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A latent class segmentation analysis of airlines based on website evaluation

dc.contributor.authorDíaz E.
dc.contributor.authorMartín-Consuegra D.
dc.date.accessioned2020-09-02T22:16:48Z
dc.date.available2020-09-02T22:16:48Z
dc.date.issued2016
dc.identifier10.1016/j.jairtraman.2016.04.007
dc.identifier.citation55, , 20-40
dc.identifier.issn09696997
dc.identifier.urihttps://hdl.handle.net/20.500.12728/4339
dc.descriptionCompany websites are an important instrument for relationship marketing activities. In the airline industry, web-based marketing has already been widely applied to service frequent customers as well as to attract new ones. Most of the established airlines are attempting to stimulate customers to shift from traditional distribution channels to online channels. Accordingly, this study identifies and evaluates different groups of airlines based on website evaluation. In order to achieve this objective, six dimensions of website persuasiveness (informativeness, usability, credibility, inspiration, involvement and reciprocity) are evaluated. The methodology applied is based on content analysis of a sample of 240 airline websites. The results obtained enable the identification and description of significant differences in the degree of persuasiveness displayed by the websites. Specifically, this research has identified three airline segments: (1) "influential", (2) "follower", and (3) "passive". The "influential" segment is the most persuasive and can generate influence on other groups of airline websites. The "followers airlines" segment comprises airlines that have a high initiative to implement tools to increase the persuasiveness of the websites. Finally, the "passive airlines" segment comprises airlines with lower website persuasiveness, along with low readiness to communicate and influence the users' buying decisions. The findings can provide valuable information for airlines managers to understand the relative level of competitiveness of their websites in the airline industry. © 2016 Elsevier Ltd.
dc.language.isoen
dc.publisherElsevier Ltd
dc.titleA latent class segmentation analysis of airlines based on website evaluation
dc.typeArticle


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