The study uses the case of two regions with small and medium sized cities (Agder in Norway and the greater Innsbruck area in Austria) and two European capitals, Vienna and Oslo, to showcase the impact of the COVID-19 pandemic on public transport ridership in northern and central Europe. The comprehensive timeline of actions taken by governments and public transport providers in Austria and Norway, and their impact on public transport ridership in the first and second waves of the pandemic form the basis of a descriptive study.
Comparing the data, a strong negative impact on the public transport patronage in the first wave of the pandemic was found, despite a comparable low number of cases per 100,000 inhabitants. Furthermore, a smaller impact of the second wave of the pandemic on the ridership was registered. The study provides valuable first insights on how the pandemic affected different settlement types. It also documents, in detail, the measures taken by two distinct European countries to curb the pandemic infection rates and how these actions impacted public transport patronage.
The results pointed in the direction of a need for further analysis of aspects such as “fresh fear” and “lingering fear” in relation to the effect of a pandemic on public transport. Data availability limitations show the necessity of upgrading and aligning ridership and ticketing monitoring systems across Europe, to allow for better understanding of pandemic impacts on public transport in a more unified manner.
Abstract:In this article, we take stock of the findings from conceptual and empirical work on the role of transition initiatives for accelerating transitions as input for modeling acceleration dynamics. We applied the qualitative modeling approach of causal loop diagrams to capture the dynamics of a single transition initiative evolving within its regional context. In doing so, we aim to address two key challenges in transition modeling, namely conceptualization, and the framing of empirical insights obtained for various case study regions in a consistent modeling framework. Our results show that through this systematic approach one can translate conceptual and qualitative empirical work into a transition model design. Moreover, the causal loop diagrams can be used as discussion tools to support dialogue among researchers and stakeholders, and may support a comparison of transition dynamics across case-study regions. We reflect on main limitations related to empirical model validation (lack of data) and to model structure (high level of aggregation), and describe next steps for moving from a qualitative single transition initiative to a quantitative multiple transition initiatives model.
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