This dataset presents statistics about the businesses which are involved with tourism in specific Local Government Areas (LGA) around Australia. The LGAs covered in the data are a subset of the LGA boundaries classified in the 2018 Australian Statistical Geography Standard (ASGS). The data represents information about the number of businesses involved in tourism by the number of employees they have employed. The data was sourced for the year 2018. Tourism Research Australia (TRA) first developed Local Government Area tourism profiles in 2007 to assist industry and Government decision making and to identify and support investment opportunities, particularly in regional Australia. The latest profiles provide an update for over 200 Local Government Areas. Data are drawn from TRA's International Visitor Survey (IVS) and National Visitor Survey (NVS), along with demographic and business data from the Australian Bureau of Statistics (ABS). Profiles were only prepared for Local Government Areas with adequate IVS and NVS sample to present robust results. For more information please visit TRA. Please note: AURIN has spatially enabled the original data.

Additional information reported in lieu of inclusion in the 2018-2019 DITID Annual Report. Read the complete report here: https://www.publications.qld.gov.au/dataset/2018-2019-annual-report-departmen…Show full descriptionAdditional information reported in lieu of inclusion in the 2018-2019 DITID Annual Report. Read the complete report here: https://www.publications.qld.gov.au/dataset/2018-2019-annual-report-department-of-innovation-and-tourism-industry-development

Context

This dataset contains countries against years containing incoming international tourists to countries. This dataset i used to understand effect of cross-country travel on spread of COVID-19.

Content

International inbound tourists (overnight visitors) are the number of tourists who travel to a country other than that in which they have their usual residence, but outside their usual environment, for a period not exceeding 12 months and whose main purpose in visiting is other than an activity remunerated from within the country visited.

Acknowledgements

https://www.e-unwto.org/doi/suppl/10.5555/unwtotfb0156250119952018202001 https://data.worldbank.org/indicator/ST.INT.ARVL

Gap between demand and supply in Tourism sector

Tourism Revenues in Egypt increased to 14.40 USD Billion in 2024 from 13.60 USD Billion in 2023. This dataset provides - Egypt Tourism Revenues- actual values, historical data, forecast, chart, statistics, economic calendar and news.

The underlying figures and data from the Annual Population Survey three-year-pooled dataset (2016 to 2018) and the ONS Longitudinal Study for the publication 'Migrant labour force within the tourism industry: August 2019'

This dataset presents statistics about the top international markets for tourism to specific Local Government Areas (LGA) around Australia. The LGAs covered in the data are a subset of the LGA boundaries classified in the 2018 Australian Statistical Geography Standard (ASGS). The data presents the top three origin countries which produce the highest number of international tourism visitors to the specified LGA. Data relating to the number of visitors and nights stayed by these visitors are provided for each of the three origin countries. The data values are representative of a yearly average based on the four years of: 2015, 2016, 2017 and 2018. Tourism Research Australia (TRA) first developed Local Government Area tourism profiles in 2007 to assist industry and Government decision making and to identify and support investment opportunities, particularly in regional Australia. The latest profiles provide an update for over 200 Local Government Areas. Data are drawn from TRA's International Visitor Survey (IVS) and National Visitor Survey (NVS), along with demographic and business data from the Australian Bureau of Statistics (ABS). Profiles were only prepared for Local Government Areas with adequate IVS and NVS sample to present robust results. Further, data are averaged over four years, which minimises the impact of variability in estimates from year to year, and provides for more robust volume estimates. For more information please visit TRA. Please note: AURIN has spatially enabled the original data.

This dataset presents key performance metrics regarding tourism to specific Local Government Areas (LGA) around Australia. The LGAs covered in the data are a subset of the LGA boundaries classified in the 2018 Australian Statistical Geography Standard (ASGS). The data presents metrics for visits, spending and length of stay to the specified LGAs by their location of origin and visit duration. The data values are representative of a yearly average based on the four years of: 2015, 2016, 2017 and 2018. Tourism Research Australia (TRA) first developed Local Government Area tourism profiles in 2007 to assist industry and Government decision making and to identify and support investment opportunities, particularly in regional Australia. The latest profiles provide an update for over 200 Local Government Areas. Data are drawn from TRA's International Visitor Survey (IVS) and National Visitor Survey (NVS), along with demographic and business data from the Australian Bureau of Statistics (ABS). Profiles were only prepared for Local Government Areas with adequate IVS and NVS sample to present robust results. Further, data are averaged over four years, which minimises the impact of variability in estimates from year to year, and provides for more robust volume estimates. For more information please visit TRA. Please note: AURIN has spatially enabled the original data.

Tourism Revenues in Sri Lanka increased to 169.50 USD Million in June from 164.10 USD Million in May of 2025. This dataset provides - Sri Lanka Tourism Revenues- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Overseas travel undertaken by Gold Coast 2018 Commonwealth Games Corporation listed by financial year.

