This document discusses a pilot project using big data sources to support tourism statistics in Italy. The goals were to: 1) Inventory data sources related to tourism like accommodation listings, transportation, and surveys. 2) Use web scraping to collect listing data from Booking.com to understand coverage of accommodation surveys. 3) Develop methodologies to combine data sources like matching administrative registers to scraped listings. The results showed scraping over 25,000 Italian listings on Booking.com, with methods matching around 30% of listings to regional registers. Future work includes using platforms to provide new accommodation and price data, spatial-temporal disaggregation, and improving tourism satellite accounts.

1. SMART TOURISM
Istat | Direzione Centrale per le Statistiche Sociali e il Welfare
Roma, 5 maggio 2021
ESSnet Big Data Pilots II: Risultati e
prospettive di sviluppo verso le Trusted
Smart Statistics
MASCIA DI TORRICE

2. 2
…OF OTHER (BIG) DATA SOURCES

3. o Goals of WPJ
o Inventory of data sources related to tourism statistics
o Web scraping
o Developing a methodology for combining data from various sources
o Perspective
Indice della presentazione
SMART TOURISM | MASCIA DI TORRICE
3

4. o Set up a smart pilot Information system to support statistical production in the field of tourism by integrating
various big data sources with administrative registers and statistical databases
o Italian team: Mascia Di Torrice (DCSW), Massimiliano Amarone (DCIT), Lorenzo Cavallo (DCAT), Barbara
Dattilo (DCSW), Valentina Minnetti (DCME), Maria Teresa Santoro (DCAT), Mariangela Sabato (DCSW),
Antonella Simone (DCIT)
Goals of WPJ
SMART TOURISM | MASCIA DI TORRICE
4

5. Inventory of data sources related to tourism statistics
SMART TOURISM | MASCIA DI TORRICE
5
DATA SOURCES FREQUENCY ADDITIONAL INFO
POTENTIAL RISK
INVOLVED
LEVEL LEGISLATION
EXTERNAL/
INTERNAL
SHORT/MIDDLE/
LONG TERM
SOURCE
WASTE PRODUCTION annual
only annual data; so it's
impossible to know the seasonal
peacks
NUTS3 (Cities)
External (National
Institute for
Environmental
Protection)
Long term
WATER CONSUMPTION annual
only annual data; so it's
impossible to know the seasonal
peacks
NUTS3 (Cities) national Internal Long term
AIRPORT DATA monthly
number of passenger (national, international,
scheduled, charter service)
difficulties to distinguish between
tourism and non-tourism mobility
airport
Regulation EC n.
437/2003 and n.
1358/2003, updated by
Regulation (EC) n.
1791/2006
internal Long term
PORT AUTHORITY DATA monthly number of passenger
difficulties to distinguish between
tourism and non-tourism mobility
ports embarking/disembarking
at least 200,000 passengers.
Directive 2009/42/EC internal Long term
RAILWAY DATA quarterly number of passenger
difficulties to distinguish between
tourism and non-tourism mobility
size of railway enterprises
Regulation EC n.
91/2003
internal Long term
OCCUPANCY OF TOURIST
ACCOMMODATION ESTABLISHMENTS
monthly
data on arrivals and nights spent (by residents
and non-residents) at tourist accommodation
establishments in Italy
LAU (Municipalities)
Regulation EC 692 and
1681 on tourism
statistics
internal Long term
CAPACITY OF COLLECTIVE
ACCOMMODATION ESTABLISHMENTS
annual LAU (Municipalities)
Regulation EC 692 and
1681 on tourism
statistics
internal Long term
TRIPS AND HOLIDAYS SURVEY monthly
data on participation of residents in trips for
personal reasons and business trips (domestic
and outbound); provides a wide set of information
on tourist trips, such as destination, booking, main
purpose, main type of accommodation and main
means of transport, duration and period of the
year for each trips made
NUTS2 (REGIONS)
Regulation EC 692 and
1681 on tourism
statistics
internal Long term
INTERNATIONAL TOURISM SURVEY monthly
resident and non-resident travelers at the Italian
borders (road and rail crossings, international
ports and airports).
NUTS2 (REGIONS)
External (Bank of
Italy)
Long term
SURVEY ON RURAL TOURISM
ACCOMMODATIONS
annual Characteristics of farmhouse accommodations NUTS3 (Cities) national internal Long term
SURVEY ON MUSEUMS AND SIMILAR
INSTITUTIONS
every four year (2006-
2011-2015-2019)
number of admissions
usable only to estimate this
specific part of cultural tourism
NUTS3 (Cities) national internal Long term

