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2023
Conference Paper
Title

A mobility app for everyone?

Title Supplement
An empirical analysis of user types based on social lifestyles and personal characteristics
Abstract
Moving via an app? Necessary information or tickets to arrive at the required destination can be accessed via smartphone, which is a constant companion anyway. Whether taking the train, choosing a ride-sharing service or even an electric scooter - all one must do is download the right app to use and operate the preferred means of transport.This work focus on the understanding of user types and their relationship with mobility apps with the motivation of better understanding mobility user needs when it comes to the digitalization of services. Through an in-depth literature review, we identified a variety of models that study behavior and specifically the use of technological innovations, such as apps. While approaches such as the Theory of Planned Behavior, the Norm Activation Model, or the Utility Approach apply to different contexts, the Acceptance Theory or the Mobile Phone Appropriation Model sets the specific focus on apps and mobile devices. Since each of the models has certain limitations, several approaches were integrated into a new, conceptual research model, which was empirically examined by a representative survey. We collected empirical data using a survey spread throughout Germany, with a representative sample size of 2501, and afterwards applied a cluster analysis to describe user types. Since the respondents needed to be typified according to both individual characteristics and social characteristics, two clustering focuses were carried out i.e., user types according to personal characteristics/user types according to social lifestyles. The cluster analysis included attributes related to attitudes, the general use of technical devices and mobility behavior. Mean differences were considered to compare the identified groups to each other. The first clustering approach shows that two types of mobility app users can be distinguished. "Combiners" i.e., people who spend more time with technical devices and apps, that are more willing to use different means of transport and have a more positive attitude towards shared consumption, are more inclined to use mobility apps than "Privacy protectors", for whom private property and the protection of their data are more important.In a second clustering, respondents were grouped according to their social lifestyles. The analysis revealed that individuals characterized as "Modern Materialists" and "Relationship-Oriented" have higher mobility app awareness and use it more often. In contrasts, "Conversative Lovers", individuals which do not attach great importance to social contacts or a modern, upscale standard of living, are hardly aware of and use mobility apps. Thus, we could conclude that consolidated social relationships and openness to multiple social contacts seem to influence mobility app awareness and use.The further assessment shows that respondents feel that the functions that are already established to a greater or lesser extent in apps are important. The ability to combine or communicate different means of transportation via a mobility app does not meet an acute need. Depending on the cluster, however, the needs vary in strength and functions are seen as having different relevance.
Author(s)
Tsaga, Irini
Univ. Stuttgart, Institut für Arbeitswissenschaft und Technologiemanagement -IAT-  
Motzer, Nicolaj
Univ. Stuttgart, Institut für Arbeitswissenschaft und Technologiemanagement -IAT-  
Kern, Mira  
Univ. Stuttgart, Institut für Arbeitswissenschaft und Technologiemanagement -IAT-  
Soares Amorim, Marco Raul  
Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO  
Mainwork
Human Factors in Transportation  
Conference
International Conference on Human Factors in Transportation 2023  
International Conference on Applied Human Factors and Ergonomics 2023  
DOI
10.54941/ahfe1003815
Language
English
Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO  
Keyword(s)
  • Mobility App

  • User groups

  • Cluster analysis

  • Mobility Survey

  • User behavior

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