Research agenda - part of the KIA Key Enabling Technologies 2020-2023

Authors Miguel Bruns Alonso, Mieke van der Bijl-Brouwer, Paul Hekkert, Caroline Hummels, Jos Kraal, Kees Krul, Geke Ludden, Tom van der Horst, Linda Rindertsma, Paul Rutten, Nynke Tromp.

An initiative of Hans de Bruijn - TU Delft/NWO Marco Hekkert - Universiteit Utrecht Paul Hekkert - Topsector Creatieve Industrie Tom van der Horst - TNO Janneke van Kersen - NWO Nico van Meeteren - Topsector Life Sciences and Health

In this agenda we present eight categories of KEMs that are indispensable in the context of tackling societal challenges and shaping transitions. Each category represents a collection of methods, processes and strategies related through the purpose for which they are deployed. For example, the category Behaviour and empowerment stands for all those methods and strategies that can be applied to develop an intervention with which (desired) behaviour can be influenced, adjusted or made possible. Although not an exhaustive list, these eight categories cover the main areas of KEMs for the realisation of the missions. These are the eight categories that are detailed in the subsequent chapters:

Vision and Imagination (Chapter 2) Every mission requires that we know where we are headed. Sometimes that goal is obvious, but more often it is necessary to design that goal, make an inspiring vision of the future visible and tangible by using imagination, and in doing so, give direction to change. KEMs in this category help map today's world, imagine new worlds, and view phenomena and problems differently.

Participation and co-creation (Chapter 3) Missions involve many players with diverse interests. From citizens and companies to governments and domain experts. You want to involve them in the process, for the knowledge and experience they bring to the table, to enable them to take the initiative and to achieve commitment and support. KEMs in this category help to engage stakeholders, to go through the process systematically, to analyse and understand the context of issues, and to develop new propositions.

Behaviour and Empowerment (Chapter 4) In order for a transition to succeed, a behavioural change is often required. For example, to eat less meat or to fly less. In addition, people must be enabled to make conscious choices and be empowered to take control themselves. KEMs in this category help develop, test and validate an intervention to change people's behaviour directly (via motivation) or indirectly (via influence).

Experimental environments (Chapter 5) Transitions are not easy to manage, and related issues are often surrounded by uncertainties and ambiguous information. In the early stages of the innovation development process, space is needed to experiment. Further down the process, there must be room to test and adjust the effects of developed interventions in simulated and / or real-life contexts. KEMs in this category help set up these experimental environments and provide methods of work and experimentation.

Value creation and upscaling (Chapter 6) Current societal challenges require effective interventions and upscaling of innovations in a relatively short term. The speed with which transitions can be realised goes hand in hand with the ability and speed to create new value for society. The (changing) relationships in ownership and profit play a role in this, and issues surrounding management and governance come into the picture. KEMs in this category help to structure this process, and to validate and test it at an early stage.

Institutional change (Chapter 7) In addition to the wishes and possibilities of citizens and stakeholders, the organisation in and around the contexts of transition issues also has a crucial influence on the desired changes. Institutional change is a response to technical and social changes and at the same time these changes can in turn bring about institutional change. KEMs in this category provide insight into the behaviour of institutions and help develop appropriate structures and procedures for changes.

System change (Chapter 8) Transitions require a transformation or overturning of an existing system. Systems are characterised by the fact that they are difficult to define and are unpredictable. Moreover, systems have a multitude of elements and (mutual) relationships and thus form a complexity that is difficult to control or change. Development for and on systems is therefore a dynamic issue. KEMs in this category help to operate in a system-oriented and future-oriented way, and to elicit debates and feedback.

Monitoring and effect measurement (Chapter 9) Due to the long horizon and the unpredictable nature of (changes to) systems, it is particularly relevant for transition issues to monitor and (intermediately) evaluate the effects of interventions. In this way, knowledge is gained about the possible effects of the manner in which an intervention was made, which can be directly fed back into the process, in order to support iterative further development and adjustment. KEMs in this category help to measure the effects of interventions and monitor the impact on the system.

The eight categories are conceptually easy to distinguish. However, methods in one category sometimes have properties related to methods in another category and / or methods from different categories are often used in combination. For example, we see that some experimental environments are specifically suitable for user participation and / or co-creation and a process of system change often cannot be done without a previously compiled vision for the future. The most common connections between the eight categories are indicated below. These connections don’t necessarily say something about the order in which the methods are ideally used in an innovation process. The nature of a chosen change process or transition strategy requires a specific sequence regarding the use of these KEMs.

The eight KEM categories are described in detail in chapters 2 to 9 of this agenda. In addition to an overview of the current (scientific) state of affairs in the development and application of KEMs, each chapter discusses the most important themes and questions that should be addressed in future research. This agenda is therefore explicitly a research agenda.

Global societal challenges, such as making the economy and society more sustainable, and an inclusive, healthy and happy society, require innovation. These large-scale and complex issues need a multidisciplinary approach, in which technological innovation goes hand in hand with social impact. The acquisition of fundamentally new insights for, and the application and development of key technologies and methodologies are indispensable.

With the renewed top sectors policy, the Mission-driven Innovation Policy, the government wants to use the innovative strength of the top sectors to tackle societal challenges. The top sectors focus on cross-sectoral collaborations between science, applied research, companies and civil society organisations. The Mission-driven Innovation Policy focuses on four themes: Energy transition and sustainability, Agriculture, water and food, Health and healthcare, and Security.

In order to take targeted and joint steps in tackling the societal challenges, concrete, measurable goals and ambitions have been formulated: the missions. Missions focus on the challenges and function as a point on the horizon. Based on the missions, the top sectors developed six Knowledge and Innovation Agendas (KIAs) that form the basis for programming groundbreaking research. In addition to the four mentioned themes, agendas have been developed for the overarching theme Social Earning Capacity and for the Key Enabling Technologies, including the key enabling methodologies outlined here. This last KIA thus provides the means to tackle the challenges mentioned in the other five mission-driven agendas.

Missions require major social change processes The missions focus on realising social and economic change processes. It is about the realisation of a complex whole of closely intertwined interventions[1], systems and institutions. This requires not only research and innovation, but also accompanying measures, such as legislation and regulations, and education aimed at behavioural change. There is no one-size-fits-all solution: missions differ and each mission requires a specific policy mix and approach.

The creation of missions requires a multidisciplinary, cross-sectoral and multi-stakeholder approach, which not only makes use of new technology, but also pays attention to psychological and social, organisational, ethical and cultural aspects. The knowledge to address these aspects is developed in disciplines such as innovation sciences, public administration and business administration, psychology, law, philosophy, behavioural sciences, economics and anthropology. There is an increasing need to apply that knowledge from the social sciences and humanities in formulating and realising the social missions.

These missions provide new contexts in which this social form of innovation must take place. The successful examples of previous major interventions, such as the Delta Works and the offshore wind farms, cannot be translated directly into the currently desired changes in their specific contexts. In addition, changes like these rarely take place as a linear process and the challenges are surrounded by uncertainties and ambiguous information. The missions require a transition strategy[2] in which policy processes and innovation processes are deployed in the right way and at the right time. Without making a choice or going into the exact nature of such a coherent strategy, we can state that instruments are needed to develop widely supported interventions, accelerate or scale up new solutions within such a strategy, and to realise system changes and breakthroughs.

1. Introduction to the agenda 3 1.1 Background: Mission-driven Innovation Policy 3 1.2 Key methodologies or KEMs 4 1.3 Categories of KEMs 7 1.4 Conditions and the deployment of KEMs 9 1.5 This agenda 11

2. Vision and imagination 12 2.1 Introduction 12 2.2 State of the art 12 2.3 Challenges and research questions 14 2.4 References 17

3. Participation and co-creation 18 3.1 Introduction 18 3.2 State of the art 18 3.3 Challenges and research questions 21 3.4 References 23

4. Behaviour and empowerment 26 4.1 Introduction 26 4.2 State of the art: perspectives on behavioural change 26 4.3 Challenges and research questions 29 4.4 References 31

5. Experimental environments 33 5.1 Introduction 33 5.2 State of the art: from modeling to experimentation 33 5.3 Challenges and research questions 37 5.4 References 39

6. Value creation and upscaling 40 6.1 Introduction 40 6.2 State of the art 41 6.3 Challenges and research questions 43 6.4 References 46

7. Institutional change 48 7.1 Introduction 48 7.2 State of the art 48 7.3 Challenges and research questions 51 7.4 References 54

8. System change 55 8.1 Introduction 55 8.2 State of the art 56 8.3 Challenges and research questions 59 8.4 References 61

9. Monitoring and effect measurement 63 9.1 Introduction 63 9.2 State of the art 63 9.3 Challenges and research questions 66 9.4 References 68

10. Methods in the Mission-driven Innovation Policy 69 10.1 Programming and KEM research 69 10.2 Methodological issues in the missions 70 10.3 Application in conjunction 71

About the development of this agenda 73 Colophon 74

This agenda mainly aims to point out where the strengths (existing methods) and weaknesses (knowledge gaps) lie and which opportunities / needs are most urgent to address in the short term. The further development of existing KEMs and the development of new strategies and methods will mainly take shape through application in concrete innovation processes (also see Chapter 10). Although this agenda does not address the meta-question of what makes a ‘good’ methodology, KEM development will also involve addressing more fundamental, methodological issues.

The eight categories elaborated in the document do not cover the entire methodological field, but mainly those domains that are particularly relevant to the Mission-driven Innovation Policy. This agenda is therefore not a catalog of all methods, strategies and processes with which change trajectories and innovations can be shaped. The agenda provides an overview of the available KEMs for the eight categories, the usability of specific methods in various transition issues, the scientific state of affairs within each category and what further research is needed. The agenda can therefore also be used as an entrance to the world of KEMs; a diverse world where change professionals can give and receive a great deal.

Every mission requires that we know where we are heading. Sometimes that goal is obvious, but more often it is necessary to design that goal, make an inspiring vision of the future visible and tangible by using imagination, thereby giving direction to change. KEMs for vision and imagination help map the current world, imagine new worlds, and view phenomena and problems differently. They provide support with questions such as: How do you design an inspiring vision of the future? How does the vision of the future help us to give direction to interventions now and in the medium term? How do you determine the steps towards a social mission? How do you bring the interests of stakeholders together and design a supported and desired direction?

This chapter focuses on KEMs for vision and imagination that can strengthen the Mission-Driven Innovation Policy in the Netherlands4. Many methods are already available and are already widely used. The introduction of the mission-driven innovation policy in particular requires a major change in thinking and methods. After all, it marks a turnaround in the innovation policy itself; from the generic stimulation of innovation to the targeted use of people and resources for a concrete goal, a mission. This is a new challenging task for all actors in the Dutch innovation system in which new methods for vision and imagination play an important role.

To develop interventions, systems or institutions that shape the process of social change, we use ‘instruments’ that direct and structure our way of working. By analogy with the key enabling technologies, we refer to this toolbox, or set of instruments, consisting of methods, models, strategies, processes and tools, as Key Enabling Methodologies (KEMs). This includes ways of working (together), dealing with problems and creating interventions; tools with which ‘change’ professionals, such as designers, policymakers or public administrators, are able to structure their work, give direction and realise impact.

Two examples of KEMs that clarify the nature and application of KEMs:

KEMs are enabling and thus provide a working principle for an integrative, change-oriented and design based approach

They are instrumental and indispensable in determining the desired change - or at least the direction of the desired change - and in bringing about that social change at the level of interventions, systems and institutions.

KEMs contribute to the integration of knowledge from the social sciences and humanities (for example knowledge about motivation, behaviour, ethics or organisations) with the opportunities offered by technological developments. In this way they support the development of useful applications and meaningful interventions.[3] In doing so, KEMs answer questions such as: how can interventions respond to the connections that social science theories reveal? How can interventions intervene in these specific situations to make people enthusiastic, involved, empowered or to influence their behaviour? How can one intervene in a system to bring about a desired change?

