Segmenting Markets by Bagged Clustering

Segmenting Markets by Bagged Clustering: Young Chinese Travelers to Western Europe

Market segmentation is ubiquitous in marketing. Hierarchical and non-hierarchical methods are the most popular for segmenting tourism markets. These methods are not without much controversy. In this study, we use bagged clustering on the push and pull factors of Western Europe to segment potential young Chinese travelers. Bagged clustering overcomes some of the limitations of hierarchical and n...

Getting More Out of Binary Data: Segmenting Markets by Bagged Clustering

There are numerous ways of segmenting a market based on consumer survey data. We introduce bagged clustering as a new exploratory approach in the field of market segmentation research which offers a few major advantages over both hierarchical and partitioning algorithms, especially when dealing with large binary data sets: In the hierarchical step of the procedure the researcher is enabled to i...

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

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 (B...

Algorithms for Segmenting Time Series

As with most computer science problems, representation of the data is the key to ecient and eective solutions. Piecewise linear representation has been used for the representation of the data. This representation has been used by various researchers to support clustering, classication, indexing and association rule mining of time series data. A variety of algorithms have been proposed to obtain...

Bagged Clustering