Persona Design Methodology for Work-Commute Travel Behaviour Using Latent Class Cluster Analysis

Sinziana Ioana Rasca · Karin Markvica · Benjamin Biesinger

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Transportation Planning and Optimization Transportation and Mobility Innovations Persona Design and Applications

Abstract

The present study proposes a new methodology that combines quantitative and qualitative data for the generation of representative personas for commuters. The profiles can be used to better understand their travel behaviour and mode choices. The research is based on the example of the region of Agder in Norway and aims to overcome the persona development shortcomings identified by previous researchers. Data from a regional travel behaviour survey (N= 1 849) is analysed using latent class cluster analysis (LCCA), and enriched with qualitative input from 32 interviews, and information provided by an expert panel. This results in a set of 20 representative persona profiles for the case study region. The proposed methodology is easily replicable in other urban networks and has the potential to provide insight into the mobility behaviour and needs of specific groups of people in order to adapt the transport services and encourage climate-friendly behaviour.

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References

1985From Intentions to Actions: A Theory of Planned Behavior 2007Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study 2011Latent Class Analysis: An Alternative Perspective on Subgroup Analysis in Prevention and Treatment 2007Interpersonal Behavior 2003Applied Latent Class Analysis 2016How Effective are Behavior Change Interventions Based on the Theory of Planned Behavior?2010Latent Class Procedures: Applications to Organizational Research 2010A Multifoci Person-Centered Perspective on Workplace Affective Commitment: A Latent Profile/Factor Mixture Analysis

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2026An integrated mutual-information clustering and deep neural network framework for forecasting travel behaviour under flexible working arrangements 2024Agent-based decision-support model for bus route redesign in networks of small cities and towns: case study of Agder, Norway 2025Exploring variabilities of multi-week activity-travel patterns: a deep embedded clustering approach 2025Understanding the role of decentralised workspaces and hybrid working in alleviating city centre pressure and promoting urban sustainability

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