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Table 1 Tabular overview of empirical approaches to measure sustainable tourism, sustainable development indicators and related phenomena with online platform data

From: Measuring sustainable tourism with online platform data

Publication

Main variable

Data Source

Data type

Ground truth

Country/Region

Sample size

Bassolas et al. (2016) [39]

Touristic site attractiveness

Twitter

Geolocated tweets and user home locations

Africa, Asia, Europe, North and South America

9.6 million geolocated tweets; 59,000 users’ places of residence

Batista e Silva et al. (2018) [32]

Average daily numbers of overnight tourists

Booking.com; TripAdvisor; Eurostat

Accommodation location and capacity

EU-28 (incl. GB)

716,103 establishments

Buning and Lulla (2020) [28]

Spatio-temporal usage patterns of bike shares

Bike fleet GPS; user zip codes

GPS; User data

Indianapolis, USA

353,733 individual trips

Falk and Hagsten (2020) [34]

Visitor flows to world heritage sites

Instagram; UNESCO

Number of posts, hashtags

Europe, North America

680m Instagram posts for 525 sites

Fatehkia et al. (2020) [42]

Wealth Index at clustered geographic locations

Facebook

Advertisement market audience size estimates

DHS wealth index

India and Philippines

1,205 (Philipines); 28,043 (India)

Gallego and Font (2021) [30]

Air passenger demand forecasts

Skyscanner flight searches (ForwardKeys)

Global air capacity and flight search data

Global

5,000m searches and >600m picks

Grybauskas et al. (2021) [44]

Apartment revisions

Property listing sites

Property listings with up to 16 numerical features

Vilnius, Lithuania

18,922 listings

Hardy and Arval (2020) [29]

Tourist movements in national park

Mobile app; GNSS

Location data; Demographic survey data

Tasmania, Australia

472 tourists (4-14 days, 1 signal/10 seconds)

Kashyap and Verkroost (2021) [43]

LinkedIn GGI = gender gaps along different dimensions

LinkedIn

Advertisement market audience size estimates

Country-level professional gender gaps data from international labour organisation (ILO)

Global, up to 234 countries predicted (depending on level of analyis); Up to 185 in ground truth

460 million users, 165,02 million without missing data

Londoño and Hernandez-Maskivker (2016) [38]

Customer feedback to GreenLeader program

TripAdvisor

Sustainability mention, gender, nationality, hotel category, city, GL level

Review concerning sustainability or not

6 Cities in Europe and North America

572 comments

Mariani and Borghi (2021) [37]

eWOM (presence and depth of discourse)

Booking.com; TripAdvisor

Text (Comments)

Americas, Europe

4,12 million TripAdvisor and 1,56 million Booking.com reviews

Mendoza et al. (2019) [41]

Intensity of an earthquake in terms of damages

Twitter

Tweets (text mining)

Earthquake catalogue provided by Seismological Center of Chile

Chile

Initially 825,310 tweets; final sample: 187,317 geo-mapped tweets

Nurmi et al. (2020) [31]

Nights spent by foreign tourists

GDS; Amadeus, Sabre, Galileo

Flight bookings

Official accommodation statistics (Finland)

Finland

58 months × 7 countries

Quattrone et al. (2018) [33]

Number of Airbnb listings per tract (geographical unit based on census data)

Airbnb

Geolocations of listings

8 cities in USA

54,681 listings

Serrano et al. (2021) [36]

Attributes important to “green tourists”

Airbnb

Text (Comments)

Actual user assessments

Global, 83 cities

more than 176 million comments

Sun and Paule (2017) [35]

Restaurant and bar rating clusters

Yelp

User ratings from 1-5

Pheonix, USA

2578 restaurants, 981 fast food restaurants, 797 bars

Talebi et al. (2021) [40]

Potential to become ecotourism destination

Manually collected geo data

Geo data (slope, elevation, soil texture, vegetation, etc.)

Classification from systemic analysis

Arasbaran, Iran

637 recreational areas