Skip to main content

Bagged Clustering and its application to tourism market segmentation.

D'Urso, P., De Giovanni, L., Disegna, M. and Massari, R., 2013. Bagged Clustering and its application to tourism market segmentation. Expert Systems with Applications, 40 (12), 4944 - 4956.

Full text available as:

2013ESWA_DUrso_Degiovanni_Disegna_Massari_PROOF.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


DOI: 10.1016/j.eswa.2013.03.005


Aim of the paper is to propose a segmentation technique based on the Bagged Clustering (BC) method. In the partitioning step of the BC method, B bootstrap samples with replacement are generated by drawing from the original sample.The fuzzy C-medoids Clustering (FCMdC) method is run on each bootstrap sam- ple, obtaining (B × C) medoids and the membership degrees of each unit to the different clusters.The sec- ond step consists in running a hierarchical clustering algorithm on the (B × C) medoids. The best partition of the medoids is obtained investigating properly the dendrogram.Then each unit is assigned to each cluster based on the membership degrees observed in the partitioning step.The effectiveness of the sug- gested procedure has been shown analyzing a suggestive tourism segmentation problem. Weanalyze two sample of tourists, each one attending adifferent cultural attraction, enlightening differences among clusters in socio-economic characteristics and in the motivational reasons behind visit behavior. © 2013 Elsevier Ltd. All rights reserved.

Item Type:Article
Uncontrolled Keywords:Bagged Clustering ; Dissimilarity measures for quantitative and ; Fuzzy C-medoids ; Normalized weighted Shannon entropy ; Qualitative data ; Tourism market segmentation
Group:Bournemouth University Business School
ID Code:23312
Deposited By: Symplectic RT2
Deposited On:22 Mar 2016 10:19
Last Modified:14 Mar 2022 13:55


Downloads per month over past year

More statistics for this item...
Repository Staff Only -