Special Issue "Geo Data Science for Tourism"

Special Issue Editors

Dr. Andrea Marchetti
E-Mail Website
Guest Editor
Institute of Informatics and Telematics (CNR), Pisa, Italy
Interests: open data; data visualization; data science; web applications; cartographic mapping techniques
Dr. Angelica Lo Duca
E-Mail Website
Guest Editor
Institute of Informatics and Telematics (CNR), Pisa, Italy
Interests: data science; data collection; data analysis; web applications; tourism; cultural heritage

Special Issue Information

Dear Colleagues, 

The hospitality and tourism industries are considered as critical parts of the economy of a Country. Thanks to the availability of a huge quantity of geographical data, such industries can offer high-quality Web applications, which improve the attractiveness of tourism destinations as well as all the businesses related to tourism. In addition, the use of Web applications for tourism helps to understand tourists behavior, by managing, analyzing and visualizing huge quantities of geographical data, such as those contained in reviews about accommodations. However, Web applications applied to the tourism domain present several issues and challenges, such as their durability and copyright related to collected data. The use of open data for tourism (e.g. accommodations, restaurants, attractions, events, transportations) and open source maps to represent geographical data can be an answer to all these challenges. 

This Special Issue calls for research articles related to novel approaches to geographical data collection, analysis and visualization related to the design and implementation of Web applications in the tourism domain. Original contributions that report on real experiences and use cases in the usage of any kind of geo data in the tourism domain are also encouraged. 

While not excluding the possibility of presenting works on other topics regarding tourism, the specific topics of interest of this Special Issue are the following:

  1. Issues, challenges and solutions related to geographical data in the tourism domain
  2. Data Collection, Cleaning, Enrichment, Integration and Visualization of tourism geographical datasets
  3. Copyright issues related to the publication and use of collected geographical datasets of tourism entities
  4. Data Matching techniques for tourism entities based on geographical information (address, coordinates, geographical areas) for integrating two or more datasets
  5. Text Analysis of tourism entities reviews based on customer nationality
  6. Time Series analysis and forecasting related to tourism data of different geographical areas
  7. Machine Learning and Deep Learning Analysis of geographical datasets related to the tourism domain
  8. Web applications for tourism based on geographical maps
  9. Comparison among different open map services for tourism
  10. Analysis and Impact of the COVID-19 pandemic on tourism

Dr. Andrea Marchetti
Dr. Angelica Lo Duca
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Tourism
  • Geographical Data
  • Data Science
  • Data Collection
  • Data Analysis
  • Data Visualization
  • Web Applications
  • Open Data
  • Open Map Services

Published Papers (2 papers)

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Research

Article
Socioeconomic and Environmental Impacts on Regional Tourism across Chinese Cities: A Spatiotemporal Heterogeneous Perspective
ISPRS Int. J. Geo-Inf. 2021, 10(6), 410; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10060410 - 14 Jun 2021
Viewed by 327
Abstract
Understanding geospatial impacts of multi-sourced drivers on the tourism industry is of great significance for formulating tourism development policies tailored to regional-specific needs. To date, no research in China has explored the combined impacts of socioeconomic and environmental drivers on city-level tourism from [...] Read more.
Understanding geospatial impacts of multi-sourced drivers on the tourism industry is of great significance for formulating tourism development policies tailored to regional-specific needs. To date, no research in China has explored the combined impacts of socioeconomic and environmental drivers on city-level tourism from a spatiotemporal heterogeneous perspective. We collected the total tourism revenue indicator and 30 potential influencing factors from 343 cities across China during 2008–2017. Three mainstream regressions and an emerging local spatiotemporal regression named the Bayesian spatiotemporally varying coefficients (Bayesian STVC) model were constructed to investigate the global-scale stationary and local-scale spatiotemporal nonstationary relationships between city-level tourism and various vital drivers. The Bayesian STVC model achieved the best model performance. Globally, eight socioeconomic and environmental factors, average wage (coefficient: 0.47, 95% credible intervals: 0.43–0.51), employed population (−0.14, −0.17–−0.11), GDP per capita (0.47, 0.42–0.52), population density (0.21, 0.16–0.27), night-time light index (−0.01, −0.08–0.05), slope (0.10, 0.06–0.14), vegetation index (0.66, 0.63–0.70), and road network density (0.34, 0.29–0.38), were identified to have nonlinear effects on tourism. Temporally, the main drivers might have gradually changed from the local macro-economic level, population density, and natural environment conditions to the individual economic level over the last decade. Spatially, city-specific dynamic maps of tourism development and geographically clustered influencing maps for eight drivers were produced. In 2017, China formed four significant city-level tourism industry clusters (hot spots, 90% confidence), the locations of which coincide with China’s top four urban agglomerations. Our local spatiotemporal analysis framework for geographical tourism data is expected to provide insights into adjusting regional measures to local conditions and temporal variations in broader social and natural sciences. Full article
(This article belongs to the Special Issue Geo Data Science for Tourism)
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Article
Why Is Green Hotel Certification Unpopular in Taiwan? An Analytic Hierarchy Process (AHP) Approach
ISPRS Int. J. Geo-Inf. 2021, 10(4), 255; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040255 - 10 Apr 2021
Viewed by 397
Abstract
The main purpose of this study was to investigate the factors that discouraged Taiwan hoteliers from applying for green hotel certification. The analytic hierarchy process (AHP) method was used to perform a weighted analysis that comprehensively identified important hindering factors based on information [...] Read more.
The main purpose of this study was to investigate the factors that discouraged Taiwan hoteliers from applying for green hotel certification. The analytic hierarchy process (AHP) method was used to perform a weighted analysis that comprehensively identified important hindering factors based on information from hotel industry, government, academic, and consumer representatives. Overall, in order of importance, the five dimensions of hindering factors identified by these experts and scholars were hotel internal environment, consumers’ environmental protection awareness, environmental protection incentive policy, hotel laws and regulations policy, and hotel external environment. Among the 26 examined hindering factor indices, the three highest-weighted indices overall for hoteliers applying for green hotel certification were as follows: environmental protection is not the main consideration of consumers seeking accommodations, lack of support by investment owners (shareholders), and lack of relevant subsidy incentives. The major contribution of this study is that hoteliers can understand important hindering factors associated with applying for green hotel certification; therefore, strategies that can encourage or enhance the green certification of hotels can be proposed to improve corporate image in the hotel industry, implement social responsibility in this industry, and obtain consumers’ approval of and accommodation-willingness for green hotels. Full article
(This article belongs to the Special Issue Geo Data Science for Tourism)
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