Market Segmentation using Bagged Fuzzy C–Means (BFCM): Destination Image of Western Europe among Chinese Travellers
AbstractMarket segmentation offers several strategic and tactical advantages to marketers. Hierarchical and non-hierarchical segmentation methods have several weaknesses but remain widely applied in tourism studies. Alternative segmentation methods such as fuzzy, mixture models, and Bagged Clustering are relatively less popular. In this study, we propose a novel method, the Bagged Fuzzy C–Means (BFCM) algorithm, for segmenting tourism markets. A sample of 328 Chinese travellers revealed the existence of four segments (Admirers, Enthusiasts, Moderates, and Apathetics) of perceived images for Western Europe. BFCM is able to identify stable clusters, inheriting this feature from Bagged clustering method. Furthermore, fuzzy allocation allows to idetify travellers whose profiles match with more than one cluster. Destination marketers need to proactively manage the image of Western Europe to attract the increasingly discerning Chinese traveller. Information provision and on-line presence strategies will be critical for destination success.
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Bibliographic InfoPaper provided by School of Economics and Management at the Free University of Bozen in its series BEMPS - Bozen Economics & Management Paper Series with number BEMPS13.
Length: 50 pages
Date of creation: Oct 2013
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Bagged Clustering; Fuzzy C–means; Chinese travellers; Tourism market segmentation; Western Europe; Likert–type scales; fuzzy coding.;
Find related papers by JEL classification:
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