Insurance premium model for case delay or cancelation of Indonesian local flight

Stefani, Dina; Lukas, Samuel; Adiwena, Stevanus; Margaretha, Helena; Widjaja, Petrus

doi:10.1063/1.5139126

Cited by 2 publications

(1 citation statement)

References 2 publications

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“…In the work of Samuel Lukas et al (Lukas et al 2019), they use standard deviation, Generalize Linear Model, and Support Vector machine to calculate the premium, which will be included in the ticket price and help the airline's company to improve their service and cover the cost of compensation. An insurance premium model for case delay or cancellation is proposed from Stefani et al (2019), the author found that the calculation works better when considering the airline and the departure city of the flight. However, the methods above have two shortcomings.…”

Section: Introductionmentioning

confidence: 99%

The personalized recommendation for OTA flight cancellation and change services during the pandemic

Gong¹,

Wang²,

Nie³

et al. 2022

J Revenue Pricing Manag

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The COVID-19 pandemic has had a dramatic impact on people's travels. Due to the recurrent pandemic and regionally different policies in China, travelers must pay a lot for flight cancellations and changes. To accommodate this, online travel agencies (OTA) can provide a more flexible ancillary as a supplement to the airline company's services. Here, we introduced the upgraded all-in-one (AIO) service package, which offers compensation for flight delays, changes, or refund. We also designed a dynamic recommendation engine (DRE), which can make real-time personalized recommendations. Backed by AB testing, the machine learning-based DRE not only raises the package attach rate without interrupting the flight ordering process, but also helps the customers cut cost when making flight cancellations or changes.

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Section: Introductionmentioning

confidence: 99%