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Promet - Traffic&Transportation journal

Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

PUBLISHED
30.09.2022
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Copyright (c) 2024 Yinying He, Csaba Csiszár

Correlation Analysis Method of Customisation and Semi-Personalisation in Mobility as a Service

Authors:

Yinying He
Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering

Csaba Csiszár
Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering

Keywords:Mobility as a Service, mobile application, customisation, semi-personalisation, correlation analysis

Abstract

Mobility as a Service (MaaS) has been proposed as a user-centric, data-driven and personalised ser-vice. However, full personalisation is not available yet. Customisation settings are developed in mobile appli-cations, and several semi-personalised functionalities are also involved. The quantitative analysis of relation between these two could be the reference for further de-velopment tendency of interface functions in mobile ap-plications. Thus, the research objective is identified as: the quantitative correlation analysis between semi-per-sonalisation functionalities and customisation settings. Accordingly, the multi-criteria qualitative analysis method is applied to identify the assessment aspects regarding mobile applications. The scoring method is also introduced. Then the correlation quantitative anal-ysis method is applied to calculate the correlation coef-ficient. We have assessed 25 MaaS applications regard-ing determined aspects. The correlation coefficients for each application together with the overall coefficient are calculated, the assessment results are summarised, and the correlation tendency is interpreted. According to assessment results, the correlation between custom-isation settings and semi-personalisation is not strong at current stage. Selected MaaS mobile applications are customisation setting oriented applications. Fewer manual selections are expected in further personalised services. Our results facilitate development of further personalised functions in MaaS mobile applications.

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How to Cite
He, Y. (et al.) 2022. Correlation Analysis Method of Customisation and Semi-Personalisation in Mobility as a Service. Traffic&Transportation Journal. 34, 5 (Sep. 2022), 767-777. DOI: https://doi.org/10.7307/ptt.v34i5.4126.

SPECIAL ISSUE IS OUT

Guest Editor: Eleonora Papadimitriou, PhD

Editors: Marko Matulin, PhD, Dario Babić, PhD, Marko Ševrović, PhD


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