Work

From Traffic Dynamics to Smart City Solutions: Identifying Key Elements for Data-Driven Traffic Management

Year: 2025

Type: article

Abstract: Urban mobility is a critical challenge in smart city development, requiring innovative solutions to address housing shortages, congestion, and pollution. While smart city solutions have advanced, they often overlook the systemic complexity of urban environments, where infrastructure, governance, and human behavior are deeply interconnected. Addressing this gap, our study employs Vester's Sensitivity Model to analyze urban traffic as part of a dynamic city ecosystem. We conduct our study in the context of smart traffic management to identify key elements that shape traffic in a city and that can be targeted with related data-driven applications. By adopting a systemic approach, this research contributes to the development of smart city strategies that balance technological, environmental, and societal needs. Our findings provide a foundation for future scenario-based assessments and offer insights for policymakers and practitioners seeking to improve urban mobility while ensuring long-term sustainability.

Source: Journal of the Association for Information Systems

Authors: Lorenz, Alisa, Rozbitski, Paul, Leyh, Christian, Madeja, Nils

Institution: Technische Hochschule Mittelhessen

Language: English

Topic: Smart Cities and Technologies

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7025192021

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