Induced demand happens when, as a response to congestion, governments invest in more road infrastructure and expand road capacity, which leads to reduced congestion. If everything else were constant, this would be a long-lasting effect. However, solutions that may seem logical with linear thinking often reflect a narrow view of the problem that misses the unintended effects that appear in complex systems. In the case of induced demand, congestion decreases only in the short term because as congestion decreases, driving becomes more attractive, making more people buy cars and drive more, which increases traffic volume again. The fundamental economic principle of supply and demand applies here: when the “price” of driving, in terms of travel time, goes down, the quantity of driving goes up, leading to more congestion again over time (Litman and Colman, 2001[1]). However, as congestion increases, more investment in roads increases the capacity to absorb more vehicles within acceptable congestion levels. Thus, the equilibrium at which the system would reach traffic saturation increases. Figure A A.1 below describes the observed trend in traffic that results from the induced demand phenomenon.
Climate Mitigation in Intermediary Cities
Source: Adapted from Litman and Colman (2001[1]).
Urban sprawl is a term frequently used in urban planning and development, it is usually associated with a fast and unplanned expansion of urban areas. In practice, urban sprawl is an urban development pattern characterised by low population density that can be manifested in multiple ways (OECD, 2018[2]). Despite its widespread discussion, there is no single, universally accepted definition of urban sprawl. This lack of a definitive description underscores the complexity and varied nature of the phenomenon, which encompasses a range of physical, social, and environmental attributes.
Urban sprawl has direct effects on the landscape. Although sprawl can be measured through different metrics, in a given territory, urban sprawl usually intensifies under three primary conditions (Schwick, 2012[3]): first, when there is an expansion in percentage of built up, i.e. the area covered by buildings and other structures; second, when there is a noticeable increase in the scattering or spreading out of built-up areas; and third, when there's a rise in the amount of land uptake per person, whether for living or employment purposes. This expansion is indicative of a more extensive use of land for urban purposes, reflecting changes not only in the quantity of land used but also in the patterns of its usage and the density with which it is occupied.
Source: Adapted from Schwick (2012[3]).
A causal loop diagram is a tool in systems analysis that depicts how different elements interact with each other. It involves identifying elements and their connections, marked by arrows indicating positive or negative relationships. The diagram includes feedback loops: reinforcing loops (R) amplify changes, while balancing loops (B) stabilise the system. Overall, the diagram helps visualise the dynamics of a system by showing how changes in one part can affect the whole.
The image below presents a causal loop diagram with two interconnected feedback loops. The reinforcing loop, illustrated in blue, shows that an increase in body mass leads to an increase in food intake, which in turn further increases body mass, creating a cycle of growth. This is depicted by the positive signs along the arrows, indicating that the variables change in the same direction. On the other hand, the balancing loop, shown in red, indicates a negative relationship where an increase in food intake leads to a decrease in appetite. This loop acts as a counterbalance, aiming to stabilise the system by reducing the appetite as food intake increases, denoted by the negative sign. Together, these loops model the complex interplay between body mass, food intake, and appetite, illustrating how they can drive and regulate each other in a dynamic system.
Source: Authors’ elaboration.
References
[1] Litman, T. and S. Colman (2001), “Generated traffic: Implications for transport planning”, ITE journal, pp. 71(4), 38-46.
[2] OECD (2018), Rethinking Urban Sprawl: Moving Towards Sustainable Cities, OECD Publishing, Paris, https://doi.org/10.1787/9789264189881-en.
[3] Schwick, C. (2012), “L’étalement urbain en Suisse – impossible à freiner? Analyse quantitative de 1935 à 2002 et conséquences pour l’aménagement du territoire.”, Bristol-Schriftenreihe, Vol. Vol. 32.