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Analysis of Lisbon visitors’ internet access behavior: behavior analysis through the identification of clusters

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Bibliographic Details
Summary:This master's thesis focuses on clustering the internet access behavior of urban visitors in the Lisbon urban area. To promote smart city development, the study aims to provide insights into visitors' behaviors while accessing the internet in Lisbon, enabling improved decision-making processes for city management, and enhancing the overall online and offline experience for visitors. The over-tourism phenomenon has put a strain on infrastructure, public transportation, and cultural heritage sites. Therefore, innovative methods are needed for effective smart city management, particularly in urban mobility. The increasing availability of Wi-Fi networks during travel has generated valuable data that can be used to develop groundbreaking approaches to understanding visitors’ behaviors and mobility patterns in urban areas. This knowledge enables the analysis and clustering of urban visitors' behavior, contributing to improved decision-making processes in smart city management.
Main Authors:Silva, Beatriz Miguel Carvalho
Subject:Urban planning Visitor’sspatial behavior Urban mobility Travel behavior Mobile phone data Visitors mobility
Year:2023
Country:Portugal
Document type:master thesis
Access type:open access
Associated institution:Universidade Nova de Lisboa
Language:English
Origin:Repositório Institucional da UNL
Description
Summary:This master's thesis focuses on clustering the internet access behavior of urban visitors in the Lisbon urban area. To promote smart city development, the study aims to provide insights into visitors' behaviors while accessing the internet in Lisbon, enabling improved decision-making processes for city management, and enhancing the overall online and offline experience for visitors. The over-tourism phenomenon has put a strain on infrastructure, public transportation, and cultural heritage sites. Therefore, innovative methods are needed for effective smart city management, particularly in urban mobility. The increasing availability of Wi-Fi networks during travel has generated valuable data that can be used to develop groundbreaking approaches to understanding visitors’ behaviors and mobility patterns in urban areas. This knowledge enables the analysis and clustering of urban visitors' behavior, contributing to improved decision-making processes in smart city management.