As the figure above illustrates, KEMs are enabling and facilitate the connection between technology and society. KEMs can be used to successfully implement a technology in a social context, but can also be applied to directly achieve that social goal, with or without the use of (new) technology. KEMs can thus help with the successful application of technology as well as guide its development.

Although KEMs are often developed at knowledge institutions, they regularly find their application in practice in a way that deviates from the prescribed way. For example, variants of existing and validated KEMs are developed and sometimes completely new instruments emerge from that process.

The nature of KEMs can vary widely. Some KEMs are generic in nature and - if properly applied - lead directly to new concepts, interventions or institutional changes. Other KEMs give direction and interpretation to a single and specific aspect of the intervention. Still other KEMs are more conditional in nature and provide steps in the process (for example, techniques for vision development, methods for involving end users). KEMs can therefore be used at different times and for different purposes in the innovation process.

Of course, the user of the method or process also plays a major role in the adequate use of KEMs. In addition to knowledge about the working principle of a KEM and the ability to select the right KEM for an issue, competences and skills are necessary to apply the selected KEM successfully. Proper use of a KEM requires the right skills and mindset, reflection and adaptability, and trust. This usually concerns tacit knowledge that a professional acquires through training and experience. Frequent trial and error with various methods in equally diverse issues and contexts ensures the development of intuition about when which method - or combination of methods - leads to successful results, and about how to mold a method for the specific situation. Finally, the use of KEMs often requires collaboration between different parties, and multidisciplinary thinking and acting. This also entails specific competences. To illustrate the role of KEMs in transition projects, we briefly describe three recent projects in which different KEMs are applied below:

New perspectives on agriculture and nature In line with the nitrogen crisis, a breakthrough is necessary to deal with the recurring tension between nature and agriculture. A team of specialists in the fields of design and organisational science works together with agricultural entrepreneurs, nature managers and conservationists and policymakers on new perspectives. These new perspectives must contribute to a system change in which vital ecosystems, businesses and areas go hand in hand. It is important in this regard that the government is explicitly part of both the problem and the solution through new policy. This is no easy task: political and social consensus is lacking and there is also no consensus about the underlying scientific knowledge. By means of experiments and co-creation, new values will set the entire problem field in motion.

Methods, processes and strategies are indispensable in the realisation of missions and transitions. They give the professional a perspective for action, make clear what to do and what not to do, which steps must be taken and which paths may lead to a desired result. At the same time, KEMs are not the whole picture. Many steps in a transition process can also take place without methods, based on knowledge and logic. Either intuitively, fed by years of experience, or simply through trial and error. KEMs are supportive, a resource. Sometimes the key to a breakthrough, but never a guarantee for success.

KEMs offer so-called ‘change’ professionals support in tackling transition issues. In light of this, it is important to be aware of the context-dependent nature of KEMs. The contexts in which methods are applied and the way in which they are deployed ultimately determine the quality of the intervention and thus the effectiveness of the method. These contexts are formed by all kinds of variables related to the nature of the issue, the involvement of users, consumers and citizens (quadruple helix) and the situation in which the issue is being tackled.

The mission-driven transition challenges at hand cover a broad spectrum of subjects and contexts within which the desired interventions must land. Variables that characterise these issues and contexts and are relevant to the choice of KEMs to be deployed include:

• the nature of the intended impact: from incremental to radical impact. The energy transition is an intended radical change; financial incentives to get people using renewables are often incremental in nature.

• the nature of the intervention: from instrumental to institutional intervention. With instrumental interventions the direct goal is to bring about a change in behaviour; Institutional interventions involve, for example, new or stronger supervisors.

• the level at which the intervention takes place: from individual to collective level (also referred to as micro and macro level). Installing a smart meter is an intervention at an individual level (household); a new regulation to protect privacy is an intervention at a collective level.

In addition, the situation in which the challenge is tackled is relevant for choices in the way in which the chosen KEMs are applied. Variables are for example:

• the degree of politicisation;

• the degree of technological control;

• the degree of substantive uncertainty;

• the degree of social attention and urgency;

• the degree of interdependence with other issues;

• the degree of willingness to change or expected social resistance;

• the degree of involvement of the client and other stakeholders, and

• the availability of time and resources.

The conditions that are formed by these variables, and the choices that are made on the basis thereof about the use of KEMs (both the choice of KEMs and the way in which they are used) determine to what extent a specific KEM - or a combination of KEMs - leads to successful results in specific issues and situations. Although theoretically any method can be used for any issue and in any situation, some methods are more effective for certain issues and situations than others: the conditions for which the KEM is designed partly determine the situations in which this KEM comes into its own and has impact. The success of the application of KEMs therefore depends on many variables and therefore requires a professional approach. It is important that the variables are taken into account and that attention is always paid to the conditions of the issue, the context and the situation.

As outlined in the introduction, the Mission-driven innovation policy marks a change in thinking about innovation policy from generic (‘let a thousand flowers bloom’) to specific policy (goal-oriented, mission-driven), and this is a new challenging task for all actors involved. This new policy requires, among other things, a new or renewed use of methods for vision and imagination. It is precisely these that can play an important role in this visionary policy. At the same time, this change can also be a driver for scientific innovation of these methods and their foundations.

Foresight & Imagination With regard to methods for Foresight & Imagination, the question is what exactly is a representation of or vision for the future. How is it designed? And can we say something about the quality?

Do we not have more and other means at our disposal (for example thanks to the internet and artificial intelligence) to conduct explorations? And will we be able to see where it is going faster?

In many cases visions for the future arise from various forms of foresight studies.

Is there a relationship between the quality of the exploration and the vision for the future? For example, is it a mix of fact-based analyses and appealing images? When does it appeal to the imagination, when does it mobilise a vision? To what extent do artistic aspects play a role? Does that depend on target groups?

And: why are certain visions of the future dominant? Can that be traced back to specific basic characteristics?

There are also opportunities to make a better link between foresight and innovation systems. For example, by developing foresight methodologies that link the organisational short term (exploitation) and long term (exploration). Last but not least, we see the pursuit of paradigm shifts as a fundamental and challenging ambition. Recognising a true paradigm change requires in-depth analysis and conceptual thinking, rather than speculation on the future (so philosophy, more so than Star Trek). The aforementioned H.G Wells also confirms this. He was a powerful and fearless conceptual thinker. His visions of the future are so different because they are anchored in such deep understanding. Paradigm shifts are not an end in themselves, but they do get to the heart of what we try to pursue with vision and imagination: a challenging new view of the world and the future.

Shared Vision Development How do we recognise desirable visions, implying that subjective, ethical, moral and also politically charged aspects are involved? And how do we deal with this? How does a desirable vision (for example a mission) contribute to valuable social change processes? And by whom and how is determined what is valuable? A related question is how vision and imagination become embedded in society. More specifically aimed at the mission-driven innovation policy: how can missions for which there is broad support in society be realised? How can methods based on vision and imagination involve society in the development of missions? Pathways How can visions of the future actually be linked to decision-making? Which organisational and institutional factors play a role in this? How can you focus methodologies for vision and imagination on specific forms or moments of decision-making? Who has the power to create and embed visions? This touches on the question of who makes choices in the mission-driven innovation policy and how these are established. How can visions support strategic choices at national, regional and European level being made faster and more effectively, given their interdependence?

Research challenges across the clusters of methods The ambition is to make a better connection between the research into and the application of KEMs for vision and imagination and the Mission-Driven Innovation Policy. This requires interaction between the initiators of missions and the mission-driven innovation policy (‘what does it add to what I am already doing?’) And the providers of methods (‘what questions are there that could possibly be supported more effectively?’). Below is a proposal to give substance to this.

Context-specific research into and application of KEMs for vision and imagination There are opportunities to conduct more context-specific interpretative research in the context of the mission-driven innovation policy. Addressing visions for the Energy Transition requires a completely different approach than for the development and upscaling of the Quantum Internet. In one area, for example, the solutions are reasonably tangible and imaginable, while in the other area they are virtually elusive. There are big differences between the actor fields and how they get moving. Careful alignment with and anticipation of these contexts is therefore of primary importance.

Context-specific research for (spatial) design issues, for example, can be carried out by co-designing research questions with citizens in combination with analyses of the processes by which visions spread through society. For example, by setting up an analytical framework to answer questions about 'techniques of futuring', the social practices that bring people together and orient them towards certain visions and future-oriented actions.

Cross- and transdisciplinary research into and application of KEMs for vision and imagination There are also opportunities to better link activities in the field of vision and imagination that are already implicitly or explicitly carried out in the context of the mission-driven innovation policy. KEMs for vision and imagination are researched and applied from a wide variety of disciplines. There are opportunities to apply these discipline-specific methods to other disciplines and areas of innovation (cross-disciplinary). For example, (product) design methods such as context mapping and systems mapping that could be used more broadly on the complex societal challenges of mission-driven innovation policy.

There are also opportunities to intensify transdisciplinary research in collaboration from different disciplines. For example, by linking design methods with methods from intervention research (change management). Or interdisciplinary methods in which art, science and technology come together.

In general, the idea is to develop a transdisciplinary language and methodology for vision and imagination that simultaneously bridges macro and micro perspectives and diverse application areas. This can result in a joint (transdisciplinary) body of thought and the bringing together of vision developers from different areas. Which in itself can give an impulse to the development of entirely new innovation practices that further strengthen the mission-driven innovation policy.

New tools for vision and imagination The tool and methodology development of KEMs for vision and imagination also has a 'hard' or - in other words - a practical side on which a lot of innovation is possible and necessary. Until now, the mission-driven innovation policy has been little visible in the broad public domain. Increasing the attention and public support for mission-driven innovation policy requires, for example, conscious and targeted use of new digital technology and social media.

New tools and methods to communicate and involve actors can be of decisive importance in this.

Connections to Other KEM Categories The KEMs for vision and imagination have common ground with the KEM categories described in the other chapters. Achieving optimal synergy between the KEM categories is a challenge in itself, both in the development of KEMs and in their application in practical situations. For example, there is a clear relationship between the approaches described above for shared vision development and KEMs for participation and co-creation in Chapter 3. The framing of a joint innovation assignment can be started with joint vision development and then further developed in co-creation processes. develop. Similarly, vision and imagination can be the first impetus for behavioural change and empowerment processes (Chapter 4). In Experimental Environments (Chapter 5) can be very focused visionary concepts are developed and tested. In addition, it is possible to use KEMs for monitoring and effect measurement (Chapter 9) also validate the actual impact of visions in practice (scientifically), a challenging perspective.

Wherever possible, it is recommended to pursue these kinds of interactions between KEM categories in the development and implementation of KEMs for vision and imagination.

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In the field of vision and imagination, we distinguish roughly three clusters of methods: foresight & imagination, shared vision development and pathways.

Foresight & imagination By foresight, we mean the methods that aim to map, analyse and understand the autonomously developing future and environment. There are different forms of exploration.

Explorations of the future, also called futures studies or futurology, are those studies that seek to understand ‘what is likely to continue and what is likely to change." Part of this discipline strives for a systematic and pattern-based understanding of past and present and toward determining the likelihood of future events and trends. For example, one of the early thinkers was H.G. Wells (1901), who predicted the atomic bomb at the beginning of the 20th century. Or Rachel Carson who started the environmental movement with The Silent Spring (1962). Scenario analysis (e.g. Kahn, 1965; Wack, 1985), trend analysis and delphi can also be included in this group. In addition, explorations can focus on all possible more specific areas, such as technology explorations (Jansen, 1994) and learning curves, market or economic explorations, or environmental or landscape explorations. Although explorations are becoming richer and more exhaustive due to the greater availability of data, the key challenge remains how to deal with uncertainties that the future by definition holds.

Imagination, or imaginative power, is the ability to evoke mental images, ideas and / or feelings, without being perceived by the senses (Szczelkun, 2018). Imagination creates space to interpret reality and to look for new forms of looking and thinking. The imagination is the basis for inspiration and new ideas and plays an important role in the learning capacity of people (Hajer, 2017).

