Global disruptions, from geopolitical tensions to energy shocks, show up in how people move through cities every day. In this interview, Nancy Tzioutziou, a researcher at the Aristotle University of Thessaloniki (AUTH), shares what the data tell us about cities under stress and what a truly antifragile response looks like in practice.

From your area of expertise, how do global disruptions, like fuel price spikes or supply chain pressures, translate into changes in urban mobility?

From the perspective of urban resilience, global disruptions drive changes in everyday operations alongside long-term adaptations in cities. In mobility systems, these disruptions cause changes in how people travel, how far they go, and how goods are delivered in cities. These changes depend on people’s economic situation, social profile, and whether other transport options are available. These changes may either reinforce existing vulnerabilities or pave the way for adaptive strategies that foster more sustainable and resilient cities, as shown in the following examples.

Impact of fuel price spikes

Fuel price changes directly affect how people travel, but not everyone is impacted the same way:

• Reduced travel range: Big jumps in gas prices make people travel much shorter distances. During price surges tied to the Russia–Ukraine war, people in Warsaw, Paris, and Berlin travelled over 50% less (Shu et al., 2024).

• Congestion and demand shifts: High fuel prices reduce road traffic delays because fewer people use private cars, but subway and train patterns don’t change much right away, as schedules stay the same no matter fuel prices (Fang et al., 2022).

• Socioeconomic vulnerability: Poorer neighbourhoods far from subways suffer more from fuel price hikes. For instance, in Rio de Janeiro, over 50% of districts have low resilience to these shocks (Aprigliano et al., 2019).

• Technological transition: High fuel prices encourage governments and businesses to invest in cleaner vehicles and systems. But cheap fuel slows down the switch to sustainable options (ITF, 2021).

Supply chain pressures 

Disruptions in global supply chains, such as those seen during the COVID-19 pandemic, have changed urban delivery by speeding up e-commerce and online shopping:

• Last-mile delivery inefficiency: The final step of delivery to homes is the least efficient and most polluting part, taking up 13% to 75% of total shipping costs (Jagoda et al., 2023). This causes more city traffic jams as delivery vehicles go deeper into neighbourhoods (Jagoda et al., 2023).

• Modal shifts in delivery: Quick “instant deliveries” for food and groceries have added more variety to city traffic, with growing use of bikes and mopeds—though bike shares vary by local rules and demand (ITF, 2023).

• Substitution effects: City travel patterns shift as people choose deliveries over personal shopping trips. While online orders boost delivery traffic, they may cut back on car or bike trips to stores (ITF, 2023).

What are the early warning signs that a city’s mobility system is under stress?

Early warning signs of stress in a city’s transport system show up in key measurements, everyday patterns, and chain reactions where problems spread. These signs range from daily hassles to major disruptions that need action. Key indicators of transport stress include traffic slowdowns measured hourly by road sensors, the seriousness of recent events, average trips per person, and shifts in travel patterns. Simple metrics like system stress, mobility throughput, and distribution of mobility flows spot building congestion and problems early, before they worsen. 

City transport faces a spectrum of disruptions ranging from daily hassles like traffic jams and parking shortages, to mid-level issues such as local floods and strikes on buses/metros, to major crises from widespread blackouts or wars damaging infrastructure. These disruptions often appear in everyday mobility patterns as longer travel times, less reliable transport services, and higher running costs, pointing to bigger weaknesses in the system. The cascading impacts of these disruptions are soon evident on the environmental conditions (increased carbon emissions and noise pollution) and the economic landscape (higher operational costs for logistics and reduced economic productivity due to congestion). Additionally, there are significant impacts on the users’ satisfaction and social equity of urban populations. Some of these impacts can be obvious even within a few minutes of a disruptive event, revealing the need to respond timely and effectively to the current challenge. 

AntifragiCity has developed a framework of KPIs to monitor urban mobility under disruption. Which indicators are you watching most closely, and why?

