Air Cargo Overbooking

1. Air Cargo Overbooking By Silvia Ito December 2nd, 2009

2. 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!

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

4. 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.

5. Air Cargos

7. Cargo Capacity

8. 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)

9. 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.

10. Passenger VS Cargo RM Passenger Cargo • 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)

11. 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

12. 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

13. 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

14. 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)

15. 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

16. 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

17. Overbooking Model • Newsvendor Problem: • Normal Distribution

18. 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:

19. 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

20. Overbooking Model • Newsvendor Problem: • Discreet Distribution

21. 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

22. 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

23. 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: AndreeaPopescu, 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.