Imagination can thus be seen as an important basis for innovation and development.

Well-known methods of mobilising the imagination are scenario thinking, visualisations and storytelling, but films (science fiction) and the arts in a broad sense also give shape and content to imagination.

Shared vision development These are methods that aim to develop a perspective of a desirable future and thereby arrive at visions that are supported by actors. These are desirable visions on, for example, new products and services, technology or specific societal challenges. Developing desirable visions implies that subjective, moral and also politically charged aspects are at stake. Resistance to a particular innovation strategy or the degree of politicisation is often also related to the fact that innovations are in various cases also political interventions that will influence people's living environments. A good example of this is the Mission and Man on the Moon thinking, put on the agenda by Marianne Mazzucato (2013), among others.

On the one hand, the methods in this category help to give meaning to the desired visions in effective ways. In the (product) design field, these are Design Fiction (speculative design), Technology Pyramid, Visual Thinking, Frame Innovation (Dorst, 2015) and Vision in Design (Hekkert & van Dijk, 2011). On the other hand, these approaches also support the development of support for visions, for example for Co-design, Design for Debate, Critical Design, Future Labs / Experience Labs and World Student Challenges. The Hyperloop is a good example of the latter.

Pathways (Ex ante) Impact pathways map out how and through which mechanisms and actors impact is achieved. In other words, they do not so much support the determination of the mission / vision, but the mapping of the way to it. The concept of theory of change plays an important role in the ex ante way of mapping impact. KNAW (2018) describes theory of change as: “... a causal framework that provides insight into how and why a change process will take place and how the steps are related in a specific context. The starting point of the theory of change is not the output of a research project, but the intended social impact or possibly the outcome. To this end, concrete goals are formulated and the assumptions underpinning them made explicit.

Subsequently, it is analysed which activities are necessary to achieve this impact and which conditions must be met at a particular moment. Based on this, it can also be determined which stakeholders should be involved - an approach that is further elaborated in the Participatory Impact Pathway Analysis (Blokdyk, 2019).

Well-known methods for developing pathways are Backcasting (Robinson, 1982), forecasting, roadmapping and, more specifically, Technology roadmapping (Hasberg et al., 2012). Characteristic elements of the approach of Mission-Driven Innovation Policy (Goetheer et al., 2018) and Transition Management (Loorbach, 2007) can also be counted as part of the pathway group.

Participation and co-creation processes are characterised by the collaboration of a range of stakeholders / actors from various disciplines, sectors, with various roles, including other aspects such as geographic and cultural backgrounds, social vision, paradigm and various perspectives (e.g. technical, economic , socio-cultural, institutional) play an important role. These diverse stakeholders benefit from a systemic approach, based on the values ​​and motivations of the actors, thereby doing justice to the complexity of the whole. Co-creation can help them act strategically in developing interventions, model the system to understand the dynamics, facilitate and stimulate reflexivity and reflection during the process, and many other things. The complexity and plurality makes the need for supporting methods great. The wide range of such methods seems to be divided into six headings, two of which are based on defining and connecting the various stakeholders, two on collecting perspectives and giving meaning to them, one heading on developing new propositions, and one section on the self-managing process of a multitude of stakeholders.

1) Determining the stakeholder landscape These methods focus on exploring, determining and mapping stakeholders, their skills and expertise, their area of ​​influence, and how they relate to each other in a partnership. This may include all parties directly involved and beneficiaries of the project, but also indirectly involved, disadvantaged parties or potential stakeholders who are unable or unwilling to participate. Examples of these methods are:

• Actor Analysis and Multi-actor Perspective enable the exploration of the actor field, interests, roles, the field of influence, and demands placed on the process by actors.

  (Hermans & Thissen, 2009; Avelino & Wittmayer, 2016).

• Value Flow Model supports the identification, linking and balancing of relevant stakeholders and the values ​​that are important to each of them, in a complete system (den Ouden & Brankaert, 2013).

• Strategic Navigation Methodology supports strategic dialogue and decision making for business and market development related to complex projects that require multi-stakeholder collaboration (Brand et al., 2020).

2) Realisation and strengthening involvement and connection These methods are aimed at realising cohesion and involvement, among other things, by involving stakeholders, strengthening joint responsibility, being able to contribute personal values, and giving room to personal motivation. Therefore it is important to experience together what the different motivations are to participate, what binds and separates everyone, and how people actually experience the feeling of belonging and connection. Examples of such methods are:

• Engaging Catalysers are specific tools that introduce stakeholders through their skills, in order to increase empathy, respect and mutual connection (Trotto & Hummels, 2013).

• Empathic co-design is a specific form of co-design aimed at strengthening empathy, for example when vulnerable groups are difficult to involve (Smeenk et al., 2018).

• Participatory Video allows stakeholders to interview and film each other in order to create a people-oriented collective partnership (Nemes et al., 2007).

3) Collection and exchange of different stakeholder perspectives These methods focus on the collection and exchange of personal perspectives, experience, knowledge and skills in order to obtain a multiform collection of perspectives on the complex challenge. This ranges from the micro level of individual experience to the macro level with questions such as ‘what do we as a society think is justice, democracy and desirable?’ Examples of such methods are:

• Context mapping facilitates people in a creative and collaborative way to collect insights about needs, wishes, (im) possibilities, motivations and experiences of ordinary people, to use them in designing (Sleeswijk Visser et al., 2005).

• Participatory / Embodied Sensemaking is about collaborating with stakeholders to create new, shared meaning, with an eye for the embodied / situated setting for meaning making (Jaasma, 2018; Hummels & van Dijk, 2015)

• Constructive Conflict Methodology is aimed at clarifying and learning about the diversity of perspectives on unstructured (policy) issues, in which there is disagreement or uncertainty about the facts and values ​​(Cuppen, 2012).

4) Joint meaning making and decision-making through analysis and modeling These methods focus on generating overview, insight and joint agreement and decisions through the analysis, mapping and modeling of the collected data. Examples of these methods are:

• Group Model Building supports stakeholders in jointly unraveling problem-cause relationships and building a picture of ‘the system’ (Vennix, 2001).

• Participatory Multi-Criteria Decision Analysis (MCDA) / deliberative decision analysis supports stakeholders in weighing various options against a diverse set of criteria in order to arrive at a weighted decision (Salo & Hämäläinen, 2010).

• Participatory Multi-Modeling supports decision-making on complex issues with great uncertainties, in which input is collected for the multi-model and the unlocking of system knowledge, followed by design, programming and proof of concept simulation (Wurth et al., 2019).

5) Co-design of scenarios, propositions and innovations These methods focus on jointly exploring and developing new value propositions, innovations, future scenarios in response to the societal challenge. There are several methods, such as:

• Participatory design and co-design have developed a foundation of methods for several decades. Participatory and co-design focus on the participation of a multitude of actors and stakeholders in design processes (Schuler & Namioka, 2017; Brandt et al., 2012; Sanders & Stappers, 2008).

• Multiple Scenario Development, Scenario-based Design and Futuring focus on the development of various scenarios and shared fictional expectations, aimed at and based on uncertain future developments (Schoemaker, 1993; Anggreeni & van der Voort, 2009; Hajer, 2017)

• Value Sensitive Design aims to systematically involve humanitarian values of all stakeholders in the development process. The conceptual phase explores which values exist, to whom they apply and to which extent they are inconflict.

6) Progress of the collaborative process These methods focus on the progress and organisation of the entire process. How is the entire process organised? Who are the driving forces? Who takes responsibility for what? What decision-making power do the various stakeholders receive and take? Is transparency essential and how is this arranged? How are more people slowly being involved in the process of systematically changing regular policy and processes? Methods for this are for example:

• Transition arena is a setting in which initially a select group of participants and later coalitions of stakeholders develop alternative visions and solutions through a systems approach in the lee of regular policy.

• Multi Gains Approach is about exchanging interests and finding a win-win solution. It supports the design of an appropriate process with associated rules based on intended goals. In combination with process monitoring, interim process adjustments can be made (Susskind & Field, 1996).

• Transdisciplinary research focuses on transcending one discipline-specific approach by integrating a diversity of approaches to create new conceptual, theoretical, methodological and translational innovations (Hirsch Hadorn et al., 2008).

Missions involve many players with diverse interests. From citizens and companies to governments and domain experts. You want to involve them in the process, for the knowledge and experience they bring in, to enable them to take the initiative, but also to achieve commitment and support and to increase the chance that transitions will actually take place.

Co-creation can be seen as any act of collective creativity (Sanders & Stappers, 2008); as the partnership between different actors to jointly realise value (Osborne et al., 2016; Brandsen et al., 2018). Co-creation requires participation, whereby the form of participation and the role of the participant within the partnership may differ. KEMs in this category help to engage, connect and streamline the process, analyse and understand the context of issues, and develop new propositions. Co-creation can be initiated for various reasons: for example, to ensure that the various requirements and limitations are identified (functionality / interests), because complementary knowledge, resources or competences must be brought together (this is essential given complexity), or because a value chain and good innovation can then be developed (value or innovation-driven) and / or because the stakeholders have the right to be involved (value-driven). The process can be aimed at viewing the current situation or have a focus on the desired (future) situation.

The KEMs in this category answer questions such as: how, when and which stakeholders should be involved in a transition process? How to deal with the diverse interests and insights of citizens, government, industry, experts, etc.? How do we make the pros and cons, and the give and take of the various stakeholders visible? How do we stimulate and support initiatives where co-creating partnerships are initiated bottom-up, for example through citizen initiatives? How do we make them effective? How do we deal with ownership of transition issues? How do we determine that we involve the right set of stakeholders in the right stages? Who has an interest in this social innovation? And who directs and has the authority to do so, and how does this influence the questions that are being worked on? But also, when is participation not a good idea?

In order for a transition to succeed, a behavioural change is often required; for example to eat less meat or to fly less. And to do so, people must be able to make conscious choices and take control, but also in others, in addition to the citizen or consumer, behavioural change may be necessary to achieve transitions. For example, at the care provider (who needs to discuss nutrition, rather than medicine), or the retailer who has to switch to a different proposition, or a teacher who will provide sustainability education. The context in which behaviour is established is a reason for favoring certain behavioural alternatives over others. This context is colored by customs, individual beliefs, social norms and practices, as well as by the design of environment, information and products. Consider, for example, how information on packaging, but also the presentation of healthy or unhealthy snacks in a school canteen, and even of these choices being available at all, can influence the food choice.

KEMs in this category can help determine the target group and other stakeholders that play a role in the transition, map current (undesirable) behaviour, and determine the behaviour that needs to be changed (the so-called 'target behaviour '). In addition, KEMs in this category help develop, test and validate an intervention. In this context, an intervention is any (orchestration of) design of services, means of communication or (digital) products that aims to change behaviour. Interventions can be overt and explicit, aimed at strengthening knowledge or changing attitudes, but can also be less overt and use more implicit influencing strategies such as framing or nudging. Finally, KEMs in this category can also be aimed at mobilising and activating change processes by citizens themselves: citizen empowerment. They answer questions such as: what type and what degree of influence is desirable and morally acceptable? How do you set up mechanisms that enable individuals to take control of their own actions and / or to take action together to bring about change in society?

Anggreeni, I., & Van der Voort, M. (2009). Supporting Scenario-Based Product Design: The First Proposal for a Scenario Generation Support Tool. Proceedings of the 19th CIRP Design Conference – Competitive Design, Cranfield University, 30-31 March, 475-482.

Brandsen, T., Steen, T., & Verschuere, B. (2018). Co-production and co-creation: engaging citizens in public services. New York: Routledge.

Brandt, E., Binder, T., & Sanders, E. (2012). Tools and techniques: Ways to engage telling, making and enacting. International Handbooks In: Jesper Simonsen & Toni Robertson (Eds.), Routledge International Handbook of Participatory Design, Edition 1. Routledge.

Cuppen, E. (2012). Diversity and constructive conflict in stakeholder dialogue: considerations for design and methods. Policy Sciences, 45(1), 23-46.

