Who’s Moving? Measuring Urban Mobility Gaps in the Digital Age: A Theoretical Agent-Based Model

The growing integration of Information and Communication Technologies (ICT) into all aspectsof daily life has intensified discussions on the deepening of digital inequalities, underscoringthe need for research to understand how individuals navigate this evolving landscape. This paperinvestigates the relationship between technology adoption and urban mobility dynamics, framingthe exploration within the ’mobilities turn’ conceptual framework. We introduce the Digital MobilityModel (DMM)—an agent-based model designed to explore how digital technologies influenceindividual mobility patterns and delve into how technological advancements could shape or reshapeinequalities at the urban level. The DMM employs the concept of ”learning by moving,” whereinindividuals acquire digital skills during their mobility experiences, thereby affecting their abilityto access digitally enabled places. The model simulates the interaction between individuals (i.e.,dynamic agents) and places (i.e., static agents) demonstrating how technology adoption dynamicsresult in unequal mobility patterns, which in turn impact access to urban services. As such theDMM provides a novel theoretical framework, bridging mobility studies and ICT approaches, andunderscores its potential for understanding the evolving landscape of digital inequalities in urbancontexts, which contributes to ongoing discussions on mobility, technology, and societal transformations.Keywords: Mobilities, Digital divide, Digital mobility, Agent-based model, Technology adoption

Authors

Publication Details

Published
2025-09-24
DOI
https://doi.org/10.31235/osf.io/j2d9f_v1
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

Who’s Moving? Measuring Urban Mobility Gaps in the Digital Age: A Theoretical Agent-Based Model

Andrew Crooks, Fiammetta Brandajs, Na Jiang
Human Mobility and Location-Based Analysis
article

Who’s Moving? Measuring Urban Mobility Gaps in the Digital Age: A Theoretical Agent-Based Model

Andrew Crooks, Fiammetta Brandajs, Na Jiang
article en

Abstract

The growing integration of Information and Communication Technologies (ICT) into all aspectsof daily life has intensified discussions on the deepening of digital inequalities, underscoringthe need for research to understand how individuals navigate this evolving landscape. This paperinvestigates the relationship between technology adoption and urban mobility dynamics, framingthe exploration within the ’mobilities turn’ conceptual framework. We introduce the Digital MobilityModel (DMM)—an agent-based model designed to explore how digital technologies influenceindividual mobility patterns and delve into how technological advancements could shape or reshapeinequalities at the urban level. The DMM employs the concept of ”learning by moving,” whereinindividuals acquire digital skills during their mobility experiences, thereby affecting their abilityto access digitally enabled places. The model simulates the interaction between individuals (i.e.,dynamic agents) and places (i.e., static agents) demonstrating how technology adoption dynamicsresult in unequal mobility patterns, which in turn impact access to urban services. As such theDMM provides a novel theoretical framework, bridging mobility studies and ICT approaches, andunderscores its potential for understanding the evolving landscape of digital inequalities in urbancontexts, which contributes to ongoing discussions on mobility, technology, and societal transformations.Keywords: Mobilities, Digital divide, Digital mobility, Agent-based model, Technology adoption

Openalex Percentile: Top 74%
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.