A Tourist Segmentation Based on Motivation, Satisfaction and Prior Knowledge with a Socio-Economic Profiling: A Clustering Approach with Mixed Information

D’Urso, Pierpaolo; Giovanni, Livia De; Disegna, Marta; Massari, Riccardo; Vitale, Vincenzina

doi:10.1007/s11205-020-02537-y

Cited by 16 publications

(12 citation statements)

References 90 publications

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“…The majority of market segmentation studies have used agglomerative clustering technique, especially using Ward’s method. Although there are many ways to define distance metrics, the most popular one which is most commonly used both in literature and practice is the Euclidean distance (Arunachalam and Kumar, 2018), including in tourism studies (D’Urso, 2021). Ward’s clustering has also traditionally dominated data-driven segmentation studies in tourism and is still popular, although other approaches have also emerged (Dolnicar, 2020; D’Urso et al , 2021).…”

Section: Methodsmentioning

confidence: 99%

The relative importance of culture in urban tourism: implications for segmentation

Smith

Pinke-Sziva

Berezvai

2023

CBTH

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Purpose This paper aims to contribute to urban tourism segmentation studies by examining the role of culture as a motivation for city visits, different preferences for activities and the demographic factors that influence activity choices. This study also compares the memorability of the trip across the segments identified based on their undertaken activities. Design/methodology/approach This paper draws on questionnaire data that was collected from 614 tourists in Budapest, Hungary. Tourist segmentation was based on a two-step procedure: principal component analysis and Hierarchical Cluster Analysis. Multinomial logistic regression was applied to reveal the effect of different demographic and travel-related characteristics on the segments. Findings The research revealed that cultural activities are still the most important motivation for urban tourists and that cultural tourists constitute the biggest segment (43%). They show a preference for heritage sites, museums and galleries rather than performing arts and festivals. Multinomial logistic regression showed that party tourists can be differentiated from cultural tourists and city break tourists predominantly by age and travel status. Older age groups and women are more likely to be interested in heritage sites, museums and galleries. Party tourists found their experience significantly more memorable than any other group and were much more likely to re-visit and recommend. Research limitations/implications Overall, this study provides useful information for destination management organisations and city agencies about which activities to promote and how to segment and potentially target tourists. This study did not include lifestyle and personality factors, secondary and complementary attractions or cultural proximity and distance. Originality/value There have been relatively few recent studies on urban cultural tourism segmentation, especially in whole destinations rather than at individual attractions, it was therefore considered timely to re-visit this area of research. This paper reinforces the importance of segmentation studies in tourism and analyses the changing motivations and activity preferences of urban cultural tourists over time.

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Section: Methodsmentioning

confidence: 99%

The relative importance of culture in urban tourism: implications for segmentation

Smith

Pinke-Sziva

Berezvai

2023

CBTH

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“…Cluster analysis has emerged as the dominant analytic approach for grouping tourists (Dolnicar, 2020; D'Urso et al , 2021), though other techniques have been adopted, among which are predictive (decision) trees – the classification approach used in this study. Predictive trees are largely used when there is one dependent variable that the researcher is attempting to predict.…”

Section: Literature Reviewmentioning

confidence: 99%

Segmenting tourists by length of stay using regression tree models

Jackman

Naitram

2021

JHTI

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PurposeThis study analyses how the socio-demographic profile of the tourist, trip-related characteristics, distance, and economic conditions in the source country affect pleasure tourists' length of stay behaviours in Barbados.Design/methodology/approachThe study uses “biggish” data (over 3.6 million observations), parametric models (OLS) and statistical learning models (regression trees) to develop a length of stay decision rule to segment pleasure tourists' length of stay. Our sample period is January 2004 to March 2013.FindingsThe analysis revealed a great deal of heterogeneity in the impact of the predictors across segments, which would be typically hidden from simple parametric approaches often used to model length of stay (such as OLS).Practical implicationsThe main implication is that conventional models of length of stay should be complemented with segmentation analyses to shed some light on the heterogeneous length of stay behaviours of specific market segments.Originality/valueMany studies on small tourism-specialising states focus on modelling aggregate arrivals. By modelling micro-data for Barbados, we provide insights on this aspect of tourism demand for small states. Second, very few studies use classification tools to analyse length of stay. The study contributes to the literature through its methodological approach.

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“…The findings of the cluster analysis performed in the study suggest that the identified markets can be replicated to manage the destination sustainably. On the other hand, D'Urso et al [13] reviewed the evolution of market segmentation with cluster analysis adoption. The study highlighted the importance of performing a cluster analysis using mixed data as segmentation variables to discover groups of homogeneous units.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For instance, clustering visitors according to preference attributes to determine their preference. D'Urso et al [13] reported that a non-overlapping clustering algorithm (mainly using Ward's method) has been adopted in many tourisms related research [15,16] to determine the number of clusters. It has been demonstrated that the result of Ward's clustering for the k-mean cluster analysis in tourism works well only when the true number of clusters is known [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Spatio-Temporal Clustering of Sarawak Malaysia Total Protected Area Visitors

et al. 2021

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Based on data of visitors to national parks, nature reserves and wildlife sanctuaries in Sarawak, this study’s objective is to use the spatial and temporal analysis to describe the underlying trend and temporal pattern of local and foreign visitors and ultimately infer the temporal distribution of visitors to 18 different TPAs. The second aim of the study is to cluster the visitors according to the location of TPAs using Wards hierarchical clustering method. By comparing average monthly visitors’ count, we observed that the average number of monthly visitors significantly reflects the distribution concentration of visitors based on the spatial map. Findings indicate that the monthly distributions of local and foreign visitors differ according to different TPAs. The spatial and temporal analysis found that local visitors’ arrival is high at the end of the year while foreign visitors showed significant arrival during the months of July, August and September. The Wards minimum variance method was able to cluster TPAs local and foreign visitors into very high, high, medium and low visitor area. This study provides additional information that could contribute to identifying the periods of highest visitor pressure, design measures to manage the concentration of visitors and improve the overall visitors’ experience. The findings of the study are also important to respective local authorities in providing information for planning and monitoring tourism in TPAs. Consecutively, this will ensure sustainability of TPAs resources while protecting their biodiversity.

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A Tourist Segmentation Based on Motivation, Satisfaction and Prior Knowledge with a Socio-Economic Profiling: A Clustering Approach with Mixed Information

Cited by 16 publications

References 90 publications

The relative importance of culture in urban tourism: implications for segmentation

The relative importance of culture in urban tourism: implications for segmentation

Segmenting tourists by length of stay using regression tree models

Spatio-Temporal Clustering of Sarawak Malaysia Total Protected Area Visitors

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