DEMATEL and ANP
A combined MCDM model based on DEMATEL and ANP for the selection of airline service quality improvement criteria: A study based on the Taiwanese airline industry
abstract The aim of this study is to select airline service quality improvement criteria for the Taiwanese airline industry. Numerous factors such as low railway prices, the development of high-speed rail, increases in petroleum prices, increases in foreign airline competition, and the recent economic depression have led many airlines in Taiwan to encounter financial difficulties and even closure. Researchers have begun to identify critical service quality improvement criteria with the goal of increasing the competitive advantages of airlines. Most of the selected criteria, however, suffer from a major technical problem: all of the measurement dimensions are independent, leading to inadequate criteria for measuring service quality. Our calculations consider the interrelationships and effects among the evaluation dimensions and criteria to precisely rank and select criteria. The value of this study is that it provides airlines with a direction for measuring and improving their service quality with the goal of developing sustained competitive advantage over the long term
Keywords: Service quality Airline Taiwanese airline industry DEMATEL ANP MCDM
Introduction
In light of Taiwan's demographics and geographical structure as an island, its interactions and global trade depend largely on marine transit and airlift activities (Civil Aeronautics Administration [CAA], 2009). However, airlift activities are much more important in determining efficiency than marine transit activities, and effi- ciency in these activities is necessary to improve the Taiwanese economy and its international relationships. With the current domestic and international pressures stemming from, for example, low railway prices, the development of high-speed rail, increases in petroleum prices, increases in foreign airline competition, and the recent economic depression, an increasing number of airlines are facing financial difficulties due to a deficit and low market share, and some airlines failed to survive beyond late 2008. To resolve these difficulties, an increasing number of airlines have focused on improving their service quality to provide customers with a comfortable and safe experience while transporting them to their destinations on time (Wu et al., 2012). In this study, we do not consider low-cost carriers such as Ryanair. Based on O'Connell and Williams's (2005) research findings, passengers who travel on low-cost carriers pay great attention to price and arrange their itineraries to take advantage of the least expensive airfares. Thus, they do not focus on other factors when they book their travel, and the brand reputations of low fare airlines have been embedded into their minds (O'Connell and Williams, 2005). O'Connell and Williams also find that passengers who use full service airlines do pay attention to price but tolerate higher airfare to acquire the advantages of the additional products and/or services provided by such airlines (O'Connell and Williams, 2005). In short, the market segment of low-cost carriers is customers who do not pay attention to service quality but to price, while the market segment of full service carriers primarily pays attention to service quality over price. Therefore, it would not be appropriate to incorporate low-cost carriers in this study, as we aim to provide a direction for airlines that use service quality as part of their strategy for developing sustained competitive advantages in the long term by helping them to measure and improve their service quality. Lowcost carriers are therefore beyond the scope of this study. Although a stream of studies has developed numerous related models accompanied by various evaluation indices, the study of such indices has been predicated on a major technical problem;
pany. An ANP is usually conducted to loosen the restrictions of hierarchical structures (Yang et al., 2008) and was originally proposed by Saaty (1996). The ANP is used to address the hierarchical representation of relationships by taking the dependency of the factors (e.g., criteria and/or indices) into account while calculating the data (Yüksel and Dagdeviren, 2007). Many decision-related problems are difficult to structure hierarchically because they involve interaction and dependence between higher- (e.g., dimensions and/or criteria) and lower-level elements (e.g., criteria and/or indices). The ANP replaces hierarchies with networks and emphasizes the interdependent relationships among various decision criteria, therefore allowing for a more systematic analysis (Franek and Kresta, 2013). The current research demonstrates the advantages and reliability of each method (Lin and Wu, 2008; Momoh and Zhu, 2003). In this study, the DEMATEL is adopted to determine causal relationships and different impacts among service improvement dimensions. The IRM of the service improvement dimensions, which is developed through the DEMATEL, becomes a network evaluation structure for an ANP analysis, which is then used to calculate the relative weights of the service improvement criteria. The remainder of this study is organized as follows. Service quality in the airline industry is discussed in Section 2. A combined MCDM model is proposed in Section 3. An empirical study is conducted in Section 4. A discussion on the application of our results to practice is presented in Section 5. A conclusion is presented in the final section.
