Modeling overbookings on air cargo transportation

Abstract

PurposeIn order to hedge against fluctuation in actual “show” for air freight services, cargo airlines engage in the allocation of more space capacity than they actually have. This practice can lead to overbooking of capacity which can incur costs to the airline when a cargo does show that is larger than predicted. In this study, the authors set out to model an optimised value for air cargo booking which is tested against five different cargo case‐representative scenarios. The paper aims to discuss these issues.Design/methodology/approachThe methodology which is primarily discursive utilises a synthesis of existing literature to develop a model to replicate the overbooking problem.FindingsThis paper finds that the optimised value of cargo size may not necessarily depend on the probability of actual “show”. Instead, this variation appears dependent on a random demand for larger sized cargo, and thus, price.Practical implicationsThe model which is developed serves as a potential framework for airlines to avoid uncertainty associated with cargo capacity spoilage and overbooking.Originality/valueIn this study, the passenger overbooking model under the cancellation and no‐show problems in the static single leg case was adapted for use during the modelling of air cargo overbooking.

A mixed wholesale-option-contract to fix the demand imbalance between substitutable air cargo routes: A cooperative game approach

“…Similarly, a fuzzy reasoning model used the same parameters to obtain overbooking levels (Wang & Kao, 2008). Furthermore, it has been indicated that cancellation rates and shipping information records should be added to these parameters in overbooking calculations (Chalermkiat et al, 2013). Additionally, Kasilingam (1997a) discussed the difference between passenger and cargo overbooking as a revenue management tool.…”

Voluntary overbooking in commercial airline reservations

“…Scientific methods have been successfully used to improve revenue management in the commercial airline industry (Singhaseni et al, 2013;Rose, 2016;Yeoman, 2016). One of those improved areas is in seat pricing and allocation (see Singhaseni et al, 2013;Lan et al, 2015;Hjorth et al, 2018;Ko, 2019).…”

“…Scientific methods have been successfully used to improve revenue management in the commercial airline industry (Singhaseni et al, 2013;Rose, 2016;Yeoman, 2016). One of those improved areas is in seat pricing and allocation (see Singhaseni et al, 2013;Lan et al, 2015;Hjorth et al, 2018;Ko, 2019). Commercial airlines will reserve airline seats in excess of their existing capacity (overbooking) as a way to counter the loss of revenue from 'no shows', late cancellations, and early and/or late departures.…”

Oimpacts of Multi-Class Oversubscription on Revenues and Performance in the Cloud

“…The healthcare industry overbooks doctors' time which can lead to increased waiting time for customers and physician overtime costs when all patients arrive for their appointments (Zacharias & Pinedo, 2013). Airlines have been known to overbook seats (Coughlan, 1999) and cargo space (Singhaseni, Wu, & Ojiako, 2013). When more customers show up than predicted, they are typically moved to another flight which causes delays and other inconveniences for the customer.…”