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

D'Urso, P., Disegna, M., Massari, R. and Prayag, G., 2014. Bagged fuzzy clustering for fuzzy data: An application to a tourism market. Knowledge-Based Systems, 73, 335 - 346.

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DPDM_KBS_pre-print version.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


DOI: 10.1016/j.knosys.2014.10.015


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.

Item Type:Article
Uncontrolled Keywords:Bagged clustering; Chinese consumers; Fuzzy C-means; Fuzzy data; Likert-type scales
Group:Bournemouth University Business School
ID Code:23278
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:16 Mar 2016 14:10
Last Modified:15 Aug 2021 09:14


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