Den Ouden, P. H., & Brankaert, R. G. A. (2013). Designing new ecosystems: the value flow model. In: C. de Bont, P. H. den Ouden, , R. Schifferstein, F. Smulders, & M. van der Voort (Eds.), Advanced design methods for successful innovation (pp. 189-209). Den Haag: Design United.

Friedman, B., Kahn jr., P. H., & Borning, A. (forthcoming). Value Sensitive Design and Information Systems. In P. Zhang & D. Galletta (Eds.), Human-Computer Interaction in Management Information Systems: Foundations. M.E. Sharpe, Inc: NY.

Hajer, M. (2017). De macht van verbeelding. Oratie Universiteit Utrecht.

Hermans, L.M., & W.A.H. Thissen (2009). Actor analysis methods and their use for public policy analysts. European Journal of Operational Research, 196(2), 808-818.

Hirsch Hadorn, G., Hoffmann-Riem, H., Biber-Klemm, S., Grossenbacher-Mansuy, W., Joye, D., Pohl, C., Wiesmann, U., & Zemp, E. (2008). Handbook of Transdisciplinary Research. Springer Science + Business Media B.V.

Hummels, C., & Van Dijk, J. (2015). Seven principles to design for embodied sensemaking. Proceedings of the 9th International Conference on Tangible, Embedded and Embodied Interaction (TEI '15), January 16-19, 2015, Stanford, CA, USA, ACM: New York, 21-28; New York: ACM.

Jaasma, P. G. (2018). Exchanging perspectives: designing for public sphere. Eindhoven: Technische Universiteit Eindhoven.

Nemes, G., High, C., Shafer, N., & Goldsmith, R. (2007). Using participatory video to evaluate community development. XXII European Congress of Rural Sociology, Wageningen.

Osborne, S., Radnor, Z. & Strokosch, K. (2016) Co-Production and the Co-Creation of Value in Public Services: A suitable case for treatment? Public Management Review, 18(5), 639-653.

Salo, A., & Hämäläinen, R. P. (2010). Multicriteria decision analysis in group decision processes. In: Handbook of group decision and negotiation (pp. 269-283): Springer.

Sanders, E., & Stappers, PJ (2008). Co-creation and the new landscapes of design. Co-design, 4(1), 5-18.

Schoemaker, P. J. H. (1993). Multiple scenario development: its conceptual and behavioral foundation. Strategic Management Journal, 14(3), 193-213.

Schuler, D., and Namioka, A. (2017). Participatory Design: Principles and Practices. CRC press (original publication 1993).

Sleeswijk Visser, F., Stappers, P. J., Van der Lugt, R., & Sanders, E. B. (2005). Contextmapping: experiences from practice. CoDesign, 1(2), 119-149.

Smeenk, W., Sturm, J. A., & Eggen, J. H. (2018). Empathic handover: how would you feel? : handing over dementia experiences and feelings in empathic co-design. CoDesign, 14(4), 259-274.

Susskind, L., & Field, P. (1996). Dealing with an angry public. The mutual gains approach to resolving disputes. New York: Free Press.

Trotto, A., & Hummels, C. C. M. (2013). Engage me, do! Engagement Catalysers to ignite a (design) conversation. In DPPI ‘13 Proceedings of the 6th International Conference on Designing Pleasurable Products and Interfaces. Newcastle, September 3-5, 2013, 136-145.

Vennix, J. (2001). Group model building: Facilitating team learning using system dynamics. John Wiley & Sons.

KEMs in this category are based on models and theories from different disciplines (including social, cognitive and environmental psychology, organisational psychology, communication sciences and sociology). We can place theories from the different disciplines on a continuum that extends from the individual to the broader context (individual - social structure - environment, see also Niedderer et al., 2017). While theories from cognitive psychology are often aimed at a better understanding of the individual and how the individual's actions are determined, theories from sociology and organisational psychology are more aimed at a better understanding of broad social structures and how these influence our daily lives and actions. At the other end of the continuum, we find the theories from environmental psychology in which a better understanding of how the environment influences our behaviour is central. In the diversity of KEMs in this category, we see the philosophies of the different disciplines reflected. On an individual level we can influence behaviour by supporting people in prioritising the desired behaviour. The pedometer is an example that we all know. It makes us (individually) aware of how much we move.

An example at the level of social structures is social proof. For example, think of how web shops almost constantly point out what your peers think of the product you are viewing or what else they have bought. An example at the last level, more environmentally-oriented behavioural change, is choice architecture, which is based on a default in the environment that prescribes the desired behaviour. The printer that defaults to double-sided and black and white printing (and thus promotes more sustainable behaviour) is often mentioned. But a city that is designed for pedestrians and not for motorised traffic is also an example of a design that follows this strategy. Further analysis of KEMs aimed at behavioural change shows that they are by no means always limited to one of the levels of influence. They can, to some extent, combine several levels. Not least because the design of products, services and systems - as a contextual factor - mediates the interaction between people and their environment.

Examples of methods Behavioural change, theories and tools In a recent review, Kwasnicka and colleagues looked at what, according to 100 different theories, contributes to lasting behavioural change (Kwasnica et al., 2016). They then group their results into 5 categories: 1) change in the environment, 2) interventions on motivation, 3) support for self-regulation, 4) support for psychosocial resources (resilience, optimism), and 5) habit formation. We give a number of examples within these categories here.

As an example in the first category, we can look at the theory of nudging, originating from the discipline "behavioural economics", which combines theories from psychology and economics (Thaler & Sunstein, 2008). An example is how the design of our environment can influence our willingness to recycle. A waste container design can make recycling very clear and easy or provide information about how many other people in the area choose to recycle. See also Varotto & Spagnolli (2017) who discuss the effectiveness of different strategies in a meta-review.

If we look at examples in the second category, interventions on motivation, we see, for example, strategies that support behavioural change in a more conscious way and are, for example, based on the self-determination theory (Ryan et al., 2006) and rewarding ( van Dooren et al., 2019). Support in self-regulation (category 3) can, for example, happen through providing feedback (Casal et al., 2017) on behaviour and goal setting (Strecher et al., 1995). Examples of strategies in the fourth category, resilience support, are pats on the back and emotional support from the environment. A number of strategies in this category have been implemented in the Stopadvisor intervention (see Brown et al., 2014). In the last category, habit formation, focusing on how one's own identity is seen is a strategy (see e.g. Hoie et al., 2010).

Selection of theory / tool It is important to select within the many theories and KEMs based on them, so that the desired transition that must start with a behavioural change is consciously chosen. It is essential to consider the desired mechanism of change: how persuasive (strong) must / can / may the influence be and what level of influence is desired (see also Tromp et al., 2011). A number of KEMs offer guidance when selecting from a wide variety of theories and tools. A nice overview that shows the relationships between Behaviour Change Techniques (BCTs, behaviour change strategies) and Mechanisms of action (MoAs) is the Theory & Techniques Tool developed within The Human Behaviour Change Project (2020). Mechanisms of Action are the processes that take place within a person that initiate behavioural change. Behaviour Change Techniques are the strategies to initiate these mechanisms of action in humans (from the outside).

The Behaviour Change Wheel (Michie et al., 2014) is another example of a tool that brings together multiple behavioural change theories and allows you to discover fruitful strategies for developing interventions and policies for behavioural change by playing with the dimensions of the wheel. The BCW model is used to determine which behavioural intervention offers the best solution for a particular problem. The model analyses the motives for a certain behaviour by looking at Capacity , the Opportunity, and the Motivation. Based on this, it can be determined which intervention function(s) and behavioural techniques are necessary to influence the behaviour. The BCW model is used both to analyse the behavioural issue (explore and orientate) and to systematically choose a strategy and develop a behavioural intervention based on this. Lockton's Design with intent cards (Lockton et al., 2010) provide a wonderful and broad overview of the different ways of influence and how these can be expressed in design.

Empowerment and engagement are concepts that have long been used in various fields of application. For example, we can speak of engagement with one's own health or care, but also of engagement with sustainability and measures that promote sustainable behaviour. There are also concrete examples in these different domains. There are neighborhood initiatives in which people collectively and locally generate and share their energy or, for example, collect solar panels. There are also initiatives in which people buy a piece of land together, hire someone to grow food on that land and thus work together towards a change they want, and to a more sustainable model for the production and consumption of food.

The field seems unanimous in their assessment that there are actually sufficient methods for participation and co-design. The challenges for this category exist on a different level. These can be summarised in three themes: what, who and how?

What are the societal benefits of this method and can this be demonstrated? One of the main challenges seems to be identifying potential success criteria for participation and co-creation. What is the added value of this way of working together, and which underlying principles contribute to possible success and social impact? This is not only about individual methods, but mainly about which combination / approach works, why and in which situations? How do we determine what value to create? How do we determine what contribution we can make to major transition issues?

Who do we need on board and what is their input, expectation, responsibility and connection, or how can this be established? What contributions can actors make to local challenges and major transition issues, and what are the mechanisms to achieve successful participatory co-creation? How can we jointly steer, guide and adapt these complex, long-term and dynamic processes, whereby new responsibilities and processes may need to be introduced to achieve successful transitions? How can we tackle complexity together without resorting to our own mechanisms and hobby horses? What new legal forms and forms of business and communication are required to cooperate successfully?

How do we get a clear and mutually reinforcing landscape of participatory co-creation? A frequently heard challenge is connecting the different methods and insights from the various interdisciplinary and trans-disciplinary fields, and developing a common language to be able to do this. How do we prevent fragmentation between specialisms, boundaries between disciplines and other dividing lines that stand in the way of a trans-disciplinary mutually reinforcing, co-creating collaboration that seems so essential for addressing the complexity of our transition challenges?

It is important that we not only do research on transitions and participation, but also actually change our own practice and attitude and that we become participatory and co-creating in our daily work and life: to practice what we preach.

Methodical research questions These challenges lead to various research questions, aimed at, among other things, the actors and stakeholders, the method, context, organisation, the system, the content and the effect of participation and co-creation, including:

• Stakeholders: How do you determine which people are involved in the various stages of the process? How do you involve them, in the short and longer term? What competences and expertise do stakeholders need for certain transition issues? How do you create shared understanding, empathy, connection, responsibility? How do you achieve long-term commitment?

• Impact and effectiveness: How do we determine whether the methods really work in messy and diverse practice, and not just in simple situations? How do you generalise lessons from interventions in complex systems? What are the stimulating and hindering factors that determine whether value actually arises in co-design and participation processes? Can causal connections be found between approach and success / failure?

• Perspectives and assumptions: How do we make explicit whether and how the transition is viewed from various complementary perspectives (social, economic, technical and institutional, for example experience and business perspective)? How can methods be linked so that integration takes place, as current methods often focus on a single dimension? What are the (normative) assumptions and objectives in processes of participation and co-creation and how do they influence the interpretation of the processes? Which contextual factors such as culture, degree to which knowledge is implicit, future orientation, etc. influence the co-creation process?

• Various scales and structures: What is the effect of interventions on a small and large scale, and in the short and long term? How do we deal with different time-space scales (for example, shifting societal challenges from national to local politics has disadvantages, but also opens up new possibilities)? What is the role of politics and power? How can participation be anchored in institutional and other relevant structures?

Need in the future for ... As mentioned, many methods already exist for the various aspects that are important in this category, including to identify actors, to identify conflicts and to work with a group of complementary stakeholders . That is why there is a particular need for integration and connections between all the different approaches and for 'meta' methods, so that we gain tools and insight into:

• When and in what form co-creation or participation (g) is a useful approach,

• which combinations of methods to choose for which context (e.g. based on of proven impact in previous applications),

• how to adapt various methods to the specific context in which they are used,

• how we ensure that the outcomes are distributed as well and fairly as possible among all stakeholders, including those indirectly involved, disadvantaged parties or potential stakeholders who are unable or unwilling to participate.

