Paradise for who? Segmenting visitors' satisfaction with cognitive image and predicting behavioural loyalty

Abstract

The purpose of this research is to assess the infl uence of socio-demographic characteristics on destination image and loyalty, thereby offering a segmentation perspective of visitors to the island of Mauritius. A self-administered survey of hotel guests was undertaken and resulted in a sample of 705 respondents. Using a k-means clustering algorithm and discriminant analysis, three clusters of visitors were identifi ed. Different image attributes predict visitors' revisit and recommendation intentions. These fi ndings allow destination marketers to adapt the marketing mix elements to different segments while enabling a destination to emphasize the relevant attributes in promotion and positioning efforts.

Bagged fuzzy clustering for fuzzy data: An application to a tourism market

“…Within image segmentation studies, two distinct approaches exist: a priori [e.g., 37,49,50] and post-hoc [e.g., 29,31,51]. The segmentation of images is not only prevalent in tourism studies but has also been related to benefit segmentation.…”

“…Existing studies on segmentation of destination images or pull attributes have relied on a variety of techniques including, cluster analysis [31,56], factor-cluster analysis [29,30,55], factor analysis and t-test/ANOVA [51], factor analysis and regression [57], canonical correlation analysis [14], and multi-dimensional scaling [48] amongst many others. The use of a factorcluster approach for segmentation in general has been heavily criticized [see 1,58].…”

“…In particular, the proposed method allows the attribution of a unit to more than one cluster, which is often more realistic than assigning a unit to only one cluster in tourism. Third, image segmentation studies in tourism rely heavily on cluster analysis to understand tourists' perceptions of destinations [29][30][31] but the stability and reproducibility of the identified clusters remain questionable. By using BFCM-FD, we obtain clusters which are stable and reproducible.…”

Analysis of the impact of length of stay on the quality of service experience, satisfaction and loyalty

“…As for the length of stay, some recent studies compare shortstay tourists with longstay tourists (Neal et al 2007; Prayag 2012 and firsttime visitors with repeat visitors (Li et al 2008; Alegre et al 2011. However, to the best of our knowledge, this paper is the first one to analyse significant differences between sameday visitors whose trip does not include an overnight stay and overnight tourists who stay overnight, regarding their quality of service experience, satisfaction and destination loyalty.…”

Exploring Pull Factor Influences at Campgrounds by RV Association Members

“…Previous literature has identified pull factor influences of travel, including destination value (Kim et al, 2003), image (Prayag, 2012), kid-friendly destinations when traveling with children (Turley, 2001;Johns and Gyimothy, 2003;Brey and Lehto, 2008), landscaping, outdoor activities, and hassel-free environments (Frochot, 2005;Park and Yoon, 2009). Pull influences have also included beaches, weather, exotic food, culture, novelty (Uysal and Jurowski, 1994), lakes and historic sites (Horneman et al, (2002).…”