6. o Identification of the most popular national
and international websites in the tourism sector
https://www.similarweb.com
o Most popular websites in Europe:
 Booking.com
 Airbnb.com
 Trivago.com
o In Italy, Booking has also the greater number of
establishments on the national territory
Inventory of data sources related to tourism statistics
SMART TOURISM | MASCIA DI TORRICE
6
PORTAL Worldwide BG Hesse EL IT NL PL PT SK
Booking.com 1 1 1 1 1 1 1 1 1
Airbnb.com 2 3 2 2 2 2 2 2 2
Vrbo.com 3 4
Hotels.com 4
Trivago.com 5 3 3 3
Pochivka.bg 2
Visit.bg 4
Hometogo.de 3
Fewo-direkt.de 4
Traum-ferienwohnungen.de 5
Ekdromi.gr 4
Casevacanza.it 4
Bed-and-breakfast.it 5
Landal.nl 3
Roompot.nl 4
Centerparcs.nl 5
Noclegi.pl 3
Profitroom.com 4
Noclegowo.pl 5
Megaubytovanie.sk 3
Ubytovanienaslovensku.eu 4
Sorger.sk 5
MOST POPULAR WEBSITES FOR ACCOMMODATION AND HOTELS (2020)

7. o Completing and enriching information on the
tourist accommodation establishments already
surveyed in the context of the traditional
statistical surveys
o Understanding the degree of coverage of these
surveys, particularly in the case of those
typologies of accommodation not well or not yet
covered by the official statistics on tourism
SMART TOURISM | MASCIA DI TORRICE
7
Web scraping
Official Tourism
statistics
(Census surveys on
the Capacity and
Occupancy of
accommodation
establishments)
Web
portals
Administrative
regional archives
Other
sources

8. o Italy carried out the web scraping in 2019 and
2020 on the Booking.com portal
o The high number of structures in the country
required limiting the search to Emilia-Romagna
region
o Emilia-Romagna data:
 25,683 establishments
 15,950 accommodation establishments
 9,733 «Other private establishments»
 7.4% of Italian establishments
Web scraping
SMART TOURISM | MASCIA DI TORRICE
8
Official Tourism
statistics
(Census surveys on
the Capacity and
Occupancy of
accommodation
establishments)
Web
portals
Administrative
regional archives
Other
sources

9. Listings on Booking.com and accommodations of the Emilia-Romagna (E-R) regional archive (2019)
TITOLO PRESENTAZIONE | AUTORE
Web scraping
9
Type of accommodation on E-R regional
archive
Type of
accommodation on Booking.com
SOURCE
Difference
(absolute values)
% potential
coverage
E-R archive Booking.com
Nr of accommodations Nr of listings
Hotel Hotel 3,982 1,810 2,172 45.5
Rented house Rented house 2,917 2,296 621 78.7
Bed & Breakfast Bed & Breakfast 2,349 948 1,401 40.4
Rented room Rented room 1,115 333 782 29.9
Farmhouse Farmhouse 791 244 547 30.8
Holiday house Holiday house + Country house 846 354 492 41.8
Other private accommodation (not enterprise) Not present 349 - 349 -
Residence Residence 294 199 95 67.7
Camping sites Camping sites 100 13 87 13.0
Hostel Hostel 70 17 53 24.3
Alpine refuge Not present 22 - 22 -
Hiking refuge Not present 11 - 11 -
Holiday village Holiday village 11 11 0 100.0
Others Not present 5 - 5 -
Not present
Chalet, Boat, Inn, Lodge, Motel,
Resort, Villa,
Homestay accommodation
- 194 - -
TOTAL 12, 862 6,419 6,443 49.9

