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

• Introduces a novel segmentation method based on bagged and fuzzy clustering.
• Proposes how to adapt Bagged fuzzy clustering for fuzzy data.
• Segments the market of potential Chinese consumers to Western Europe.
• Four segments of perceived images are identified.
• Results have implications for the application of market segmentation algorithms in marketing.

Segmentation has several strategic and tactical implications in marketing products and services. Despite hard clustering methods having several weaknesses, they remain widely applied in marketing studies. Alternative segmentation methods such as fuzzy methods are rarely used to understand consumer behaviour. In this study, we propose a strategy of analysis, by combining the Bagged Clustering (BC) method and the fuzzy C-means clustering method for fuzzy data (FCM-FD), i.e., the Bagged fuzzy C-means clustering method for fuzzy data (BFCM-FD). The method inherits the advantages of stability and reproducibility from BC and the flexibility from FCM-FD. The method is applied on a sample of 328 Chinese consumers revealing the existence of four segments (Admirers, Enthusiasts, Moderates, and Apathetics) of the perceived images of Western Europe as a tourist destination. The results highlight the heterogeneity in Chinese consumers’ place preferences and implications for place marketing are offered.