In addition, there is a need to explore and develop the craft of co-creation and participation. The same method can work out in completely different ways, depending on the people involved and the context, which requires (learning) specific competences to make these types of processes run successfully. Finally, most knowledge and most methods are applicable to processes of relatively short duration. Societal transitions, however, require patience. There is therefore a need for methods that support longitudinal participation development processes.

From mission to behavioural change In order to bring about behavioural change to support transitions, it is essential to better determine which ingredients are necessary for public support for the missions. What is needed to motivate people to adopt interventions? Part of this can also be determining what the most important psychological factors are that encourage people to take social action / citizen engagement. Attention to the (in) visibility of the problems and the legitimacy of the status quo are important conditions for change.

Effectiveness of methods Although we have many theories, methods and tools, it appears time and again that behavioural change is not easy. See, for example, Ludden and Hermsen (2020) for an overview of types of interventions that have been used for lifestyle change and a discussion of why they are often not effective (enough). Besides the fact that behavioural change is a complex process, there is a lack of knowledge about when, which method / intervention works best and why, partly due to the wide variety of methods within this category. To investigate this, systematically conducted studies are needed to evaluate the effect of interventions on actual behaviour. It is also important to get a picture of the underlying process (mechanisms of action). We also still have relatively little knowledge of how behavioural change can be sustained in the longer term.

Ultimately, more knowledge about when which methods are effective could also lead to a situation in which we have standard solutions and tools for less complex situations surrounding behavioural change. A challenge here is to develop / refine KEMs that can be put to good use by many people in developing interventions and that have a solid scientific basis. Current KEMs are often still too complex and do not make the translation from theory to intervention clear (actionable) enough. More complex situations may require approaches and solutions led by specialists (behaviour change designers) who can work on these issues within a network of stakeholders.

Personalisation of behavioural change / interventions In behavioural change at the level of the individual, more and more use is made of the possibilities that personal data offer to personalise an intervention. Knowledge about when and whether personalisation of interventions is effective (leading to sustainable behavioural change) is still largely lacking. Also, little is known about effective ways of personalising, for example how to link this to personal characteristics. These questions are also relevant for interventions that do not focus purely on an individual but on social structures - for example couples and families / organisations. Also interesting is the development of adaptive interventions that personalise contextually (JITAI, Continuous Tuning Interventions).

Where in the system? In the introduction to this category, we discussed that interventions can be used at various points in a system (for the citizen vs for the care provider / teacher). An important challenge is that there is a lack of knowledge about where a change / intervention can best be implemented. How do we determine at what level a transition must be initiated to be effective and how do the behaviours of the various stakeholders interact? How do we prevent the behaviour of different groups from having an opposite effect? A second important question is how combinations of interventions that are deployed at different levels can be combined and what effects we can then expect. Can we combine interventions in the environment with interventions at the level of the individual and does that make the interventions more effective or transitions more likely? For example: my app also uses location-specific data and tells me at the station where I can find something healthy to eat. Knowledge and methods on how we can develop this type of combination interventions are lacking.

With regard to grassroots initiatives, we lack knowledge of how to grow changes that have been achieved locally. How do we shape the step from local initiatives to actual change in the system? Are local initiatives growing from regional to national to global? Where do we encounter barriers in this?

The KEMs described here are categorised from research on large-scale and complex systems, up to the impact of specific interventions on the individual. Research is done through models of reality, field research and observations in specific contexts. They provide insight into the effect of interventions and offer a perspective on how people deal with their (new) reality. In addition, we describe methods that provide insight into the way in which the individual experiences his or her daily life. Of course, science still makes extensive use of laboratories in which humans are observed while they are subjected to behavioural experiments. In transitions, however, behaviour is more complex due to relationships between individuals and dependence on environmental factors. There is therefore a need for environments that are more open and therefore less controllable. In addition to the categorisation of complex systems versus the individual, a distinction can also be made based on the time dimension. Models sometimes try to imagine a new reality, for example in a virtual world. Research is also being done into the future in the present. By means of exhibitions and the creation of prototypes that can be experienced, visions are presented that give people a critical / different view of reality.

In the design and engineering sciences, transitions are often addressed by research by design or by design research. In this process interventions are conceived, executed, analysed and reflected on. In their book on design research in practice, Koskinen et al. (2011) distinguish the lab, the field and the storefront as research domains with their variety of underlying theories and methods. The model of reality is not addressed in this, because the engineering sciences are often concerned with artifacts. Given shifts in the design domain to networked systems, data-driven methods and social design, not only analysis but also synthesis will become increasingly important for this approach. The artifact will no longer only be seen as a separate element, but as a connector between the stakeholders in an environment.

Virtual environments When systems have a major social impact, they cannot be easily regulated. In addition, interventions in this type of system are often irresponsible or too expensive. Examples are safety-critical systems. In these cases, one can decide to model the system. Based on a broad knowledge and experience of the factors that influence a system, models can be created that simulate reality. These KEMs are therefore mainly focused on simulation. An example of this is Digital Twins. These are digital replicas of living or non-living physical entities, where the digital replica adapts based on data from the physical world (El Saddik, 2018). The digital replica can be used as a test environment for monitoring. For example, when maintenance is necessary in complex infrastructural or industrial installations, to research processes. One can also try to predict the possible impact of interventions by adjusting certain variables in the models.

Another context where models of reality are applied is in economics, where the impact of interventions is studied by means of, for example, Equilibrium Analysis. Furthermore, Sandboxes offer isolated digital environments in which developers can create and test new concepts without interfering with other (critical) parts of a project. There are also virtual environments that can actually be experienced by people, the so-called Virtual Reality. These virtual environments offer the control of laboratories, but can also simulate complex processes such as an industrial production line or airport traffic control. In virtual environments, for example, using methods such as Serious Gaming (e.g. Mayer et al., 2014), collaboration can be studied and training courses can be realised. The limitation of these virtual environments, however, is that to date they mainly serve the visual and auditory channel and still to a very limited extent the other senses.

Everyday life Today's connected and data-driven systems and the link with artificial intelligence make it increasingly easy to observe human behaviour in daily life. Methods such as Crowdsourcing, in which both sensor data and other user information are acquired via, for example, the mobile phone, offer a view that interferes minimally with daily life. From software development, the method is Perpetual Beta, in which the implementation of systems is always in a test phase, and developers make continuous interventions. It allows early design iterations to be implemented in the real world and uses online channels to gain feedback from users and improve designs. Perpetual Beta is used, for example, in urban development (Fredericks et al., 2019).

In addition to acquiring data by mobile phones, use can also be made of so-called Technology Probes, specially designed artefacts with sensors and possibly actuators that are connected to the internet and can therefore exchange data from the environment. This allows the creation of experimental environments in physical and / or virtual environments that are part of society. These so-called Experiential Design Landscapes serve as a playground for in-situ design research by multi-stakeholder teams (Peeters & Megens, 2014). Existing products and services can also provide contextual data from the environment. This is already widely used in the business community for the development of new products and services. At Philips Design, for example, the Data-enabled Design method is used, in which sensor data from physical and digital products is combined with qualitative data from users. In this way, designers obtain detailed and nuanced contextual, behavioural and experiential insights from daily life (Van Kollenburg & Bogers, 2019).

In daily life there are also various experimental environments in which large, possibly more homogeneous, target groups come together, the so-called Pilot Grounds, Field Labs and Living Labs. User-oriented methods are used in these environments and open innovation is often stimulated. They are used to observe and measure, build and validate prototypes, and address complex challenges in as many real-world situations as possible. Many labs are linked to so-called Smart City initiatives around Amsterdam, Rotterdam and Eindhoven in particular. The environments are linked to daily activities. However, they offer more control than everyday life because they are often bound by environment or time. In City Labs, citizens, researchers, students, technologists, businesses, NGOs, entrepreneurs, teachers and policymakers come together (e.g. Scholl & Kemp, 2016). An example of this is NEMO Kennislink, where, in the context of the Science Museum, co-creation is used to develop solutions for the future of the Amsterdam metropolitan region. In addition to cities, regional applications can also be considered: in the Brainport region, for example, a stretch of motorway and several streets have been brought together in the Helmond Smart Mobility Living Lab where traffic research can be carried out.

Living Labs can also be linked to specific target groups, such as athletes, by turning a sports complex into an experimental environment. Or doctors, nurses and patients in a hospital. They can also be temporary, such as festivals. Prototypes can be tested and experienced during festivals and a lot of data can be generated or feedback can be obtained in a short period of time. A festival is seen as a temporary mini-society with challenges in areas such as energy, waste, logistics, water and food. Innofest, for example, is an organisation that offers entrepreneurs the opportunity to conduct research at various festivals. On the other hand, during the GLOW festival in Eindhoven, researchers observed how light can influence the routing of large groups for crowd management (Corbetta et al., 2018). Finally, Policy Labs (Olejniczak et al., 2019) are environments where government and citizens come together to explore innovative ideas. People hope to achieve social impact through citizen participation and a changing government culture. However, there is limited coherence between the methods used in the different labs. The effectiveness of these environments on policy change has not yet been sufficiently proven and - due to their short existence - it is not known whether these labs are sustainable. However, the advantages are that the feasibility and scalability of initiatives can be tested in a short time and in a relatively flexible manner and that they offer a safe environment for co-design and participation.

Workshops / manufacturing environments In these environments, making is central. This can focus on the here and now, by enabling people to create. In the Maker Movement (Dougherty, 2012), people in environments such as Fab Labs can create artifacts. To this end, knowledge is shared about, for example, production processes, models and software code. This may also lead to new research initiatives such as Citizen Science (Irwin, 1995). By enabling a large group of people to develop specific products to carry out measurements, such as an air quality meter, public data can be generated on a large scale. By linking the various measurements, the action perspective of the research community and thus knowledge production is increased through public involvement. Workplaces also promote bottom-up initiatives and encourage self-determination by bringing together cultural and economic practices.

Making can also be used in the arts, design and science for a critical reflection on technology in society, so-called Critical Making is based on Critical Design (Dunne, 1999). Speculative Making of Art Science creates a hybrid form of art and science, both of which have a unique ability to shape our understanding of the world. The collaboration provides new insights for both and leads to new hybrid forms of knowledge and presentation. Artistic research offers room for subjectivity that can lead to generically valid principles through the use of performative and speculative research methods. This type of research is often linked to the aforementioned Showroom Approach (Koskinen et al., 2011). The experimental environments that are linked to this are exhibitions and museums or Future Labs.

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Innovations often arise at the interface of different disciplines. The experimental environments, where these disciplines can find each other, are an ideal place to get started. However, cooperation must be facilitated, and there is an important role for the creative industries, which can bring together stakeholders and stimulate creativity and creation by means of co-creation and participation methods (see also Chapter 3). Unfortunately, the effectiveness of experiments in the described environments on policy change and transitions has not been sufficiently proven, and little is known about the sustainability of the environments. For example, what is needed to make the step from experiment to implementation? In addition, the interdisciplinary approach to experiments also leads to paradoxes, which result in a number of challenges and research questions that could be placed on the agenda for this KEM. We distilled a number of challenges, with related research questions. First, a number of practical questions with regard to the design and interaction between the participants in experimental environments, and finally a number of questions that focus on validity, and thus also link to other KEMs in this agenda, such as monitoring and effect measurement.

Design There is a great diversity of environments and methods for designing experimental environments. Several organisations and networks are also involved in both the design and participation in the experiments, and knowledge is needed about the systems that must be set up to extract the relevant data. Since many of the environments described take place in daily life, it is important to carefully consider the role of participants in the study. Reflection plays an important role in the development of the environments and can be addressed at different levels. Participating in experiments in daily life may have an impact on the behaviour of actors who are in or use the environment, because they have to learn to deal with new situations. This is related to the attitude of a reflective practitioner (Schön, 1984) who reflects on actions and a continuous adaptation of the environment. The following questions can help define common frameworks for the different experimental environments.

• What conditions must an experimental environment meet in order to generate new routes and directions?

• How are actors stimulated to contribute to and provide feedback on large-scale development and implementation of prototypes?

