From signals to statistics: Measuring same-day visits with MNO data. An Italian use case

Mobile Network Operators (MNOs) data integration into official statistics offers new opportunities for measuring tourism flows. Compared with traditional surveys, MNO data provide broader population coverage, finer spatial and temporal detail, and near real-time availability. These features make them well suited to analysing short-duration mobility patterns, such as same-day visits (SDVs). However, transforming MNO data into statistical indicators presents conceptual and methodological challenges. As these data are collected for operational rather than statistical purposes, tourism indicators must be inferred from large volumes of anonymised mobile phone location data. A key issue is ensuring consistency with internationally agreed definitions, particularly the concept of the Usual Environment (UE) from the International Recommendations for Tourism Statistics (IRTS 2008), which distinguishes tourism from routine mobility. To address these issues, the Italian National Institute of Statistics (Istat) conducted an experimental study with Vodafone between 2023 and 2024, using mobile data to estimate domestic SDVs made by residents travelling to Tuscany and Latium during the third quarters of 2022 and 2023. The study outlines methods to approximate the UE, tests, and comparisons made with survey-based estimates, highlighting both the potential and limitations of MNO data for tourism statistics.

Authors

Institutions

Publication Details

Journal
Statistical Journal of the IAOS
Published
2026-08-26
DOI
https://doi.org/10.1177/18747655261480867
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From signals to statistics: Measuring same-day visits with MNO data. An Italian use case

Mariangela Sabato, Barbara Dattilo, Mascia Di Torrice
Statistical Journal of the IAOS
Human Mobility and Location-Based Analysis
article

From signals to statistics: Measuring same-day visits with MNO data. An Italian use case

Mariangela Sabato, Barbara Dattilo, Mascia Di Torrice
article en

Abstract

Mobile Network Operators (MNOs) data integration into official statistics offers new opportunities for measuring tourism flows. Compared with traditional surveys, MNO data provide broader population coverage, finer spatial and temporal detail, and near real-time availability. These features make them well suited to analysing short-duration mobility patterns, such as same-day visits (SDVs). However, transforming MNO data into statistical indicators presents conceptual and methodological challenges. As these data are collected for operational rather than statistical purposes, tourism indicators must be inferred from large volumes of anonymised mobile phone location data. A key issue is ensuring consistency with internationally agreed definitions, particularly the concept of the Usual Environment (UE) from the International Recommendations for Tourism Statistics (IRTS 2008), which distinguishes tourism from routine mobility. To address these issues, the Italian National Institute of Statistics (Istat) conducted an experimental study with Vodafone between 2023 and 2024, using mobile data to estimate domestic SDVs made by residents travelling to Tuscany and Latium during the third quarters of 2022 and 2023. The study outlines methods to approximate the UE, tests, and comparisons made with survey-based estimates, highlighting both the potential and limitations of MNO data for tourism statistics.

Statistical Journal of the IAOS
Istituto Nazionale di Statistica (IT)
Decent work and economic growth
Openalex Percentile: Top 6%
Human Mobility and Location-Based Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.