Strategies for Urban Network Learning

In this chapter, we present a brief overview of approaches to learning in the public sector. In the history of thinking about learning in the public sector, we witness a gradual shift from individual to organisational learning and, finally, to network learning. This does not imply that one approach is better or more advanced than another, but rather that these levels of learning complement each other. Different approaches lead to different effects of learning. Individuals have learned if the new or adapted insight they have gained results in different behaviours, actions, or other effects. Organisations have learned if they adopt a different way of operating as a result of the learning process. Once this has been secured in policy processes, work processes, or other formal or informal agreements, the learning effect no longer depends on a single person or just a few people in the organisation. Similarly, a network has learned if something in the network has changed due to a lesson learned and if its participants have agreed to this change. It is often difficult to link such changes directly to the learning process (see, e.g., Riche in Learning in Networks: A Systematic Review of Public Administration Research, 2017, p. 18). Obviously, these three levels—individual, organisational, and network learning—need to complement each other. It is difficult to imagine a learning network without the individuals involved learning something as well. However, little is known about the interaction between individual, organisational, and network learning.

This chapter provides an overview of the conclusions of the research project on “Smart Transformations in City-Regional Law and Governance”. This study analysed the drivers, manifestations, and implications of hybrid city-regional governance. Hybrid city-regional governance is the kind of governance in which both public and private actors as well as public and private instruments go into the governance of a metropolitan area. The focus of the project was on “governance learning”, that is, the cognitive process in which individuals, in interaction, intentionally reflect on the process and procedures of multi-stakeholder decision-making. The data collection for the study included extensive document analyses, fifty-two in-depth interviews and five two-day workshops, called city-region labs, which involved representatives from four European city regions as well as local stakeholders. In these labs, participants from each of the four city regions collectively reflected on their experiences in dealing with the governance challenges that are particular to hybrid governance and, as a group, identified opportunities for improvement. The project succeeded in stimulating a collective learning process that drew on the participants’ experiences and research findings but cannot guarantee long-term effects.

Cities are increasingly challenged by complex problems nowadays, and local policymakers are called upon to cope with them with fewer resources and greater fiscal constraints. Urban Living Labs are a viable strategy for public administration to overcome traditional barriers to public sector innovation. This chapter analyses the Housing Innovation Lab (iLab) in Boston, an organisation created by the city administration to cope with increasing demand for affordable housing and specifically aimed at finding and testing new ways to develop, fund, and design houses for residents. Members of the Lab share the same methodological approach based on the “exploration, experimentation, and evaluation” template that is implemented in every project. Learning within each project team takes place through dialogue, discussion, and negotiation among partners. Combining a codified learning approach and stable coordination patterns with flexible participation and informal interactions among actors, iLab offers an interesting perspective on network learning in Urban Living Labs.

Gentrification is now widespread everywhere, changing the liveability, diversity, and equality of cities. As a phenomenon in urban development, it has been researched widely and extensively. The definition of gentrification, however, has recently become more diffuse as it takes on different forms and has different causes and effects in cities everywhere in the world. Gentrification is an irreversible process that may bring development and progress to neighbourhoods, but that may also involve eviction and inequality. This emphasises the need for equipping urban practitioners with an understanding of gentrification and with the ability to recognise the context in which it takes place in their own cities, as a first step to taking possible action, making improvements, and benefitting the liveability of cities and their communities. This chapter analyses a practice-oriented learning method developed for urban practitioners from various backgrounds and primarily Global South countries in an attempt to achieve this. The method was based on David A. Kolb’s experiential learning cycle, in combination with Robert Chambers’ rapid appraisals. Previous applications of the method in Amsterdam (2017) and Yogyakarta (early 2018) were considered, with a more in-depth evaluation of the learning experiences of practitioners in Rotterdam in late 2018. Generally, the method received positive feedback from participating practitioners, as well as useful suggestions for further improvement.

