Fuzzy segmentation of postmodern tourists

D’Urso, Pierpaolo; Disegna, Marta; Massari, Riccardo; Osti, Linda

doi:10.1016/j.tourman.2016.03.018

Cited by 78 publications

(76 citation statements)

References 64 publications

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“…Half of the 'difference-seekers' and a little under half (47.2%) of the 'shoppers for cultural experience' visited the city mainly to experience a new culture while almost 56% of the 'reluctant shoppers' and more than 53% of the 'total shoppers' who classified themselves as 'pleasure tourists' decided to visit Istanbul for its historical and/or cultural sites. Our results resonate with previous findings by Andreu et al (2005), Carmichael, Smith (2004), D'Urso et al (2016 and Lopez-Guzman et al (2014) and are contrary to findings by Hu, Yu (2007).…”

Section: Differences Between Clusterssupporting

confidence: 86%

“…Next, using results from chi-square tests, the following tables report on the differences in geographical origin ( The results of our research show that, similar to other studies (Brida, et al, 2012;D'Urso, et al, 2016;D'Urso, et al, 2013;Littrell, et al, 2004, Mody, et al, 2014Tkaczynski, et al, 2009), tourists' country of origin is an important indicator for tourists' shopping typologies. Table 3 shows that while Europeans are the largest group in all five clusters (they represent 62.7% of all tourists in our survey), they form the majority only among 'shoppers for cultural experience', 'reluctant shoppers' and 'total shoppers'.…”

Section: Differences Between Clusterssupporting

confidence: 72%

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Tourist market segmentation by motivation to shop: A case study of Istanbul, Turkey

Egresi¹

2017

Geographica Pannonica

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Previous research has indicated that shopping could make up for a significant part of the tourist experience and could provide significant benefits to destinations by contributing to local retail revenue and by generating many jobs. In order to design better marketing strategies, destination managers must understand what attracts tourists to a destination and makes them shop while there. However, tourists represent a heterogeneous group and subgroups of individuals are motivated to visit a destination for a variety of reasons. The primary purpose of this study is to segment tourist shoppers visiting Istanbul according to their motivation to shop. Five distinctive groups of 'product-focused shoppers', 'shoppers for cultural experience', 'reluctant shoppers', 'difference seekers' and 'total shoppers' were found and compared by the geographical origin of the tourists, their socio-demographic characteristics, travel characteristics and behaviour, primary motivation for the trip, activity participation and shopping preferences and attitudes. The findings indicate that destination marketers must develop their strategies and marketing products to address the heterogeneity of motivations underlying tourist shopping.

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Section: Differences Between Clusterssupporting

confidence: 86%

Section: Differences Between Clusterssupporting

confidence: 72%

Tourist market segmentation by motivation to shop: A case study of Istanbul, Turkey

Egresi¹

2017

Geographica Pannonica

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“…Moreover, it is also often found in empirical studies based on psychographic factors (Kastenholz et al 1999;Frochot 2005;Sterl et al 2006;Molera & Albaladejo 2007;Park & Yoon 2009;Rid et al 2014;Konu & Kajala 2012;Smith et al 2014). There are other exploratory approaches used for grouping cases, such as neural network selforganizing maps (SOM) (Oja et al 2003) and fuzzy logic segmentation (D'Urso et al 2016), which may be promising and worth applying.…”

Section: Strengths and Weaknesses Of The Applied Methodsmentioning

confidence: 99%

“…Typologies based on crowding perception (Arnberger & Haider 2005) or type of activity (Burns & Graefe 2002) are also common in tourism literature. Modern solutions such as fuzzy segmentation are also found (D'Urso et al 2016). In theoretical studies, authors focus mainly on motivational factors or visitor attitudes (Przecławski 1996;Ankre 2005;Stankey 1973), while other well-known theoretical typologies are based on the degree of institutionalization of the tourist, e. g. drifter, explorer, individual mass and organized mass tourist types (Cohen 1979).…”

Section: Introductionmentioning

confidence: 99%

Visitor profiling for cable car mountain destinations as a basis for protected area management: a case study of the summer season in the Tatra Mountains at Kasprowy Wierch (Poland) and Skalnaté Pleso (Slovakia)

Hibner¹,

Taczanowska²,

Zięba³

et al. 2018

ecomont

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Protected areas play a crucial role in the conservation of vulnerable mountain ecosystems, but at the same time they may serve as tourist destinations and attract large numbers of visitors. Areas located in close proximity to cable cars belong to some of the most challenging sites for mountain protected area management. This study focuses on two cable car areas: Kasprowy Wierch (Tatra National Park, Poland) and Skalnaté Pleso (Tatra National Park, Slovakia). Both sites belong to the most heavilyused leisure destinations in the Tatra Mountains. The study focused on the summer, snow-free tourist peak-season, for which there is an ongoing discussion concerning the development of cable car services. In 2014 and 2015, on-site interviews were conducted in the two study areas (n = 3 304). In order to better understand visitors' needs and goals, visitor profiling using K-means clustering was performed. Four distinct segments based on visitor motivations were identified: nature oriented (32 %), family / friends & well-being oriented (23 %), sports oriented (14 %), and a mixed segment with multiple motivations (31 %). The results show that two tourist segments were not particularly interested in nature experience, although they visited protected areas. A significant relationship between motivational segments and trip characteristics was identified. The visitor segments defined can be used practically in the management of cable car destinations located within protected areas.

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“…Related to this, the fourth contribution of the study is methodological. A common practice used in the profiling phase of a fuzzy clustering analysis is to convert the final result into crisp information (each unit is associated with one cluster) by adopting a "defuzzification" procedure (D'Urso et al 2016) to easily understand the relationships between the clusters and the profiling variables.…”

Section: Introductionmentioning

confidence: 99%

Me, My Girls, and the Ideal Hotel: Segmenting Motivations of the Girlfriend Getaway Market Using Fuzzy C-Medoids for Fuzzy Data

Khoo‐Lattimore

Prayag

Disegna

2018

Journal of Travel Research

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Fuzzy segmentation of postmodern tourists

Cited by 78 publications

References 64 publications

Tourist market segmentation by motivation to shop: A case study of Istanbul, Turkey

Tourist market segmentation by motivation to shop: A case study of Istanbul, Turkey

Visitor profiling for cable car mountain destinations as a basis for protected area management: a case study of the summer season in the Tatra Mountains at Kasprowy Wierch (Poland) and Skalnaté Pleso (Slovakia)

Me, My Girls, and the Ideal Hotel: Segmenting Motivations of the Girlfriend Getaway Market Using Fuzzy C-Medoids for Fuzzy Data

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