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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DOI: 10.1016/j.knosys.2014.10.015
Abstract
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 |
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ISSN: | 0950-7051 |
Uncontrolled Keywords: | Bagged clustering; Chinese consumers; Fuzzy C-means; Fuzzy data; Likert-type scales |
Group: | Bournemouth University Business School |
ID Code: | 23278 |
Deposited By: | Symplectic RT2 |
Deposited On: | 16 Mar 2016 14:10 |
Last Modified: | 14 Mar 2022 13:55 |
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