Learning and Adaptation in Polycentric Transport Governance: The Case of the Dutch Brabant Accessibility Agenda

Published date01 August 2022
Date01 August 2022
Subject MatterArticles
Administration & Society
2022, Vol. 54(7) 1402 –1425
© The Author(s) 2022
Article reuse guidelines:
DOI: 10.1177/00953997221109308
Learning and Adaptation
in Polycentric Transport
Governance: The Case
of the Dutch Brabant
Accessibility Agenda
Ingo Bousema1, Tim Busscher1,
Ward Rauws1, and Wim Leendertse1,2
The future of urban-regional transport crucially depends on the ability
of transport governance systems to adapt. Polycentric theory claims
that the presence of polycentric attributes and conditions enables
governance systems to learn and adapt. However, an analysis of the
Dutch Brabant Accessibility Agenda shows that their presence says little
about the adaptive capacity of transport governance systems because
learning and adaptation are influenced by dependencies. To optimize the
adaptive capacity of transport governance systems, it is therefore vital to
acknowledge both the diverse ways in how they learn and adapt, and the
dependencies that shape these processes.
adaptive capacity, polycentric governance, transport, learning, adaptation
1University of Groningen, The Netherlands
2Ministry of Infrastructure and Water Management, Utrecht, The Netherlands
Corresponding Author:
Ingo Bousema, Faculty of Spatial Sciences, University of Groningen, Landleven 1,
9747 AD Groningen, The Netherlands.
Email: i.t.j.bousema@rug.nl
1109308AAS0010.1177/00953997221109308Administration & SocietyBousema et al.
Bousema et al. 1403
Transport governance systems are confronted with uncertainty about how the
future of transport in urban regions will unfold (Lyons & Davidson, 2016;
Marsden & McDonald, 2019). Transport in urban regions involves a system
of relationships between locations, flows, and infrastructures (Rodrigue
et al., 2013), which is tightly interwoven with other parts of society and the
environment (Banister et al., 2011). As a result of this complexity, the exact
impact of shocks and stresses on the functionality of transport systems is
often difficult to predict (Cascetta et al., 2007). This is illustrated by uncer-
tainty about whether the outbreak of COVID-19 will result in structural trans-
formation of travel demand and flows (de Haas et al., 2020), what damage
climate change will cause to infrastructure (Bubeck et al., 2019; Forzieri
et al., 2018), and whether technological innovations such as automated vehi-
cles and “Mobility as a Service” may change travel behavior (Docherty et al.,
2018; Soteropoulos et al., 2019). The functioning of transport systems there-
fore crucially depends on whether transport governance systems have the
capacity to adapt to changing developments (Banister et al., 2011; de Rubens
et al., 2020; Geels et al., 2017).
Transport governance systems are composed of multiple, overlapping
actors that increasingly take account of each other in response to uncertainty.
Transport governance systems involve actors such as national, regional, and
local governments, public and private transport service providers, and infra-
structure network managers as well as construction companies. Traditionally,
these actors operate relatively autonomous at different scales (national, pro-
vincial, and local) and in different sectors such as railways or roads (Hysing,
2009). In the Netherlands, however, there is an increasing commitment to
exchange information, coordinate actions and set up collaborations to find
integrated and sustainable solutions for improving transport systems.
Examples include the emergence of area-oriented approaches (Heeres et al.,
2012), joint accessibility strategies (Straatemeier & Bertolini, 2020), and
public-private partnerships (Leendertse & Arts, 2020). In theory, this evolu-
tion toward polycentricity implies that transport governance systems may
have an optimal capacity to adapt.
Polycentric governance systems are often attributed with an optimal capacity
for adaptation (Carlisle & Gruby, 2019), because they are characterized as com-
plex-adaptive systems (e.g., Andersson & Ostrom, 2008). Adaptive capacity
here is understood as the capacity of a governance system to adapt structures and
processes in response to social or environmental changes (Pahl-Wostl, 2009). In
contrast to monocentricity, which involves a centrally organized system in
which decisions are made by one dominant actor, polycentricity refers to a sys-
tem composed of multiple actors that maintain a level of autonomy that allows

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