goodness of fit statistics based on the Wald test and the area under the receiver operating curves. These findings propose a modelling framework to generate relevant information for the Air Traffic Management relevant in planning and measurement of airport operational efficiency.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 22%
Student > Master 2 22%
Researcher 1 11%
Professor 1 11%
Unknown 3 33%
Readers by discipline Count As %
Engineering 3 33%
Social Sciences 1 11%
Mathematics 1 11%
Unknown 4 44%