Evaluating predictability based on gate-in fuel prediction and cost-to-carry estimation

Lei Kang, Mark Hansen and Megan S. Ryerson

Journal of Air Transport Management, 2018, vol. 67, issue C, 146-152

Abstract: Predictability in the aviation system affects costs to airlines and passengers. We propose a predictability metric based on a flight's gate-in fuel (GIF) which can be directly measured and monetized by aviation stakeholders. We estimate GIF for six major U.S. airlines. Since GIF data are not directly available, we develop an estimation methodology to obtain GIF from pushback weight and fuel burn, including a conversion from passenger to weight payload based on an econometric model. The methodology accounts for aircraft operating empty weight and payload. We find that GIF varies across airlines and time of year, and is highest during the summer period. We monetize GIF through a cost-to-carry analysis as extra fuel loading results in additional fuel burn. Our estimates reveal that, in 2012, airlines spent an additional $59 million to $667 million on carrying GIF, with a total across all six airlines of $1.46 billion.

Keywords: Predictability metric; Gate-in fuel; Cost-to-carry; Monetization; Benefit assessment (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:67:y:2018:i:c:p:146-152

DOI: 10.1016/j.jairtraman.2017.11.006

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