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An Instrument for Evaluating Data-Driven Traffic Management Applications in the Context of Digital Transformation Towards a Smart City

Lorenz, Alisa; Madeja, Nils; Cifci, Aynur (2022)

Konferenzpaper
Peer Reviewed

Erschienen in
Software Business : 13th International Conference, ICSOB 2022, Bolzano, Italy, November 8–11, 2022, Proceedings
Verlag
Springer International Publishing
ISBN
978-3-031-20705-1
eISBN
978-3-031-20706-8
Seiten
3-18

Abstract

The smart city concept represents an integrated approach for mitigating the challenges resulting from ongoing urbanization by synergizing technology, data, and citizens in a sustainable manner. Smart mobility is an important aspect of a smarty city with intelligent traffic management as one of its key enablers that can contribute to making cities more attractive for living. In this article we focus on data-driven applications for traffic management and develop a new instrument for their evaluation, sharing insights from a municipal project. Drawing on digital business research, evaluation models and expertise from traffic management, we develop criteria and apply them to a Weighted Sum Model, an established modeling technique. As a result, we obtain an easy-to-use instrument for evaluating data-driven applications that can also be adjusted to other contexts. Therefore, both our instrument and the process we employed in its development can support future smart city initiatives in their instrument development and evaluation process.

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Referat Forschung und Wissenschaftlicher Nachwuchs

Stefan Mallmann | Publikationen

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Gebäude B11, Raum 3.16

Renate Meyer | Projekte und Systemadministration

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Gebäude B11, Raum 3.13

Marcel Wagner | Systemadministration

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Gebäude B11, Raum 3.01
Hochschulkontakt

Technische Hochschule Mittelhessen
University of Applied Science

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