An extra-baggage service price setting with reference to cargo prices using multi-item newsvendor model. (February 2019)

• Record Type: Journal Article
• Authors: Shaban, I.A.; Wang, Z.X.; Chan, F.T.S.; Chung, S.H.; Qu, T.
• Is Part Of: Computers & industrial engineering. Volume 128(2019)
• Page Start: 877
• Page End: 885
• Publication Date: 2019-02
• Subjects: Pricing -- Air cargo -- Newsvendor -- Multi-item newsvendor -- Extra-baggage service; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.10.041
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: To solve the airline overcapacity problem, extra-baggage service is proposed. Comparing with the cargo, the passenger represents the extra-baggage shipper, as well as the consignee. The Multi-Item Newsvendor model is adopted to set the extra-baggage price with reference to existing cargo prices. The optimum extra-baggage price is calculated as the sum of the base and premium prices, as a function of cargo price. The premium value is the expected penalties divided by the expected sales. Abstract: The world is now considered as a small village, and with increasing commercial and cultural adverse between nations, air transport continues to boom and passenger numbers are continuously increasing. This increase leads to extensive use of wide-bodied aircraft which have large space in the aircraft belly-hold resulting in cargo sector having overcapacity. In this regard, the belly-hold overcapacity is discussed with two objectives to fill the unused spaces. Firstly, designing the extra-baggage service. Secondly, conferring price setting for the new service with reference to the cargo price. We adopt the multi-item newsvendor based pricing model to derive a price formula for the extra-baggage service as a function of cargo price. The stochastic extra-baggage and deterministic cargo demands were firstly modeled. The results showed that the optimal extra-baggage price can be determined as a function of cargo price in terms of the base price plus a premium price, but it gave an exaggerated extra-baggage price. Therefore, we modeled the cargo demand in stochastic form, and the second model showed better results because it cancels the effect of cargo penalties in deterministic cargo demand. Moreover, the stochastic cargo model gives the airline the opportunity to switch between two different pricing strategies either market penetration or pure premium strategy. Finally, the model can be generalized for any two products that share common features and serve in the same market.