The AntifragiCity KPIs’ framework focuses on a few key measures of transport types, travel times, and system features to track city travel during disruptions. We watch commuter flow centrality and mobility throughput most closely—these show how active and busy transport systems are, using data from traffic sensors and real-time social media. Other key measures include average public transport speed, daily public transport trips, and total vehicle-kilometres travelled, which reveal how efficiently the system runs and how much strain infrastructure faces. Moreover, the AntifragiCity framework highlights environmental effects, focusing on noise and air pollution to track travel’s impact on the environment. It also covers transport safety and access, costs, and satisfaction, using simple measures like crash rates, ease of getting around, and what people think to keep things fair and safe during tough times.

These KPIs are critical for the assessment of the condition of urban mobility systems and are also prioritised by local transport experts based on their applicability and data availability. These KPIs map directly to global and regional goals such as the Sustainable Development Goals and the European Green Deal, while also reflecting quantifiable and versatile metrics that enable consistent assessment of both physical urban networks and the people’s experience within the mobility system.

What does the data tell us about how citizens are adapting (for example, shifts toward public transport or active mobility when private vehicle costs rise)?

Data on public transport demand, measured through passenger-kilometres and ridership numbers, reveals shifts in community reliance on shared transit services when private vehicle costs rise. Similarly, tracking non-motorised transport demand and modal split indicators shows how citizens adapt by increasing walking and cycling for sustainability and economic prosperity in response to pricing policies that raise direct and indirect costs of car use. These metrics, combined with satisfaction indicators for bicycle accessibility, provide evidence of behavioural adaptation toward more sustainable mobility options when financial pressures make private vehicle ownership less attractive. This adaptive behaviour underscores the interplay between economic incentives and the adoption of environmentally sound transportation modalities, contributing to a more resilient urban mobility ecosystem.

What does an antifragile response look like in practice?

An antifragile response is characterised by a system that gains strength from volatility, learns from disruptions, and improves its performance in the face of future challenges. Such a response to fuel price spikes would mean quickly changing bus and train schedules and routes to match where people need them most. It would also encourage mixing transport options—like buses, bikes, and walking—using apps that show real-time information on diverse transport options. This strategy would make citizens more satisfied with their commutes, it would get services to more neighbourhoods for equitable coverage, and it would reduce environmental pollution by minimising solo car trips. Therefore, the entire mobility system would rearrange its functional architecture not only to respond to this disruption but to enhance its overall performance and adaptive capacity for future uncertainties.

Understanding how global disruptions ripple through urban mobility systems is vital to what we are building at AntifragiCity. By combining real-world data, predictive tools, and a robust KPI framework, we are helping cities move from reactive to genuinely adaptive.

References

Aprigliano, V., Rothfuß, R., Hochschild, V., Silva, M. A. V. da, Silva, W. R. da, Steiniger, S., & Santos, T. F. dos. (2019). Urban resilience in the face of fossil fuel dependency: the case of Rio de Janeiro’s urban mobility. Urbe Revista Brasileira de Gestão Urbana, 11. https://doi.org/10.1590/2175-3369.011.e20180160

Fang, Z., Wang, G., Yang, Y., Zhang, F., Wang, Y., & Zhang, D. (2022). A long-term travel delay measurement study based on multi-modal human mobility data. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-19394-z

ITF. (2021). ITF Transport Outlook 2021. https://doi.org/10.1787/16826A30-EN

ITF. (2023). ITF Transport Outlook 2023. https://doi.org/10.1787/B6CC9AD5-EN

Jagoda, A., Kołakowski, T., Marcinkowski, J., Cheba, K., & Hajdas, M. (2023). E-customer preferences on sustainable last mile deliveries in the e-commerce market: A cross-generational perspective. Equilibrium Quarterly Journal of Economics and Economic Policy, 18(3), 853. https://doi.org/10.24136/eq.2023.027

Shu, Y., Chen, X., & Di, X. (2024). Mobility Pattern Analysis during the Russia–Ukraine War Using Twitter Location Data. Information, 15(2), 76. https://doi.org/10.3390/info15020076

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