Clustering Territorial Units Upon Tourism Seasonality Patterns Based on Mobile Phone Time Series Data

Christian Weismayer; Sabine Sedlacek

Clustering Territorial Units Upon Tourism Seasonality Patterns Based on Mobile Phone Time Series Data

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Tourism influences economies, societies, and whole environments. In terms of negative effects, tourist arrival peaks put temporary pressure on destina-tions. Thus, it is important to identify seasonality patterns of homogeneous regions to guide DMOs in the formation of development plans for broader geographical areas. Monthly mobile phone time series tracked from 01/2022 to 12/2023 for Friuli-Venezia-Giulia (FVG) were examined to group munici-palities along seasonality patterns using dynamic time warping (DTW) and hierarchical cluster analysis (HCA) to draw conclusions at the sub-regional level.

Original language	English
Title of host publication	PROCEEDINGS ENTER25 Working Papers
Pages	2-9
Number of pages	8
Publication status	Published - Feb 2025
Event	ENTER25 eTourism Conference - WSB Merito University in Wrocław, Wroclaw, Poland Duration: 19 Feb 2025 → 21 Feb 2025 Conference number: 32

Conference

Conference	ENTER25 eTourism Conference
Country/Territory	Poland
City	Wroclaw
Period	19/02/2025 → 21/02/2025

Access to Document

https://ifitt.net/wp-content/uploads/2025/02/ENTER25-WP-Proceedings-v1.0.pdfLicence: CC BY

Clustering Territorial Units Upon Tourism Seasonality Patterns Based on Mobile Phone Time Series Data
Weismayer, C. (Speaker) & Sedlacek, S. (Speaker)
19 Feb 2025 → 21 Feb 2025
Activity: Talk or presentation › Oral presentation

Cite this

@inproceedings{9637d58768204836bdffcb0858440ec3,

title = "Clustering Territorial Units Upon Tourism Seasonality Patterns Based on Mobile Phone Time Series Data",

abstract = "Tourism influences economies, societies, and whole environments. In terms of negative effects, tourist arrival peaks put temporary pressure on destina-tions. Thus, it is important to identify seasonality patterns of homogeneous regions to guide DMOs in the formation of development plans for broader geographical areas. Monthly mobile phone time series tracked from 01/2022 to 12/2023 for Friuli-Venezia-Giulia (FVG) were examined to group munici-palities along seasonality patterns using dynamic time warping (DTW) and hierarchical cluster analysis (HCA) to draw conclusions at the sub-regional level.",

author = "Christian Weismayer and Sabine Sedlacek",

year = "2025",

month = feb,

language = "English",

pages = "2--9",

booktitle = "PROCEEDINGS ENTER25 Working Papers",

note = "ENTER25 eTourism Conference ; Conference date: 19-02-2025 Through 21-02-2025",

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T1 - Clustering Territorial Units Upon Tourism Seasonality Patterns Based on Mobile Phone Time Series Data

AU - Weismayer, Christian

AU - Sedlacek, Sabine

N1 - Conference code: 32

PY - 2025/2

Y1 - 2025/2

N2 - Tourism influences economies, societies, and whole environments. In terms of negative effects, tourist arrival peaks put temporary pressure on destina-tions. Thus, it is important to identify seasonality patterns of homogeneous regions to guide DMOs in the formation of development plans for broader geographical areas. Monthly mobile phone time series tracked from 01/2022 to 12/2023 for Friuli-Venezia-Giulia (FVG) were examined to group munici-palities along seasonality patterns using dynamic time warping (DTW) and hierarchical cluster analysis (HCA) to draw conclusions at the sub-regional level.

AB - Tourism influences economies, societies, and whole environments. In terms of negative effects, tourist arrival peaks put temporary pressure on destina-tions. Thus, it is important to identify seasonality patterns of homogeneous regions to guide DMOs in the formation of development plans for broader geographical areas. Monthly mobile phone time series tracked from 01/2022 to 12/2023 for Friuli-Venezia-Giulia (FVG) were examined to group munici-palities along seasonality patterns using dynamic time warping (DTW) and hierarchical cluster analysis (HCA) to draw conclusions at the sub-regional level.

M3 - Conference contribution

SP - 2

EP - 9

BT - PROCEEDINGS ENTER25 Working Papers

T2 - ENTER25 eTourism Conference

Y2 - 19 February 2025 through 21 February 2025

ER -

Clustering Territorial Units Upon Tourism Seasonality Patterns Based on Mobile Phone Time Series Data

Abstract

Conference

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Clustering Territorial Units Upon Tourism Seasonality Patterns Based on Mobile Phone Time Series Data

Cite this