• How is information secured, clustered and made accessible?

• How do actors experience a continuous experimental form and change in their daily life?

• When and how can experiments from environments be scaled up?

Ethics Many of the questions above regarding the role of the actors in an environment, also lead to discussions about ethics and values. These are therefore a second challenge. When interventions are made in daily life, a very diverse group of actors must be taken into account, all of whom must be sufficiently involved and heard in developing a picture of the future.

• When are experiments legitimised?

• How do we ensure that (different) public value (s) are safeguarded?

• How do we deal with knowledge production and innovation within planetary boundaries and how directive do these limitations become?

• How do we deal with a society that is in a continuous experiment?

• What does the research and design process look like when it relates to transformative innovations?

Time dimension A third challenge relates to the time dimension. First of all, it is important to consider when experiments take place. The zeitgeist must also be taken into account. There is also a conflict between current environments and future environments. It is (virtually) impossible to evaluate new propositions in a future context, and this is made even more difficult by the complexity and continuous dynamics of society. To what extent can people imagine that interventions are experiments, and are they able to envision how the proposition will affect their future actions? Especially because in the future the situation of both the person and the environment can change completely. A major scientific challenge is therefore to evaluate technology and interventions in the making in a world in the making, especially if propositions have been developed with the aim of achieving an impact in the long term.

• How are constants and variables determined in an experimental environment in development?

• How do you research the suitability, meaning making and significance of technology in the making related to future, complex societal challenges?

• How do you acquire insights about experiences aimed at an unknown future context?

• How can we make experimental environments suitable for the future?

• How can an experimental environment test a new route and direction for ultimate feasibility and desirability?

Validity The final challenge concerns the validity of the described experimental environments. A point of discussion that is raised from different values ​​and frames of reference. While certain groups of scientists have a need for control, there is an opposing view from the creative industries that places importance on involvement and application in society. This creates a paradox, because a society cannot be modeled and therefore does not provide the control required for particular scientific research. There is therefore a need for different experimental environments, with different levels of control.

• How can we push the boundaries of ecological validity while maintaining experimental control in everyday life?

• What is the design, structure and validation of interdisciplinary and trans-disciplinary methodologies and practices when so many stakeholders are involved in the research process?

• What happens when society is involved as a researcher and how do we validate citizen-driven knowledge production and innovation in contexts such as Citizen Science?

• How do you address and investigate complexity, ambiguity and continuous change, where even the research methods and results are not stable, because their meaning also changes over time?

• Where does the experiment end and reality begin?

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KEMs in this category help set up experimental environments, in virtual environments, everyday life and workplaces. They answer questions such as: how do you set up an experimental environment? What conditions must an experimental environment meet? What degree of imitation is needed? What should collaboration with stakeholders look like in projects in this setting?

The current state of methodology development for value creation and upscaling of innovative services and applications is to a large extent a reflection of the development of thinking about science, technology and innovation policy. This means that the methods that emphasise the creation of economic value by (networks of) companies on the basis of (the upscaling of) innovations still play a prominent role. In doing so, they focus on individual companies, value chains and networks of companies and on regional and national innovation systems. Over the years, however, there has also been a development in which mission-driven innovation themes are introduced.

For example, the Business Model Canvas introduced by Osterwald and Pigneur (2010) is still an important tool for companies to develop their value proposition and to gain insight into the alignment of their business activities with customer needs or renewed insights into the core values ​​that drive the organisation itself ( purpose). In cases of innovation of the business model and the portfolio, this often leads to business model re-development: adjusting the value proposition, the business model and realising the created value because of a new customer base. This includes the Brand Driven Innovation by Roscam Abbing (2010), which connects brand, innovation and design to help companies build people-oriented brands that match their vision and values. Within these approaches, methodologies are often used that are derived from the design discipline or science, such as the principle of the customer journey or user journey: going through the steps of a (potential) user from consideration of purchase to eventual use, so as to discover how a (broader) group of users can be served (Følstad & Kvale, 2018). Another example is (service) design thinking, in which, through an iterative process, a greater eye for and understanding of end-user problems and situations is obtained, in order to gain insight into the way in which design results can influence their specific contexts (Cross , 2013).

Research and development of methods to innovate and scale up in the context of networks is quite advanced. Several conceptual frameworks, methods and tools are available. The concept of ecosystem plays an important role in this (see, for example, Adner, 2012). Methods are mainly used to understand the complexity of multi-stakeholder settings and to create a basis for shared values, goals and actions. Stakeholder analysis provides insight into actors who can exert an important stimulating or counteracting force on innovation and upscaling. Another known method in such situations is agent based modeling. One method to map out the value network within a consortium and to ensure alignment, for example, is the value case methodology (Dittrich, 2015, Dittrich et al., 2015).

Frame analysis is also used for a better understanding of underlying values ​​in different actors. In line with these approaches, is the business model radar. In principle, this is a multi-stakeholder business model approach based on the so-called service dominant logic.

‘S-D logic is essentially a value co-creation model that sees all actors as resource integrators, tied together in shared systems of exchange – service ecosystems or markets. In this way markets are characterised by mutual value propositions and service provision, governed by socially constructed institutions.’ (Vargo, 2011, p220).

A so-called value-in-use approach is central to the elaboration of a joint idea of ​​and for value creation. More specifically, an approach referred to as orchestrating innovation (Valkokari et al., 2017) that helps design, set up and run an innovation hub, often a strategic public-private partnership. The approach includes a general reference business model for all variants of an innovation center (including an experimental environment) and training for the leader of such an initiative.

Approaches and methods of value creation and upscaling that fit within the framework of transformative innovation often touch upon themes such as sustainability and circularity. One of the contributions that has laid an important foundation was that of Tukker (2004) in which he tests eight product-service systems on their environmental value. In an extensive literature review, Bocken et al. (2019) provide an overview of circular business innovation tools (see also: Lüdeke-Freund et al., 2016; Lüdeke-Freund et al., 2019). In our country, various researchers and professionals are active in developing services and products that build on this, including in the CIRCO project and within design companies such as Active Cues that develop products for more inclusive healthcare. In both cases, value creation is involved in combination with upscaling, which in these cases mainly has the character of replication.

Other developments that are relevant to the development of value through transformative innovation are so-called collaborative business models that can be developed and realised within the scope of a transition (CBM4T) and the increasingly emerging commoning models, in which different independent actors (individuals and organisations) can work together. manage a resource and further develop it with the aim of creating optimal common use. Complexity theory can be of value for methods aimed at multi-actor value creation, which are also relevant here. A characteristic of methods for value creation and upscaling aimed at transformative innovation is that they have an interdisciplinary foundation. They are often developed in a field that is developing: transition studies.

Institutions play a crucial role in initiating and bringing about transitions. Heavily institutionalised systems can thwart transitions, while other institutions - or the absence thereof - can significantly boost innovation. Although there is no unambiguous definition of the concept of institutions, they are often seen as the rules of the game. These rules - formally seen as laws and regulations and informally as norms and values ​​- find meaning in facilitating and coordinating interaction between individuals and organisations. In doing so, they hold various possibilities, limitations and conditions that can ultimately influence the effectiveness and lifespan of transitions. The games are often played in different political, economic and social arenas, but often also in between.

The central question in this category is how institutional change can contribute to achieving a better connection with desired transitions. On the one hand, institutional change is a response to technical and societal changes, but at the same time these changes can in turn bring about institutional change. KEMs in this category belong to this dual dynamic and offer insight into the behaviour of institutions, in order to determine which institutional arrangements can best match which societal challenges.

KEMs therefore help with questions such as: how can policy and regulatory resources be used to guide transitions? How do you design the associated organisation, network rules, and behaviour? What leadership is desired in transitions? But also: which institutional arrangements ensure that transitions can take place spontaneously and then move autonomously? How to deal with new forms of governance such as network and self-government? And what ultimately ensures social acceptance of transitions?

KEMs mediate between technology and its use and application, including in (design for) services of goods or in broad social applications at the level of cities, regions and societies or even internationally. All this mainly to stimulate transitions that are of value to society as a whole or a significant part of it. This includes new forms of value creation that are not only effective in an economic sense, but have just as much influence in a cultural sense, or are at the service of ecological information (cf. Rutten et al., 2019, 100-117). Its nature is reflected in the United Nations Sustainable Development Goals, but also in its mission-driven innovation policy[1]. Current societal challenges require effective interventions in the short term. The urgency of the present tasks is great and makes rapid upscaling of innovations necessary.

In the value creation and upscaling category KEMs help to structure this process, and to validate and test it at an early stage. They answer questions such as: how can economic, cultural, societal (such as sustainability) and social values ​​be combined and integrated? How can thinking shift from transaction and product thinking to thinking in terms of sharing, services and access? How can value be protected and cashed in? How do you ensure upscaling and acceleration of value creation and how is new knowledge optimally converted and used?

Value and policy frameworks The way in which the concept of value functions in the context of the mission-driven innovation policy shows a shift compared to previous policy frameworks. According to Schot and Steinmueller (2018), there have been three framings since WWII from which science, technology and innovation policy has been shaped. Specific and time-bound innovation systems have been cultivated and set up from each of these policy frameworks.

The initial starting point, in the first distinct policy framework, was that new knowledge development, in particular in the field of technology, should serve the development and growth of the (competitive) strength of companies that thereby create economic value and bring about social prosperity. In the second framework, which developed from the era of the oil crisis, the emphasis was on the promotion of national innovation systems. The aim was to promote (national) competitive clusters of activity, based in part on an excellent knowledge infrastructure, which generates economic value and ensures prosperity for citizens within countries and regions. In this context, the main focus was on competition between countries. The primary focus in these two first frames is economic, whereby certain negative externalities, for example in the social field or environment, are mitigated or perhaps even removed with the help of ex post interventions. The problem here is that the returns resulting from the upscaling of innovations are collected long before possible ecological effects manifest themselves. In that case, the proceeds of innovations are privatised, while the costs that fall later have to be borne by the community. Schot and Steinmueller (2018) argue that this is no longer tenable today. Economic value is no longer central in the new framing of science, technology and innovation policy. It is mainly about bringing about social transitions that encompass the economy, but also focus on other forms of value. In particular social and cultural, but also and especially ecological (Schot & Steinmueller, 2018). The mentioned authors therefore state:

‘Our core proposition is that the existing R&D and national systems of innovation frames for science, technology, and innovation policy, are unfit for addressing the environmental and social challenges’. (Schot & Steinmueller, 2018, 1561-1562).

They argue in favor of an innovation policy aimed at transitions (transformative innovation policy), but note that the policy frameworks that were dominant before, are still present in the current policy field and are of value in certain cases.

In the Netherlands too, the mission-driven innovation policy shows the development of a policy aimed mainly at strengthening primary economic value creation. Although the objective to strengthen the competitiveness of our country is still high on the cabinet agenda. In the context of the mission-driven innovation policy, companies and sectors, just like citizens and civil society organisations, are held accountable for their ability to contribute, in a broader sense than just economically, to innovations that are necessary to tackle urgent social themes and challenges. The knowledge development required for this requires a multidisciplinary approach, investments that go beyond technology development and are aimed at, among other things, social and cultural aspects that enable the broad application of that technology in socially supported solutions. The focus on innovation processes (agency) of (networks of) companies broadens to a broad social system of sometimes changing actors, depending on the mission and the domain that is central. Value creation is broader than the realisation of economic returns of (networks of) companies or an increased gross national product, while upscaling takes the form of realising transitions at the level of society or important parts of it and is seen much less in terms of for example economies of scale. This means that upscaling approaches the nearby concept of diffusion, which can take all kinds of forms and has been developed in line with the work of Everett Rogers (1962). The role of the government is also changing. It will play an important coordinating and guiding role in determining and defining missions and the targeted investment of resources in knowledge development to enable social transitions. Citizen engagement plays an important role in the definition of missions in this process (cf. Mazzucato, 2014; Mazzucato, 2019).

