Air Cargo Overbooking By Silvia Ito December 2 nd, 2009

Introduction Companies have started to ship their freight (cargo) more by air due to: ▫Globalization of trade ▫Increasing use of advanced logistics techniques ▫Rise of e-commerce It is said that the air cargo traffic will expand 3 times more than now for the next 2 decades!

Introduction Air-Cargo Supply Chain’s major players: ▫Shippers ▫Freight Forwarders (FF)  Third party logistics provider that books/arranges cargo spaces for shipments. ▫Airlines

The booking process 6 to 12 months before flight departure: ▫Freight Forwarders bid for cargo space with airlines in order to accommodate shippers demand. Allotted Capacity: Cargo capacity completed during the auction process. Cargo Capacity: Remaining capacity for free-sale.

Air Cargos

Cargo Capacity

The booking process Airlines must manage Cargo Capacity effectively, given the potential revenues from air transportation of freight. Cargo Capacity is perishable and is limited. ▫Perishable: Can be sold at different prices (depending on service: express or normal)

Revenue Management Revenue Management (RM) has been used for a while in the passenger business. Airlines seek to adapt the same techniques to cargo business. However, passenger and cargo differ in important ways.

Passenger VS Cargo RM PassengerCargo Space constraint: ▫1 dimensional: Seat Time window which airline offers capacity for free sale: ▫Longer Space constraint: ▫2 dimensional : Weight and Volume Time window which airline offers capacity for free sale : ▫Shorter (no more than 30 days before departure)

Factors affecting available capacity Freight Forwarders (FF) bid on more capacity than needed (to ensure space on constrained flights). ▫FFs are allowed to return unwanted space at no charge. Airlines don’t charge for changing reservations. You can cancel a booking, rebook to a different flight, cancel again, rebook back, etc After the bids, airlines add the completed spaces to the pool of capacity available for free sale

Factors affecting available capacity Thus until flight departure date, airlines don’t know how much: ▫ Cargo Capacity they have available for free sale ▫Allotted Capacity will be unused

Factors affecting available capacity Combination carriers (planes carrying cargo and passengers) cargo space contains both passenger’s baggage and cargo in the same compartment. All these factors plus: ▫Weather (it affects the amount of fuel on board the aircraft) and Mail influences how much capacity is available for free sale

Why Overbook? Airlines’ sell more capacity than what’s physically available to compensate for cargo that doesn’t show up at departure. Airlines commonly overbook their capacity to protect themselves from: ▫Variability in the amount of cargo actually given at departure. ▫Customer’s cancellations. ▫(and possible financial loss of course)

Important considerations in overbooking 1) Spoilage ▫Excess capacity at departure ▫(you turned demand away!) ▫Caused by having a low overbooking level 1) Off-loads ▫More capacity demanded than avail at departure ▫(You cannot accommodate the booked demand!) ▫Caused by having a too high overbooking level

Overbooking Model Overbooking Model’s goal: ▫To minimize lost revenue (spoilage) and excessive cargo off-loading Overbooking Model: ▫Passenger sector formulates it as a Newsvendor problem

Overbooking Model Newsvendor Problem: ▫Normal Distribution

Cargo Show-Up Rate Model Airlines base their decisions on: ▫Predictions of show-up rate  % of demand booked that shows up at departure ▫Show-up rate (SR) for weight and volume are estimated separately, so for weight:

Normal or Discreet? Passenger sector: ▫Uses Normal Distribution to estimate show-up rate ▫Good for approximation Air-cargo sector ▫Normal Distribution is NOT a good fit for estimating show-up rate. ▫This case proposes to use a Discrete Distribution

Overbooking Model Newsvendor Problem: ▫Discreet Distribution

Why Discrete Distribution? For the Show-up rate: ▫Discrete estimator outperforms normal estimator in various aspects:  Overbooking levels  Average yearly savings  Improved customer satisfaction  Increased profits

Discrete estimator is better! Overbooking levels ▫Better approximation of capacity at departure in terms of MAE (Mean Absolute Error) between bid cargo and actual capacity at departure, standard deviation of error (SE), spoilage, and off- loads. Average Yearly Savings ▫For combination carrier with 300 flights/day and average cargo capacity per departure of 13,000kg, savings were $16,425,000 Better customer service ▫Lower mean spoilage = better utilization of capacity = more customers served promptly ▫No increase in off-loads = airline turns down fewer customer

Notes: This PPT presentation was for DESC372 class. Students were supposed to present cases given by professor, thus this presentation summarizes the key aspects of the case in relation with what we studied in class (Revenue Management: Overbooking, Newsvendor Problem, etc) This presentation was made by a student and posted online for Concordia students studying Supply Chain Operations Management. Case: Andreea Popescu, Pinar Keskinocak, Ellis Johnson, Estimating Air-Cargo Overbooking Based on a Discrete Show-Up- Rate Distribution, Interfaces, Vol. 36, No. 3, May–June 2006, pp. 248–258.