Designing and Pricing Services Based on Customer-Perceived Value: An Airline Company Feasibility Study

Abstract

W e propose a new integrated model for pricing airline tickets that takes into account the perceived value of multiple services associated with a given flight. For instance, clients perceive benefits on different attributes such as refund options, baggage allowances, time slots, days of operations, Web check-in services, as well as airline brand. These elements of perceived values are not, to our knowledge, modeled in existing yield management systems. Our integrated model includes a classical aggregate planner for services as well as a share of choice. In this paper, we have worked closely with an airline company and provided it with relevant managerial recommendations.

Coupling techno-economic energy models with behavioral approaches

“…In the present paper, we apply these techniques and propose an original method which enables us to take endogenously into account the consumer's real behavior in an energy model. This method couples technical methods from operations research with behavioral approaches from social sciences and is inspired by the method proposed in Fragnière et al (2008) and Fragnière et al (2012).…”

Impact of Penalty Cost on Customers' Booking Decisions

“…Through a multi-item newsvendor model, the authors show that to maximize profit, on wide-body aircrafts, airlines should reduce passenger baggage allowance limit and reserve more space for air cargo. Fragniere et al (2012) look at airline passengers' perceived value on baggage allowance as well as the other services associated with a commercial flight. The results suggest that higher baggage allowance leads to not only higher perceived value but also higher fuel cost.…”

“…Fragniere et al. (2012) look at airline passengers' perceived value on baggage allowance as well as the other services associated with a commercial flight. The results suggest that higher baggage allowance leads to not only higher perceived value but also higher fuel cost.…”

Optimal Design of E-Services: A Robust Approach

“…This approach has been further developed by Fragnière and colleagues [3,4], where a meta-model combining a share-of-choice model with a production model permits one to design and price a service in an optimal way. This method combines conjoint analysis with operations research and has been successfully used to tackle problems in different domains [5][6][7][8][9][10]. Unfortunately, this method has a major drawback for non-specialists.…”