Adner, R. (2012). The wide lens. What successful innovators see that others miss. New York: Penguin Books.

Bocken, N. M., Short, S. W., Rana, P., & Evans, S. (2014). A literature and practice review to develop sustainable business model archetypes. Journal of cleaner production, 65, 42-56.

Bocken, N. M., De Pauw, I., Bakker, C., & van der Grinten, B. (2016). Product design and business model strategies for a circular economy. Journal of Industrial and Production Engineering, 33(5), 308-320.

Bocken, N. M., Strupeit, L., Whalen, K., & Nußholz, J. (2019). A review and evaluation of circular business model innovation tools. Sustainability, 11(8), 2210.

Cross, N. (2013). Design thinking. Understanding how designers think and work. New York & London: Bloomsbury Academic.

Dittrich, K. (2015). The value case methodology: A methodology aligning financial and non-financial values in large multi-stakeholder innovation projects. Delft: TNO.

Dittrich, K., Koerts, W., Berkers, F., Beckers, J., & Montalvo, C. (2015). A value case approach for analysing goal alignment in multi-stakeholder networks: the case of sustainable product manufacturing in the electronics industry. Rome: DRUID Conference.

Følstad, A., & Kvale, K. (2018). Customer journeys: a systematic literature review. Journal of Service Theory and Practice, 28(2), 196-227.

Hillebrand, B., Driessen, P.H., and Kollet, O. (2015). Stakeholder marketing: theoretical foundations and required capabilities. Journal of the Academy of Marketing Science, 43, 411-428.

Lüdeke-Freund, F., Massa, L., Bocken, N., Brent, A., & Musango, J. (2016). Business models for shared value. Network for Business Sustainability: South Africa.

Lüdeke‐Freund, F., Gold, S., & Bocken, N. M. (2019). A review and typology of circular economy business model patterns. Journal of Industrial Ecology, 23(1), 36-61.

Mazzucato, M. (2014). De ondernemende staat. Waarom de markt niet zonder overheid kan. Amsterdam: Nieuw Amsterdam.

Mazzucato, M. (2019). Governing missions in the European Union. Brussels: European Commission. DG for Research and Innovation.

Oskam, I., Bossink, B., & de Man, A. P. (2020). Valuing value in innovation ecosystems: How cross-sector actors overcome tensions in collaborative sustainable business model development. Business & Society, 1-33.

Osterwalder, A., & Pigneur, Y. (2010). Business Model Generation: A Handbook for visionaries, game changers and challengers. Hoboken New Jersey: John Wiley & Sons.

Rogers, E. (1962). Diffusion of innovations. New York & London: Free Press, MacMillan.

Roscam Abbing, E. (2010). Brand driven innovation. AVA Publishing.

Rutten, P., Koops, O., & Visser, F. (2019). Monitor Creatieve Industrie. Nederland, Top 10 steden, creatieve bedrijven en beroepen. Hilversum: Media Perspectives.

Schot, J., & Steinmueller, E. (2018). Three frames for innovation policy: R&D, systems of innovation and transformative change. Research Policy, 47(9), 1554-1567.

Tukker, A. (2004). Eight types of product–service system: eight ways to sustainability? Experiences from SusProNet. Business strategy and the environment, 13(4), 246-260.

Valkokari, K., Seppänen, M., Mäntylä, M., & Jylhä-Ollila, S. (2017). Orchestrating Innovation Ecosystems: A Qualitative Analysis of Ecosystem Positioning Strategies. Technology, Innovation Management Review, 7(3), 12-24.

Vargo, S. L. (2011). Market systems, stakeholders, and value propositions. Toward a service-dominant logic-based theory of the market. European Journal of Marketing, 45(1-2), 217-222.

In a recent article, Van Bueren and Klievink (2017) describe five institutional challenges: 1) a fragmented decision-making structure (as a result of decentralisation and deregulation); 2) the increasing dynamics in decision-making (whereby institutions transform and break down), 3) the rise of the private equity firm; 4) the declining role of knowledge in policy processes (accompanied by a shift to data-driven methodology); and finally 5) the expanding policy discussions.

While these challenges - often fueled by societal transitions and technical innovations - follow at a rapid pace, institutional change is often inherently slow. There is therefore a constant danger that existing institutions no longer match the new reality or offer insufficient room for transitions and innovation. At the same time, institutional voids can also arise, where there is no appropriate institutional framework to address and resolve the issue in question (Pelzer et al., 2019). Innovative companies such as Uber and Airbnb often take advantage of such gaps to launch new technology and business models. On the one hand, they disrupt institutions, but they also elicit a reflexive process that can lead to new institutions. In other cases, there may be institutional pressure, a challenge can then be addressed from multiple regulatory frameworks. The question then is which framework is used and under what circumstances a new framework can be created.

As a result of these constant challenges, we must look to new ways and methods of institutional change. This can be done through deliberate interventions, but also often happens through processes of emergence, evolution, and serendipity. In reality it is mainly a combination of conscious and unconscious action. The challenge for policymakers is how to steer institutional change under dynamic, complex and uncertain circumstances. While different solutions exist, each lurks an apparent dilemma. For example, how to deal with institutional inertia versus highly dynamic change? Loosening institutions and allowing them to move with them can offer a solution, but at the same time it can also undermine mechanisms of institutional stability (such as the constitution). Transformational and rapid change can be an effective means of closing institutional voids, but often inevitably leads to frictions with existing institutional structures.

Research questions The challenges described above raise new research questions. A small selection of these questions is:

• How can we design mission-driven innovation policy so that it is both effective and legitimate for those involved?

• What is the role of new organisational forms in mobilising resources, commitment and knowledge about societal problems and possible innovative solutions?

• What is the role of leadership in bringing about institutional change, and what new forms of leadership are needed for this?

• How can successful practices and institutions be transferred from one context (domain, sector, region, time) to another context?

• How can institutions on the one hand adapt to technological dynamics and on the other hand retain their desired guiding effect?

• How can a radically new solution to a societal challenge obtain support from those involved?

• How can institutional arrangements that promote transitions be designed in collaboration with citizens and stakeholders?

Need for new methods The institutional environment in which transitions take place has become increasingly diverse and dynamic. New and experimental methods can help to learn from institutional change, such as living labs that gain new insights into the microprocessing of change. New methods can build on the aforementioned methods, such as incremental change, institutional logics and comparative methods. This can lead to new insights into the institutional mechanisms that determine the effectiveness and lifespan of transitions. For example, what could cause existing power structures that have an interest in maintaining the status quo to be subverted? Or understand why many attempts at desired social change fail and only a few are successful. This means that we must also distinguish between aspects of institutions that are changeable and negotiable, under what conditions, how, and by whom? An important aspect in this is the time factor, which requires methods that go beyond a snapshot and offer the possibility to observe and monitor for a longer period of time. At the same time, historical insights can help by providing insight into how current societal challenges have been solved in the past. After all, innovation is timeless.

In addition, there are still many steps to be taken within the design methodology for institutional change that can ensure a better connection with transitions. One of the options for this is technology assessment and participatory monitoring, in which citizens or other stakeholders are involved in monitoring the effects of interventions. This also includes new methods that are specifically aimed at network governance and that can promote cooperation between different actors and sectors. It can ensure an increase in trust between parties and ultimately more support for innovations. Various initiatives have recently emerged from the government, such as the new Environmental Act or the discussed Right to Challenge, which provides a rich breeding ground for developing new insights and methodology.

Finally, there is a great need for methods that can integrate insights from emergence and design methodology. While promising steps have been taken for both over the past three decades, they are often unrelated. In addition, institutional methodology is spread over various disciplines such as economics, political science, and sociology. Integration is also desirable here. The energy transition is a good example of the fact that many solutions can no longer be approached from a single discipline. For the time being there are a multitude of analysis methods, but the field of consciously developing a systematic framework is sparse.

The developments in the significance of knowledge and innovation for the economy and society, as reflected in the changes in the policy frameworks outlined above, require a partial reorientation of methods and instruments to create social value and give substance to diffusion and upscaling of successful applications. This does not mean that existing methods have become obsolete. They often deserve adjustment and recontextualisation. In addition, there are a number of new challenges that require new methods to be developed.

First of all, the concept of value in the context of innovation for social transformations must be further elaborated and refined, focusing on broadening it beyond the until recently dominant economic interpretation. In doing so, it is necessary to no longer treat the aforementioned negative externalities (such as environmental damage or growing inequality in society as a result of the operation of the economy and market) as annoying residues, but to incorporate them fully into the valuation of new services, applications and systems and can be seen as part of societal challenges and transitions.

Another important challenge that has already been partly addressed in the context of innovation in networks and value chains is the further development and validation of collaborative models for value creation. This is important in the context of social transitions in which coalitions necessarily extend beyond the economic domain and involve social stakeholders more than before.

Methods to investigate the underlying value systems of stakeholders and to ensure alignment are crucial here in the context of innovation for societal transitions. In particular, the inclusion of users and the involvement of civil society in a broad sense is crucial, partly regarding diffusion and upscaling. Mazzucato (2019) formulates this challenge on the basis of the question of how to involve citizens in processes of co-design, co-creation, co-implementation and co-assessment of social missions. She also wondered what capabilities and tools the public sector needs to foster a dynamic and innovative ecosystem, including the skill of civil servants to enable experimentation and help governments work outside of their traditional silos.

Relatively little is known about the organisational capabilities required to create value in an ecosystem with multiple stakeholders. Value creation in such a complex context raises specific dilemmas that require special skills (see, for example, Hillebrand et al., 2015). Little is known about the dynamics of sense making: how do stakeholders jointly determine what is value, what is of value and how value should be created? In partnerships, how do you ensure that individual contributions all lead to a common goal, and that each individual contribution is properly valued (cf. Oskam et al., 2020)? The same applies mutatis mutandis to the conceptualisation of what markets exactly are in this context, how market formation comes about and ultimately what upscaling entails and whether this is desirable and possible independently of the specific contexts. It goes without saying that, in order to achieve this, cooperation between different knowledge disciplines is indispensable, which in turn must maintain a close relationship with broad social practice. It is also important to understand the resistance to innovations and to develop ways and methods to deal with this. This is topical and essential, especially in the field of social transitions, because the formulation of objectives for these transitions is also a political process and provokes discussions. In general, there is a pro-innovation bias in both the formation of theories and the practice of innovation, which Rogers (1962) noted decades ago. Too little attention is paid to resistance and it is assumed that resistance is simply the lack of adoption of innovations. However, there is often more to it.

Research questions Numerous relevant questions for further research have already been raised earlier.

Broadening the value concept aimed at societal transitions

• To what extent are the methods and instruments aimed at creating economic value through innovation suitable for the realisation of societal transitions through innovation in which cultural, social and ecological value are important in addition to economic value?

• How can economic, cultural, social and ecological value creation be combined?

Definition and specification of a minimum viable ecosystem

• Which elements are necessary for a minimum viable ecosystem that are sufficient to lay the foundation for social transitions and to which parties are added in a later upscaling and diffusion phase?

• What does a minimal viable proposition look like?

• Which methods are suitable for better understanding and getting to know the process of diffusion and upscaling?

• To what extent can diffusion modelling be used for this?

Development of collaborative business models

• What are the (basic) elements of collaborative models for value creation aimed at societal transitions and how can they serve for diffusion and upscaling of the necessary innovations?

• What is the theoretical framework that defines collaborative business models and links them to transition science? What archetypes are there?

• What are the performance indicators for the design and realisation of collaborative business models aimed at societal transitions?

• What is the basis for so-called community based business models?

Articulation and alignment of value systems

• How can the underlying value systems of stakeholders that are relevant for societal transitions be mapped out?

• How can stakeholder alignment be achieved?

• What are suitable ways to deal with resistance to broad forms of value creation and diffusion and upscaling?

• What is the influence and consequences of the frequently observed pro-innovation bias?

• In that context, what are the conditions for successful diffusion and upscaling of innovations with a view to social transitions?