Monthly tourist movements (arrivals and presences) in 2018 divided by the territories of the ATL (Local Tourist Agencies) with details for Market (Italy- Abroad) and Sector (Hotel and Extra-hotel).

Dataset

This dataset was created by mila kimna

Contents

Confidence intervals for International Passenger Survey (IPS) quarterly data.

The data presents year, nationality, and region wise distribution of people by purpose of visit. The purpose of visit includes business and professional, indian diaspora, leisure holiday and recreation, medical, student, etc. It should be noted that the categorisation used in the report has undergone changes over the years. Data for the year 2009, 2014, and 2015 is unavailable. With respect to countries covered, the

Note: 1) key changes and exclusions over the years is as follows: 2) 2003-2006 & 2013-2015: Hungary was not included in the report. 3) 2003-2006: Kazakhstan, Russian Federation, and Ukraine were categorized under the Commonwealth of Independent States (CIS). 4) 2003-2005: Argentina was not part of the dataset. 5) 2003-2008: Sudan, Iraq, and Vietnam were omitted. 6) 2007 & 2008: The Czech Republic was missing from the dataset. 7) 2006-2018: The "Others" field for the North American region was not included in the dataset. 8) From 2021 onwards: India has not formally recognized the Republic of China Taiwan as a sovereign country, and it was excluded from the dataset.

Overtourism entered the popular lexicon in 2018. Two years later, COVID-19 brought international travel to a screeching halt. Suddenly, undertourism was an issue for communities that had grown economically dependent upon the tourism industry. This shift signaled that the term overtourism was a portmanteau for a suite of risks from tourism – economic dependence, crowding, resource depletion, overburdened infrastructure, loss of local autonomy, rising xenophobia, high rents, noise pollution. Even as the crisis of overtourism reemerges, there are no defined analytic categories that measure risks from (over)tourism within and across communities. This paper offers a model for the creation of a Global (over)Tourism Index that measures risks from tourism to community well-being in multiple dimensions and at multiple scales. We posit that the indexing of tourism risk will generate questions that bring relevant stakeholders together to discuss tools and strategies for risk mitigation with more urgency than current discussions focused on sustainability.

Content

Land prices of the City of Buenos Aires from the period 2014-2018.

Acknowledgements

This dataset was built using open data from Buenos Aires Data program.

https://data.buenosaires.gob.ar/dataset/terrenos-valor-oferta

License

Open Data Commons Open Database License 1.0 (ODbL).

This dataset is a compilation and synthesis of secondary data in South Florida (Martin, Palm Beach, Broward, Miami-Dade, and Monroe Counties) corresponding to the following topics: Human population changes near coral reefs, Economic impact of coral reef fishing to jurisdiction, Economic impact of dive/snorkel tourism to jurisdiction, Community well-being, Physical infrastructure, and Governance. Data are collected from a variety of publicly available sources to supplement primary data collected through resident surveys. These secondary data are collected to address topics outside the scope of NCRMP resident surveys, and are collected on an annual basis throughout the US coral reef jurisdictions. The primary data that were collected as part of this study in Florida are available in NCEI Accession 0161541.

This article describes a dataset of user-generated content (UGC) extracted from Tripadvisor, encompassing 5,043 tourist reviews from ten African destinations between August 2018 and August 2023. The data was systematically scraped using Tripadvisor’s scraping operator, ensuring accuracy and relevance. Preprocessing techniques were applied to clean and refine the data while preserving user sentiments and feedback. The data includes structured fields such as destination names, timestamps, and review text. This dataset is valuable for tourism researchers, policymakers, and industry stakeholders seeking insights into destination popularity, visitor experiences, and service quality. It supports trend analysis, predictive modeling, and comparative studies of regional tourism patterns. The structured format allows integration with other datasets for advanced tourism analytics. Through a longitudinal view of tourist sentiments, this dataset offers a valuable resource for understanding evolving travel behaviors and optimizing destination management strategies in Africa and beyond.

The tourism sector GDP share in Saudi Arabia was forecast to continuously increase between 2023 and 2028 by in total 1.9 percentage points. The share is estimated to amount to 9.4 percent in 2028. While the share was forecast to increase significant in the next years, the increase will slow down in the future.Depited is the economic contribution of the tourism sector in relation to the gross domestic product of the country or region at hand.The forecast has been adjusted for the expected impact of COVID-19.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).Find more key insights for the tourism sector GDP share in countries like Lebanon and Jordan.

The international tourism expenditure in Israel was forecast to continuously increase between 2024 and 2029 by in total 15.9 billion U.S. dollars (+101.29 percent). According to this forecast, in 2029, the expenditure will have increased for the ninth consecutive year to 31.6 billion U.S. dollars. Covered are expenditures of international outbound visitors to other countries from the selected region, including payments to foreign carriers for international transport. Domestic tourism expenditures are not included. The forecast has been adjusted for the expected impact of COVID-19.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).Find more key insights for the international tourism expenditure in countries like Kuwait and Bahrain.