Visitor mobility in the city and the effects of travel preparation

Bauder, Michael; Freytag, Tim

doi:10.1080/14616688.2015.1053971

Cited by 65 publications

(52 citation statements)

References 34 publications

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“…There is a substantial need to understand the tourists movement behavior with respect to their destination choices since it has a deep impact on tourism development process and marketing strategy. Many of the previous studies have been conducted in investigating tourist behavior with respect to destination by primarily emphasizing on spatial and temporal patterns of tourist [7], [14], [15]. There has also been an evaluation of most popular tourist trends and choices [16]- [18].…”

Section: Literature Reviewmentioning

confidence: 99%

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A Study of Tourist Sequential Activity Pattern through Location Based Social Network (LBSN)

Talpur

Zhang

2018

2018 International Conference on Orange Technologies (ICOT)

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Sequential Pattern Mining (SPM) is an important component in establishing patterns and mining trends of certain activities. In the past, this technique has been used in various fields such as consumer-watch, making future predictions and analyzing and interpreting large datasets for deeply embedded rules and associations. The qualitative details of Singapore tourists' foursquare check-ins, represented in a tabular form, is an example of a sequential database. Therefore, the Pattern-Growth method which uses Prefix-Span Algorithm is used in this study to obtain the Tourist Sequential Activity Patterns. Insights into tourist movement and activity patterns is deemed beneficial for the tourism sector in many ways, such as designing better travel packages for tourists, maximizing the tourist activity participation and meeting the tourist demands. This research proposes to adopt mobile social media data for effective capturing of tourist activity information in Singapore and utilizes advanced data mining techniques for extracting valuable insights into tourist behavior. The proposed methods and findings of the study have the potential to support tourism managers and policy makers in making better decisions in tourism destination management.

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Section: Literature Reviewmentioning

confidence: 99%

“…Thus, the tourist activity patterns will unfold over time. It is evident from previous research that tourist behavior can be volatile and easily affected by a series of inter-twined factors [7]- [10]. Thus, we attempt to find some regularity in the extracted patterns.…”

Section: Introductionmentioning

confidence: 96%

A Study of Tourist Sequential Activity Pattern through Location Based Social Network (LBSN)

Talpur

Zhang

2018

2018 International Conference on Orange Technologies (ICOT)

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“…Research on visitor mobility by scholars and urban planners has increased in recent years [6][7][8][9][10][11]. The main interest of such research involves visitors' movement patterns and the factors influencing them.…”

Section: Introductionmentioning

confidence: 99%

Visitor Mobility and Spatial Structure in a Local Urban Tourism Destination: GPS Tracking and Network analysis

2019

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Visitor mobility is an important element for facilitating sustainable local economics and management in urban tourism destinations. Research on visitor mobility often focuses on the patterns and structures of spatial visitor behavior and the factors that influence them. This study examines the relationship between visitor mobility and urban spatial structures through an exploratory analysis of visitors’ movements and characteristics, which were collected from surveys with global positional system (GPS) tracking technologies and questionnaires. The Ueno district, one of the most popular tourism destinations in Tokyo, Japan, was selected as the study area. For local stakeholders, the low accessibility levels between this district’s park zone and downtown zone have become a major destination management issue. We compared visitor movements and flow networks in various places from different major trip origins (railway stations) by using several analysis techniques (GPS log distribution, spatial movement sequences, and network analysis), and examined physical and human factors that caused the different mobility patterns. The results demonstrated that physical factors, including major transport hubs (railway stations), topography, commercial accumulation, and POI distribution, affected intra-destination visitor behavior, and segmented visitor markets into different main zones. Such findings could inform future destination management policies and planning in local urban tourism destinations.

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“…Tourist experiences, as complex phenomena, can be seen as "an orchestrated model of interacting elements" (Pearce & Wu, 2014, p. 220). Identifying and understanding visitors' time-space activity patterns is central to efficient and successful destination management (Bauder & Freytag, 2015). Urban tourism, like any other kind, implies the consumption of the experiential characteristics (e.g.…”

Section: Urban Tourists' Evaluation Of Intra-destination Experiencementioning

confidence: 99%

It’s so hot: predicting climate change effects on urban tourists’ time–space experience

Caldeira

Kastenholz

2018

Journal of Sustainable Tourism

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Progressive changes in mean annual temperatures are arguably the strongest evidence of ongoing climate change. In destinations with a Mediterranean climate, in contrast to the colder months, during summer, rising air temperatures are believed to inhibit tourist movements and activities, and consequently affect tourists' evaluation of and satisfaction with their experiences. To the best of our knowledge, no previous study has investigated the potential impact of climate change on tourists' time-space activity using actual behavioural tracking-based information. Data collected via GPS technology and a post-visit survey of tourists (n = 404) visiting Lisbon during the summer were analysed via structural equation modelling (PLS-SEM). The results report empirical evidence of the present impact of (summer) weather on urban tourists' time-space activity and on their intra-destination experience evaluation. Specifically, maximum air temperature is found to have a significant negative effect on overall satisfaction, while the meteorological conditions of the entire day reveal a significant impact on tourists' activities and movements. The results are particularly useful for the sustainable adaptive management of urban attractions and destinations that are especially vulnerable to climate change, as well as in managing its adverse impact on tourists' experiences.

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Visitor mobility in the city and the effects of travel preparation

Cited by 65 publications

References 34 publications

A Study of Tourist Sequential Activity Pattern through Location Based Social Network (LBSN)

A Study of Tourist Sequential Activity Pattern through Location Based Social Network (LBSN)

Visitor Mobility and Spatial Structure in a Local Urban Tourism Destination: GPS Tracking and Network analysis

It’s so hot: predicting climate change effects on urban tourists’ time–space experience

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