Market segmentation

Mazany, R. Leigh; Barrett, L; Apostle, Richard

doi:10.1016/0308-597x(87)90037-6

Cited by 9 publications

(7 citation statements)

References 3 publications

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“…Market segmentation identifies groups of tourists that react in a similar way to marketing actions (Bieger and Laesser, 2002;Cha et al, 1995;Dolnicar and Mazanec, 2000;Frochot, 2005;Tkaczynsky et al, 2009). In general, there can be two ways of classifying tourists: (i) a priori segmentation: this generates a classification based on a particular criteria that is known beforehand; and (ii) post hoc segmentation or a posteriori: this identifies heterogeneous segments of tourists based on market information about target groups (Dolnicar, 2004b;Mazanec, 2000) and by utilizing statistical techniques of inference, for example, cluster segmentation. The latter method collects information from tourists in order to predict their behaviour, and the results can be influenced by the decisions taken in data collection and analysis (Dolnicar and Grün, 2008).…”

Section: Market Segmentation In Tourismmentioning

confidence: 99%

Market segmentation, activities and environmental behaviour in rural tourism

et al. 2015

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Rural tourism has developed in recent decades with an increase in the activities available to tourists. In this article, the authors apply a cluster analysis for the segmentation of rural tourism in La Palma, Canary Islands. They consider the level of environmental attitudes of tourists as a variable explaining market segmentation. The results show that there is a large heterogeneity of market segments and that the traditional activity of agro-tourism represents a small share of the total market. The segments with a greater economic impact and producing greater tourist satisfaction are those in which tourists also exhibit higher levels of environmental behaviour. Thus, rural tourist destinations can improve their economic performance by focusing on those segments attracting tourists with higher environmental concern and by adopting policies that enhance the environmental profile of the segments.

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Section: Market Segmentation In Tourismmentioning

confidence: 99%

Market segmentation, activities and environmental behaviour in rural tourism

et al. 2015

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“…Response-based approaches, on the other hand, form groups by identifying patterns of responses, given by the customers. Other terms used to describe the responsebased approach include a posteriori (Mazanec, 2000), data-driven (Dolnicar, 2002), and post hoc (Wedel and Kamakura, 2001). Numerous publications list and evaluate these approaches in a comprehensive manner (Arabie et al, 1996;Dickinson, 1990;Punj and Stewart, 1983;Baumann, 2000).…”

Section: Introductionmentioning

confidence: 99%

Segmenting Markets by Bagged Clustering

Dolničar¹,

Leisch²

2004

Australasian Marketing Journal

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We introduce bagged clustering as a new approach in the field of post hoc market segmentation research and illustrate the managerial advantages over both hierarchical and partitioning algorithms, especially with large binary data sets. The most important improvements are enhanced stability and interpretability of segments based on binary data. One of the main goals of the procedure is to complement more traditional techniques as an exploratory segment analysis tool. The merits of the approach are illustrated using a tourism marketing application. Segmenting Markets by Bagged ClusteringWe introduce bagged clustering as a new approach in the field of post hoc market segmentation research and illustrate the managerial advantages over both hierarchical and partitioning algorithms, especially with large binary data sets. The most important improvements are enhanced stability and interpretability of segments based on binary data. One of the main goals of the procedure is to complement more traditional techniques as an exploratory segment analysis tool. The merits of the approach are illustrated using a tourism marketing application.

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“…In an a priori segmentation, criteria are defined before the procedure (as they are well-known or come from a well-defined classification scheme). On the other hand, the segmentation post hoc is based on market research survey and is derived on variables that turn out the most efficient in determination of homogeneous groups (Green et al 1977;Mazanec 2000). Usually, once the segmentation based on chosen variables is done, the defined groups are additionally profiled, i.e.…”

Section: Benefit Segmentationmentioning

confidence: 99%

Benefit segmentation in the tourist accommodation market based on eWOM attribute ratings

Nessel

Kościółek

Wszendybył-Skulska

et al. 2021

Inf Technol Tourism

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Given the increasing importance of electronic word-of-mouth (eWOM) in the global tourism market, the purpose of the study was to estimate weights customers assign to main attributes of tourist accommodations embodied in easily observed eWOM numerical ratings and subsequently to determine segments of customers with homogenous preferences. To this goal, the preferences tourists attach to price and seven other accommodation attributes rated by Internet users on Booking.com were revealed with the analytical hierarchy process (AHP). Next, a two-stage clustering procedure based on these preferences was undertaken followed by profiling of the clusters in terms of their socio-demographics and travel characteristics. The results show that even if the ranking of the attributes is roughly the same for all the segments (with cleanliness, value for money, and location always in top four), all eight attributes effectively segment tourists into three clusters: “quality-seekers” (45% of the market), “bargain-seekers” (35%), and “cleanliness-seekers” (20%). The segments differ in terms of tourists’ income and expenditures, type of accommodation, actual payer for accommodation, and trip purpose. In contrast, socio-demographics, and most tourists stay variables are alike across the segments. The proposed method of benefit segmentation provides a new perspective for an exploitation of eWOM data by accommodation providers in their marketing strategy.

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Market segmentation

Cited by 9 publications

References 3 publications

Market segmentation, activities and environmental behaviour in rural tourism

Market segmentation, activities and environmental behaviour in rural tourism

Segmenting Markets by Bagged Clustering

Benefit segmentation in the tourist accommodation market based on eWOM attribute ratings

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