Traveler Geographic Origin and Market Segmentation: The Multi Trips Destination Case

Flognfeldt, Thor

doi:10.1300/j073v08n01_07

Cited by 69 publications

(38 citation statements)

References 3 publications

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“…Therefore, the study, determination and analysis of such patterns help the process of defining tourist types. Consistent use of patterns described in previous research (Flognfeldt, 1999;Lew & McKercher, 2006;Lue, Crompton & Fesenmaier, 1993;Mings & McHugh, 1992;Oppermann, 1995) is not always possible in every destination area in the lack of accurate definitions. Moreover, visually similar but not completely similar patterns regarding the aims of the research have to be separated.…”

Section: Introductionmentioning

confidence: 66%

“…Classifying linear models determined by previous research (Flognfeldt 1999;Lue, Crompton & Fesenmaier, 1993;Mings & McHugh, 1992;Oppermann, 1995) Lew and McKercher (2006) identified three different types lasting from points to points ("Type P1 Pont-to-Point Patterns"), two circular ones ("Type P2 Circular Patterns") and one complex pattern ("Type P3 Complex Patterns") that can be random or radial circular movements ("Random Exploratory (P3a) or Radiating Hub (P3b)"). This is one of the most frequently referred classification (Lew & McKercher, 2006) that gave the basis for my research as well.…”

Section: Figure 1 -Dimensions Of Databasementioning

confidence: 99%

“…For example, the pattern of travels into a given destination was studied by Mings and McHugh (1992) while Lue, Crompton and Fesenmaier (1993) described travels stopping in several destinations. Flognfeldt (1999Flognfeldt ( , 2005 analysed different patterns between the place of residence and the destination. McKercher and Lau (2008) identified patterns in urban destinations using a GIS software.…”

Section: Figure 1 -Dimensions Of Databasementioning

confidence: 99%

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Determination of tourist flow patterns in a low mountain study area

Benkhard

2018

Tour Manage Stud

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Understanding the movement of visitors contributes to appropriate management plans for visitor destinations. Determination of this movement is composed of not only the identification of the starting and end points together with the sequence of stops but the characterisation of the route pattern as well. The type of this pattern depends on the human apart from outer physical parameters and the available time thus it has a relationship with the behaviour and type of the tourist. Understanding and making use of these are important measures for organisations managing natural areas. Observation of visitors in natural areas is not possible in every environment while reducing the tread of certain popular sites can be made only with the help of such knowledge. This explains that literature describing different patterns analyse interdestination relationships. In this paper the identification of the movement pattern of hikers in a mountainous study area is presented. Visitor flow analysis of a study area in Hungary (180 km 2 area of Central Börzsöny in Duna-Ipoly National Park) was performed on the basis of a questionnaire survey carried out with the help of volunteers. Based on the analysis of the obtained data the accurate description of the movement of both individual hikers and groups became possible. Mathematics based definition of hiking routes completed in mountainous areas is new to the available data in the literature. Patterns of one day routes were classified into 6 types and two types of hiking routes requiring several days were also identified. Different route types were observed at the different entrances of the destination. Such information helps the identification of visitor types at the starting points and the design of appropriate visitor management measures.Keywords: Visitor flow, tourist movement pattern, behaviour, spatial movement, itinerary model. ResumoCompreender o movimento dos visitantes contribui para desenvolver planos de gestão apropriados para os destinos. A determinação desse movimento é composta não apenas pela identificação dos pontos iniciais e finais, juntamente com a sequência de paragens, mas também pela caracterização do padrão de rota. O tipo desse padrão depende, do fator humano, além dos parâmetros físicos externos e do tempo disponível, tendo consequentemente uma relação com o comportamento e o tipo do turista. Compreender e fazer uso desses padrões são medidas importantes para as organizações que gerenciam áreas naturais. A observação de visitantes em áreas naturais não é possível em todos os ambientes, ao passo que a gestão de certos percursos pode ser feita apenas com a ajuda de tal conhecimento. Isso explica que a literatura que descreve diferentes padrões, analisa relacionamentos entre destinos. Neste trabalho é apresentada a identificação do padrão de movimento dos caminhantes numa área de estudo montanhosa. A análise do fluxo de visitantes de uma área de estudo na Hungria (área de 180 km2 do Börzsöny Central no Parque Nacional Duna-Ipoly) foi realizada com base num...

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Section: Introductionmentioning

confidence: 66%

Section: Figure 1 -Dimensions Of Databasementioning

confidence: 99%

Section: Figure 1 -Dimensions Of Databasementioning

confidence: 99%

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Determination of tourist flow patterns in a low mountain study area

Benkhard

2018

Tour Manage Stud

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“…A variety of studies have attempted to map the movements of tourists between destinations or between their home and destination areas (Mings and McHugh, 1992;Lue et al, 1993;Oppermann, 1995;Flognfeldt, 1999;Sriram et al, 2002). Little research has been conducted, though, examining the movements of tourists within a destination area and none has explicitly attempted to understand, map and model these movement patterns.…”

Section: Introductionmentioning

confidence: 99%

“…Likewise, Lew (1987) compared attractions in Singapore that different nationality-based segments were interested in, versus where they actually went to identify under and over supply and demand patterns. Cultural distance may also affect behavior, with tourists from culturally proximate source markets seeing different attractions and traveling to different areas within a destination than those from culturally distance source markets (Lew, 1987;Flognfeldt, 1999).…”

Section: Introductionmentioning

confidence: 99%