A hybrid ANP model in fuzzy environments for strategic alliance partner selection in the airline industry
Introduction
Strategic alliances between airlines are now common in the aviation industry. They are frequently made in response to changing economic and regulatory conditions [1]. Three major alliances established within the last 10 years—Star Alliance, One-world and Sky Team—now account for nearly 70% of passengers and turn-over in the global market [2]. Strategic alliance strategies allow airlines to expand networks, attract more passengers, and take advantage of product complementarities, as well as providing cost-reduction opportunities in passenger service related areas (such as code-sharing, joint baggage handling, joint use of lounges, gates and check-in counters, and exchange of flight attendants) [3]. A good strategic partner can further enhance the quality of their connecting services by adjusting arrival and departure flights so as to minimize waiting time between flights while providing sufficient time to make connections. On the other hand, ineffective strategic alliances can lead to the loss of core competencies and capabilities, exposure to unexpected risk and even business failure. Take for example—the fall of Swissair. Financial statements show that its airline alliance policy and investment strategy were responsible for the majority of its losses from 1997 to 2001 [4].
Prior research suggests that the choice of alliance partner is an important variable with significant influence on the performance of the strategic alliance partners [5], [6]. An appropriate partner is one that can contribute resources and capabilities that the focal firm lacks. This ultimately determines the viability of the strategic alliance. Partner-related selection criteria require consideration to determine whether the corporate cultures of the partners are compatible, and whether trust exists between the partners’ management teams. This ensures that the selected partner and focal firm achieve organizational interdependence. Although the importance of selecting the right partner for forming strategic alliances has been recognized in literature, there have been few empirical studies on how to choose that partner which stress the interrelationship between the partners and the focal firm at the same time. The analytic network process (ANP) was proposed by Saaty [7] to overcome the problem of interrelation among criteria or alternatives. The ANP is a general form of the analytic hierarchy process (AHP), which releases the restrictions of the hierarchical structure. It has been successfully applied in many multi-criteria decision making (MCDM) problems [8], [9], [10], [11]. However, due to problems such as incomplete information and subjective uncertainty, even experts find it difficult to quantify the precise ratio of weights for the different criteria. The concept of fuzzy sets has been incorporated into AHP to deal with the problem of uncertainty, although ANP has not often been used to address this type of problem in fuzzy environments. A way to cope with uncertain judgments and to incorporate the vagueness that typifies human thinking is to express the preferences as fuzzy sets or fuzzy numbers [12]. Therefore, the objective of this study is to combine fuzzy preference programming and ANP to make a model capable of helping airlines select the best partner for strategic alliances.
The rest of this paper is structured as follows: In Section 2, we summarize some of the important previous studies regarding the strategic alliance strategy, and the problem characteristics are described. In Section 3, the basic concepts of fuzzy preference programming and ANP are reviewed. In Section 4, a strategic alliance model is developed. The implementation using the proposed fuzzy ANP is presented in Section 5. Section 6 includes discussions and some conclusions.
Section snippets
The strategic alliance
While merger activities have slowed significantly since 2000, strategic alliances are increasingly and widely used by airlines. International alliances give airlines access to parts of the world than would otherwise be economical, or where there may lack the authority to operate their own flights [3]. Through alliances, partners are able to compete more successfully. Yoshino and Rangan [13] and Gomes-Cassers [14] define the alliance as a cooperative venture between firms situated on the
Proposed hybrid fuzzy preference programming and ANP model
In this section, the concepts of fuzzy preference programming for coping with the uncertain judgments in a group-decision process are first introduced. The ANP method for determining the best partner for the strategic alliance is then discussed, including consideration of the dependence and feedback effects. The combined model can help companies to evaluate a suitable partner and fulfill their specified needs.
Constructing a strategic partnering model for analysis
The model was developed and validated using input from an international airline operating in Taiwan. This airline currently flies to more than 40 destinations around the world, although most are within the Asia Pacific region. The company has sought to join strategic alliances in order to develop a far-reaching service network and increase competitive power, to enhance the effectiveness of its global logistics and to provide better service for satisfying customer needs. The decision is a
Implementation of the proposed hybrid model
In this study, the general manager of the airline under study designated a team to develop a strategic partner selection plan. Twenty-five managers from different departments, including planning, operation, maintenance, human resources, information systems, and safety, with at least 15 years experience in the airline and expertise in their own particular fields filled out a survey.
Concluding remarks
The purpose of this paper is to describe a method for strategic alliance selection that allows for consideration of important interactions among decision levels and criteria. We use a hybrid model combining fuzzy preference programming and ANP methodology that considers uncertainty in group decisions, and both inner dependence and feedback effects for this evaluation. We develop a model for the strategic alliance partner selection process based on the literature and adapted for an airline in
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