Scenario tree airline fleet planning for demand uncertainty

This paper proposes an innovative multi-period modeling approach to solve the airline fleet planning problem under demand uncertainty. The problem is modeled using a scenario tree approach. The tree is composed of nodes, which represent points of decision in multiple time stages of the planning horizon, and branches, representing demand variation scenarios. The branches link the decision nodes in consequent time stages and compose scenario paths. Fleet decisions are modeled according to these scenario paths, resembling the real-life process in which fleet plans are not defined in a single moment but instead are adjusted according to the demand development. Given that some scenario paths share common decision nodes, decisions among scenarios need to be synchronized. A mixed-integer linear programming model is proposed to determine the ideal fleet composition for each scenario in the tree and to describe this interdependency between scenarios. Considering the probability of a scenario, fleet composition probabilities for each time-period can be determined. Two real-world based case studies are performed to show the validity of the model. Results show that the proposed scenario tree approach can provide flexible multi-period airline fleet plans, which are more robust to future demand scenarios than fleet solutions obtained using the traditional approach of considering a single deterministic demand evolution scenario.     

Mitigation of airspace congestion impact on airline networks

In recent years European airspace has become increasingly congested and airlines can now observe that en-route capacity constraints are the fastest growing source of flight delays. In 2010 this source of delay accounted for 19% of all flight delays in Europe and has been increasing with an average yearly rate of 17% from 2005 to 2010. This paper suggests and evaluates an approach to how disruption management can be combined with flight planning in order to create more proactive handling of the kind of disruptions, which are caused by congested airspace. The approach is evaluated using data from a medium size European carrier and estimates a lower bound saving of several million USD.     

A robust hybrid decision model for evaluation and selection of the strategic alliance partner in the airline industry

Owing to the cut throat competition and economic uncertainty in the market, airlines are focusing on strategic alliances for satisfying customer needs, especially in the current time which is dominated by global integration, demanding customer and fast changing technologies. This strategy is widely adopted by airlines. However, the selection of strategic alliance partner is a very decisive decision, and this selection process engrosses a number of complex processes which is result of compound reflection of associated various factors. In addition, the decision makers may be inconsistent in their views and preferences, arising due to imperfect information or intrinsic conflict between various departments. This paper presents a model based approach of an analytic hierarchy process (AHP) for evaluation of criteria and fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) for the selection of strategic alliance partner. A case of Indian airline industry demonstrates the application of the proposed approach. Eventually, robustness of the model is demonstrated by sensitivity analysis.     

Examining a hybrid model for e-satisfaction and e-loyalty to e-ticketing on airline websites

In the air transportation industry, web-based marketing has already been widely applied to service frequent customers as well as to attract new ones. The importance of attracting new customers and keeping existing ones loyal to e-ticketing on airline websites is crucial. Accordingly, this study proposes an integrated model for evaluating the effectiveness of airlines' websites from a customer point of view. This model is based on the three perspectives of the marketing mix 4Ps, E-SERVQUAL and Expectancy Disconfirmation Theory. E-marketing and E-SERVQUAL features are divided into three dimensions, specifically information, system and service disconfirmations. The methodology was applied based on Structural Equation Modeling (SEM) and was administered to online customers who carry out e-ticketing via an airline website. The results show that customer disconfirmations have a positive significant impact on overall customer e-satisfaction. The significance of this relationship was more considerable in the service dimension of e-marketing, as well as the system dimensions of E-SERVQUAL and e-marketing. Moreover, overall e-satisfaction was found to mediate the relationship between customer disconfirmations and consumer e-loyalty.     

Towards a maturity model for big data analytics in airline network planning

The evaluation, acquisition and use of newly available big data sources has become a major strategic and organizational challenge for airline network planners. We address this challenge by developing a maturity model for big data readiness for airline network planning. The development of the maturity model is grounded in literature, expert interviews and case study research involving nine airlines. Four airline business models are represented, namely full-service carriers, low-cost airlines, scheduled charter airlines and cargo airlines. The maturity model has been well received with seven change requests in the model development phase. The revised version has been evaluated as exhaustive and useful by airline network planners. The self-assessment of airlines revealed low to medium maturity for most domains. Organizational factors show the lowest average maturity, IT architecture the highest. Full-service carriers seem to be more mature than airlines with different business models.