10. Online Job
vacancies
o Reuse of software
o Process includes three main steps:
 Design and development of the java application
[Java with the extension of the Selenium web scraping
libraries within the Netbeans IDE development suite]
 Inspection and analysis of the Booking's site
[Web development tools to carry out preventive analysis of the
Booking.com site with a single municipality as a search
parameter  optimization of the software]
 Generation of output files
[Stored on MongoDB]
Web scraping
SMART TOURISM | MASCIA DI TORRICE
10
Webscraping software for WPJ
project
Consumer
prices of
holiday
packages
Active
companies

11. o Combination of the web scraping data with the
administrative register of tourist accommodation
establishments.
o Two different methods of matching were tried to
compare this archive with the results of web
scraping on the ER region: Jaro-Winkler distance
and Arcgis Score.
Developing a methodology for combining data from various
sources
SMART TOURISM | MASCIA DI TORRICE
11
CHOISE OF
THE
METHOD
MATCHING
EVALUATION
OF THE
RESULTS

12. RESULTS OF MATCHING ON 2018 EMILIA-ROMAGNAADMINISTRATIVE ARCHIVE
(JARO-WINKLER SIMILARITY)
Developing a methodology for combining data from various
sources
SMART TOURISM | MASCIA DI TORRICE
12
Match No. Matching type Score
Number of matched
accommodations
1
Hotel Name/Address
80 1,025 (8.9%)
85 242
JARO-WINKLER SIMILARITY
YEAR
EMILIA-
ROMAGNA
BOOKING.COM
2018
11,526
accommodations
328 municipalities
5,670
accommodations
315 municipalities

13. Developing a methodology for combining data from various
sources
SMART TOURISM | MASCIA DI TORRICE
13
ARCGIS MATCHING
Match
No.
Matching type
Score
ArcGis
Number of matched
accommodations
2018 2019
1 Linkage Hotel name and municipality - 648 1,265
2 Linkage Hotel name formatted and municipality - 1,738 2,715
3 Linkage formatted address
90 2,665 3,611
80 2,968 3,698
70 3,001 3,699
4
Linkage Geo Latitude, Longitude distance
10 meters
90 2,927 3,711
80 2,979 3,819
70 3,004 (26%) 3,820
5
Linkage Geo Latitude, Longitude distance
20 meters
90 - 3,922
80 - 4,029
70 - 4,030
6
Linkage Geo Latitude, Longitude distance
30 meters
90 - 4,156
80 - 4,269
70 - 4,270 (33%)
YEAR
EMILIA-
ROMAGNA
BOOKING.COM
2018
11,526
accommodations
328 municipalities
5,670
accommodations
315 municipalities
2019
12,877
accommodations
328 municipalities
6,419
accommodations
315 municipalities
RESULTS OF MATCHING ON 2018 AND 2019 EMILIA-ROMAGNAADMINISTRATIVE ARCHIVE
(ARCGIS MATCHING)

14. o CROSS-CHECKING OF THE MATCHING (Geographical analysis with GIS software, analysis by type of
accommodation covered)
o 3 lists of municipalities:
 Municipalities with low matching coverage, namely with the greater distances between the regional
register and the web scraping results
 Municipalities absent in the web scraping results although they have establishments in the regional
register
 Municipalities present in web scraping and not in the regional register
Developing a methodology for combining data from various
sources
SMART TOURISM | MASCIA DI TORRICE
14

15. PERSPECTIVES
SMART TOURISM | MASCIA DI TORRICE
15
o NEW ACCOMMODATIONS (holiday
dwellings, private houses,…)
o NEW INFORMATION ON
ACCOMMODATIONS (facilities, prices, ..)
o SPATIAL-TEMPORAL DISAGGREGATION
o FLASH ESTIMATES
o IMPROVEMENT OF TSA
Platforms macrodata
(Airbnb, Booking, Expedia,
Tripadvisor)
Movimento dei clienti negli
esercizi ricettivi (DCAT)
Capacità degli esercizi ricettivi
(DCAT)
Archivi regionali (DCAT)
Viaggi e vacanze (DCSW)

16. grazie
MASCIA DI TORRICE | mascia.ditorrice@istat.it