This chapter explores learning in City Deals, a Dutch policy programme aimed at accelerating transitions (i.e. long-term system changes), such as sustainable urban development, climate adaptation, and renewable energy. Within City Deals a diverse network of partners (ministries, local governments, companies, and/or social organisations) work together to find innovative solutions for complex issues in a non-hierarchical way and outside existing organisational structures. There is an inherent tension between the short duration of the City Deals individually, and the long-term goals they seek to address. To overcome this, the various learning experiences within the City Deals need to be safeguarded and the generated knowledge, insights, and experiences broadly shared. This chapter provides insight into the learning experiences encountered within the deals and the anchoring of these learning experiences within the organisations involved to stimulate or accelerate a transition. Social learning is considered any learning (either solitary or in a network setting) related to a City Deal. Organisational learning regards the embedding of the learning experiences in the organisation involved. This has the advantage of making the development less dependent on the individual. Analytically, this chapter focuses on the experiences of participants, using in-depth semi-structured interviews based on a combined framework of transition studies and network governance literature. This analytical framework matches the principles of the City Deals programme. The chapter concludes that learning experiences within the City Deals were largely social, rather than organisational, learning experiences. The participants considered working together in a diverse team and learning from each other’s perspectives as important learning experiences. They valued the access to their partners’ organisations and the insights on core capabilities within the network setting. The participants also discovered that working together on a non-hierarchical basis required balancing of traditional roles with new ones that emerged within the collaborative setting. The need for different, sometimes contrasting, roles created tensions between responsibilities. We found that while it may not be possible to eliminate such conflicts during a transition, transparency, and explicit agreements on responsibilities could assuage the process. As said, organisational learning proved limited. While the City Deals had official organisational support, high-level organisational commitment remained limited. This inhibited institutional penetration and the anchoring of learning experiences of the City Deals deeper in the organisations. We find that improvement of this organisational learning can contribute to long-term systemic changes.

This chapter explores policy evaluation that is used to inform new policy practice. Two reflexive methods for evaluating public policy practice—Learning History and Learning Evaluation—are introduced and discussed in a theoretical and practical sense. The potential value of these methods is discussed by showing their recent application to complex urban issues. The reflexive and constructivist nature of policy evaluation must lead to results that are recognised by target audiences and will lead to conclusions that can be supported by them. As such, the learning impacts of the study itself can be maximised. By deliberative inclusion of the target audiences, researchers can organise how they might productively contribute to the evaluation study at hand, without violating “common rules of good science”, or changing the evaluation instruments or results. Learning from evaluation refers to the wish to identify or initiate visible change, often presented, of course, as an improvement of the evaluated public policy practice and its artefacts (objectives, resources, relations, skills, etc.). Both methods appear to be capable of actively stimulating and facilitating learning for public policy practice through evaluation. Both learning evaluations and learning histories must be deployed in a learning manner. Through an iterative research process—of targeting, applying, reflecting, readjusting, and reapplying—in-depth insight into the evaluation issue will be gained from different perspectives, held true or relevant by the target audiences. For public policy professionals involved, both learning evaluations and learning histories appear to be safe research procedures for sharing their knowledge of and experiences with “what was going on”. Naming, shaming, and blaming of events, people, or agencies are avoided because the multi-perspective approach of both methods shows vividly that there are more sides to the story, taking the evaluation and the subsequent discussion away from conclusions that are too easy or too hasty.

This chapter describes and evaluates the pilot of a learning and group mentoring trajectory over a three-year period with city managers from ten cities in the Netherlands. The method resulted from discussions on the practice of local government assessments. The method has three steps: self-reflection, external reflection, and group mentoring. The approach was evaluated with the participants. Based on public administration literature, the chapter considers factors that could influence the learning process. Some factors stand out as general necessary conditions for a learning and group mentoring trajectory: safety, trust, preparation, time, willingness to learn, and credible peers. With regard to the structure of the network, group mentoring benefits from the structure of the network being kept informal but composed of participants representing formal organisations. Group mentoring in this context works best with a group of eight to fifteen people. An intermediate role or facilitator is needed to initiate, prepare, facilitate, and report on the learning process. Group mentoring is especially suitable for difficult and sensitive matters but can be used for other issues as well. It works well when relatively short answers suffice to show a way forward on a specific issue. Advice given mostly provides a perspective on how to act or how to treat a sensitive or complicated case. It does not work well when detailed technical descriptive advice is needed. It would be interesting to further test the approach in a setting involving other institutions, such as private companies, educational institutes, or housing corporations.

A city visitation is an independent assessment of a city’s performance and the quality of its primary processes, products, and services. It is performed by a temporary, external expert visitation committee, aiming to promote public accountability and learning and improvement. This chapter discusses the city visitations that were made to the Flemish regional capitals in 2011 as instruments of urban network learning. These 2011 city visitations were introduced by the Flemish government to evaluate the policy agreement it had signed with the Flemish regional capitals in order to manage the City Fund, an important element of Flemish urban policy. The visitation procedure involved self-assessment papers and a preparatory meeting with local stakeholders in each city, followed by on-site visits in which the visitation committee met with the city’s political and administrative officers. These visits addressed several topics of urban policy: overall performance and governance, both internally and externally in relation to local stakeholders, civil society, and other government levels; the planned social outcomes and strategic goals laid down in the policy agreements; contemporary social challenges, operationalised by two policy themes of choice; and the value of the City Fund in general. The visitation committee was chaired by academic experts and comprised a group of local government consultants and thematic experts chosen per city. The city visitations proved to be useful instruments to foster urban network learning at three levels. At the micro-level, cities learned about their own internal and external governance through the exchange of views, best practices, and policy recommendations in the visitation reports. At the meso-level, the visitations painted a picture of contemporary urban governance and its challenges in Flanders, whilst the regional capitals learned how to address important policy issues collectively. At the macro-level, finally, the procedure provided valuable insights into the way in which the different government levels interact.

Participatory reforms, the deliberative turn, and administrative reforms highlight the important role of online and offline participation in local governance. To become citizen-oriented, local governments have responded to these demands, and some have implemented platform for feedback (invited space). Different forms of online and offline participation, such as representative, direct, deliberative, and demonstrative participation try to influence local decision-making processes. These participatory channels can be divided into instruments for the planning of urban policies and instruments for the monitoring of local governance service delivery. As an example of crowd-sourced planning platforms, Participatory Budgeting processes have been analysed. As an example of crowd-monitoring processes, Fix My Street platforms have been evaluated. These two instruments were studied in two German cities to identify the success and failure factors of these instruments. Two levels of learning become clear: cities learning about different democratic and administrative innovations from other cities (intercommunal learning) and the city administration learning from citizens (responsive learning). Factors critical for successful learning are actors (the mayor as the driving agency), positive contextual factors (blending online and offline instruments), organisational culture (openness to advice and innovation), and process (transparency).

Between February and April 2018, two regional authorities and one city in Europe engaged in a peer-to-peer learning programme to learn about energy performance contracting, an innovative scheme for financing and implementing energy efficiency projects in the public building and public lighting sectors. These public authorities were the pilot participants of PROSPECT: Peer Powered Cities and Regions, a European Commission—Horizon 2020 project. PROSPECT aims to encourage the exchange of knowledge and experience on innovative financing schemes, such as energy performance contracting, to implement sustainable energy and climate action plans to deliver an energy transition in cities and regions. In this chapter, we present the development of a peer-to-peer learning methodology, highlight the lessons learned from the pilot implementation, describe the pilot participants’ learning outcomes, and examine the factors that may influence learning. From our experience in developing and implementing this learning programme, we highlight the importance of having intermediate organisations and leading facilitators in place; setting up pre-foundational engagements; enabling foundational and structured learning engagements; simplifying the process of reducing administrative demands; paying attention to language differences; addressing transaction costs involved; and diffusing learning to foster impact at scale. We observed learning outcomes ranging from cognitive and relational changes to skill development and action orientation, at the individual, network, and institutional levels in the short and medium terms. However, we have yet to monitor long-term learning outcomes. In this learning programme, factors that may have influenced learning included intermediate organisations, the role of a leading person, willingness to share knowledge, and clarity of the issue at stake. Future studies could further examine the learning outcomes of peer-to-peer learning programmes in the field of delivering energy transition in cities and regions.

Serious games have been hailed as particularly suitable learning technologies for unravelling complex urban issues and wicked problems. This chapter presents the main research findings from the development and testing of a serious game, called Energy Safari, which tackles the issue of local policy for the energy transition in the northern Dutch province of Groningen. While planners appreciate the learning and engagement potential of serious games, particularly for addressing the complexity of urban issues and large-scale transitions, games are not widely employed in practice, due to organisational and administrative constraints and lack of familiarity with the method. While engaging in a participatory game prototyping process, researchers, public administrators, and private sector and civil society representatives were able to access aspects of the energy transition outside their own disciplinary field. This enabled the research team to incrementally create an analytical model of the local energy policy and its social and technical ramifications, which were eventually implemented in the game. Learning during gameplay covered a variety of styles and goals, ranging from direct knowledge transfer to social and other forms of open-ended learning. However, a gender gap among players and a resistance towards long-term change were also observed. To summarise, despite some shortcomings, serious games cover several learning factors and can address complex issues while adapting to different network structures and participating stakeholders.

In this chapter, we show how simulation gaming can be used to experiment freely in urban development and how a variety of urban stakeholders learn about these developments in a complex environment. Simulation gaming is especially useful when the issue is a problem in a complex multi-actor system, in which sociopolitical complexity and technical design complexity need to be studied in an integrated and dynamic fashion. The Go2Zero game about the energy transition process at the local level was used to illustrate learning about the energy transition process at the local level. Based on this study, we conclude that participants of Go2Zero particularly learned about the interaction between stakeholders, working together, and the dynamics of intervention of each individual stakeholder at the system level. This chapter also discusses the factors that are critical in making simulation gaming successful. These are: the validity of the game, clarity about the issue at stake, the role of the client and the facilitator, the right number of players in a session, the creation of a safe environment to experiment freely and share knowledge, and a fair gaming session.

This chapter compares all international experiences presented in this book. All factors are revisited in a cross-case analysis. Some learning traps are discussed and an approach to move from intuition to learning to learn is presented.