Organisational capabilities, partnerships and alliances

• Which organisational capabilities are required to create value in an ecosystem with multiple stakeholders, in the context of societal transitions?

• Which partnerships and alliances of knowledge disciplines and research traditions are necessary to realise methods for broad value creation and upscaling of innovations?

• Which of these are situationally bound to specific transitions and which are more generically necessary for the development of these methods?

Financeability and value capture in societal transitions

• How is the topic of financeability and risk profile of value creation and upscaling in the context of social transitions handled?

• Is the risk profile of a distributed investment across multiple partners who are in transition in conjunction, smaller than the sum of the participants' individually assessed financing?

• What is the relationship between public and private financing and how are risks with different partners and stakeholders invested?

• How can value created within the process of societal transitions be cashed in and who will collect the proceeds at what time and how?

Formation of new markets

• Societal transitions often require new markets to be created; how does that process go and which factors influence its formation and formulation?

• What is the role of institutional and socio-cognitive aspects in this? Which factors play a role in diffusion and upscaling?

• What are variables to consider to enable reproduction, diffusion and upscaling of innovations in different contexts? For example, what is the importance of the distinction between the urban and non-urban contexts?

Much has been written about institutional change in public administration, business administration, political science and management and organisation sciences, among others. Literature has accelerated after the so-called institutional "battle" in the early 1990s. Since then, various schools have emerged within disciplines that specifically highlight the role of institutions. These efforts have led to significant strides in developing methods to encompass institutional change over the past three decades.

The traditional approach is mainly based on an exogenous perspective. It pays attention to the way in which institutions should be designed, with the underlying assumption that there is a central and benevolent actor together with a (usually rational) society that will follow the imposed rules. The emphasis is therefore on designing institutions that guarantee the most favorable outcomes - getting the institutions right is a common motto here. Recently, much attention has also been paid to other forms of institutional change. Think of transitions in which social groups emerge as institutional entrepreneurs, challenge existing arrangements, and are sometimes so successful that, over time, they force institutional change. Existing ways of governance are therefore also subject to change. In addition to traditional forms of hierarchy and markets, more and more attention is being paid to networks as an alternative way of governance. Network governance rests on the mutual relationships and trust of actors, which is often also reflected in the governance mechanisms of transitions and innovations.

These developments, often technical and social in nature, have resulted in increasing complexity in the institutional environment. This has not gone unnoticed in the institutional literature. On the one hand, it has led to conventional methodology falling short in explanatory power and applicability. On the other hand, it has accelerated the development of new KEMs. Since we are mainly interested in the latter, below is an anthology of recent state-of-the-art methods that seek to encompass and explain current institutional changes. We distinguish between methods of emergence and design, which respectively approach the endogenous and exogenous processes of institutional change.

Emergence methodology of institutional change Today, most institutions share the view that institutional blueprints or transplantation - the one-to-one copying of institutional arrangements - is a subordinate method of institutional change. People increasingly speak of polycentric governance or institutional bricolage to indicate the time and space-dependent diversity of institutional arrangements, which often manifest themselves autonomously at the micro level. This includes methodology aimed at the emergence processes of institutional change.

Many of these methods and approaches are inspired by and build on the work of Nobel Prize laureate Elinor Ostrom. Her groundbreaking research into the possibilities of governance of socio-ecological systems has shown that local actors are able to regulate the use of natural resources (the commons) without this leading to depletion. This has sparked interest in alternative (non-private or public) forms of governance, such as informal, hybrid, and self-governing forms of governance. To cover this diversity, Ostrom has designed the Institutional Analysis and Development (IAD) framework which can be applied at different interaction levels (Ostrom, 2005). Within the action arena, the relevant rules, biophysical attributes and properties of the users are then examined. There is also growing interest in the question to what extent Ostrom's (2009) Socio-Ecological Systems (SES) framework can be applied to socio-technical systems.

Besides diversity, the inclusion of institutional dynamics is also an important contribution of emergence methodology. ‘Institutions are products of the past’ is a well-known statement by the founder of institutional economics, Thorstein Veblen. With this he believed that institutions are always hopelessly behind their (technology-fueled) changing environment. We now know that successful institutional change seldom proceeds through exogenous shocks or metamorphoses, but is actually evolutionary and incremental. This is something that has been covered extensively by supporters of historical institutionalism. For example, Mahoney and Thelen (2010) have developed a new framework for incremental institutional change. With a look at the origins and history of institutions, it contributes to answers to fundamental questions about how and why institutions often change in stages. In addition, it can help to explain discrepancies (between the intentions and outcomes of institutional change) by looking at endogenous processes, such as information skew and power relations.

Another important method for approaching institutional dynamics is process tracing (Collier, 2011). This is an in-depth method that can be applied to detect causal mechanisms and how they play out within a concrete case. Detailed knowledge is gained by collecting mechanistic evidence within the case, which then provides insight into how causal processes take place in reality. Although process tracing is applied to a single case, comparative research can reveal similar mechanisms. This is closely related to comparative institutional analysis (Morgan et al., 2010). This framework can be used to learn from institutions and practices in other domains, regions or countries.

Finally, emergence methodology is increasingly paying attention to the role of underlying cognitive and psychological processes. Institutional logics is a popular method here (Thornton et al., 2015). An institutional logic is the collection of symbolic systems, such as assumptions, values, and beliefs, by which individuals and organisations give meaning to their daily activities. For example, it can explain why locally-driven transitions often gain social support.

Design methodology for institutional change The increasing degree of institutional diversity and dynamics has made the design of institutions more complex. Functional approaches that only look at organisational forms and formal rules often seem to fall short. In the need to expand our view, design methodology plays an important role in supporting policy makers in the design (design) and evaluation (assessment) of institutional change.

Institutional design focuses specifically on the design and redesign of formal institutions that should lead to desired effects (Alexander, 2005). This includes strategies for institutional design, in which knowledge about the nature and diversity of institutional rules that guide the behaviour of actors within policy networks is used to influence network rules. The design approach as applied by Waardenburg et al. (2020) offers a design approach specific to collaborative governance forms, including small-scale experimentation and co-creation of innovative solutions, that fit the dynamics and uncertainty of contemporary societal challenges.

Evaluation tools can further improve institutional design. For example, the Framework for analysing leadership functions, task and strategies (Meijerink & Stiller, 2013) can be used to make an assessment of various forms of leadership in interorganisational networks. This tool distinguishes five important leadership positions that must be fulfilled in order to achieve transitions. Closely related is the Adaptive Capacity Wheel (Gupta et al., 2010), an assessment tool developed in the Knowledge for Climate research programme to assess the adaptive capacity of institutions. It can demonstrate the strengths of existing institutions, as well as indicate where adjustments are needed. Besides the use of independent assessments of researchers, the tool can also be used to allow practitioners to reflect on the institutional context in which they operate. This coincides with process management (de Bruijn et al., 2010), as part of which a variety of strategies can be deployed to get actors moving and to bring about change in institutions. For technological change, the technology assessment offers an interactive and communicative method to arrive at a public opinion about the desirability and the manner of institutionalisation of new technologies (Van Est & Brom, 2012).

Finally, we see that new principles and ways of design methodology are also emerging within governments. Contemporary policy, for example, relies less on cost-benefit analysis, but is increasingly based on ethical, environmental and social interests. Vision Zero is exemplary, a Swedish policy approach that is based on an ethical principle that every road death is socially unacceptable (Johansson, 2009). As a result of this programme, a series of technological, institutional and behavioural measures have been taken that have significantly reduced the number of road deaths in Sweden. The Vision Zero principle is now being applied in other countries and in various domains, such as in healthcare and environmental policy. At the same time, new policy instruments are also being designed that can move with social change. An example is the Right to Challenge (RTC), which originated in England. Nowadays this is also used in the Netherlands (Ministry of Economic Affairs, 2016). With a focus on the participatory society, RTC gives social groups the legal possibility to realise or even adopt the goals of a legal regulation in an alternative way. This example shows that governments are prepared to allow the opportunities for innovation to outweigh additional regulatory burdens and uncertainty.

Alexander, E. R. (2005). Institutional transformation and planning: from institutionalization theory to institutional design. Planning theory, 4(3), 209-223.

Collier, D. (2011). Understanding process tracing. PS: Political Science & Politics, 44(4), 823-830.

De Bruijn, J. A., ten Heuvelhof, E. F., & in 't Veld, R. J. (2010). Process management: why project management fails in complex decision making processes. Berlin: Springer.

Gupta, J., Termeer, K., Klostermann, J., Meijerink, S., van den Brink, M., Jong, P., & Nooteboom, S. (2010). Institutions for climate change: A method to assess the inherent characteristics of institutions to enable the adaptive capacity of society. Environmental Science & Policy, 13, 459-471.

Johansson, R. (2009). Vision Zero - Implementing a policy for traffic safety. Safety Science, 47(6), 826–831.

Mahoney, J., & Thelen, K. (2010). A theory of gradual institutional change. In: J. Mahoney, & K. Thelen (Eds.), Explaining institutional change: Ambiguity, agency, and power (1, 1-37). Cambridge: Cambridge University Press.

Meijerink, S., & Stiller, S. (2013) What kind of leadership do we need for climate adaptation? A framework for analyzing leadership functions and tasks in climate change adaptation. Environment and Planning C, 31(2), 240-256.

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Morgan, G., Campbell, J., Crouch, C., Pedersen, O. K., & Whitley, R. (2010). The Oxford Handbook of Comparative Institutional Analysis. Oxford: Oxford University Press.

Ostrom, E. (2005). Understanding Institutional Diversity. Princeton: Princeton University Press.

Ostrom, E. (2009). A general framework for analyzing sustainability of social-ecological systems. Science, 325(5939), 419-422.

Pelzer, P., Frenken, K., & Boon, W. P .C. (2019). Institutional entrepreneurship in the platform economy - How Uber tried (and failed) to change the Dutch taxi law. Environmental Innovation and Societal Transitions, 33, 1-12.

Thornton, P. H., Ocasio, W., & Lounsbury, M. (2015). The institutional logics perspective. Emerging trends in the social and behavioral sciences: an interdisciplinary, searchable, and linkable resource, 1-22.

van Bueren, E., & Klievink, B. (2017). Institutionele leegte: nieuwe bronnen, nieuwe uitdagingen. Bestuurskunde, 26(3).

Van Est, R., & Brom, F.W.A. (2012). Technology assessment: Analytic and democratic practice. In: Chadwick, R. (Ed.), Encyclopedia of Applied Ethics (2nd ed., 4, pp. 306-320). San Diego: Academic Press.

Waardenburg, M., Groenleer, M., de Jong, J., & Keijser, B. (2020). Paradoxes of collaborative governance: investigating the real-life dynamics of multi-agency collaborations using a quasi-experimental action-research approach. Public Management Review, 22(3), 386-407.

Desired societal and technological change can be influenced by taking a systemic perspective and acting in a related systemically strategic manner. The systems perspective is an addition to traditional natural science reductionism. Where reductionism seeks explanation and improvement in analysing the elements of a problem and searches for linear cause-effect relationships, a systems perspective shifts our view to the relationships between those elements and their influence on the change of the whole. In the context of KEMs, we are talking about a transition or shift of socio-technical and / or societal systems. A characteristic of socio-technical systems is that they are difficult to define and are unpredictable in their (emergent) behaviour. Systems have a multitude of elements and (mutual) relationships and thus form a complexity that is characterised by non-linearity, coevolution, emergence and self-organisation. As a result, we cannot control or change systems in a controlled manner. It is therefore important to develop knowledge about how we ‘dance’ with these systems (Meadows, 2001): about how our values ​​and the properties of a system can work together. Central to this strategic learning process is the link between the systemic perspective, the dynamics within that system and the intervention. Given the systemic lens and the dynamics we observe, how and where do we want to intervene - and what dynamics are the result of our intervention?

System change is therefore about the link between interventions and the dynamics of a system. Understanding the dynamics within these systems requires a holistic perspective: all elements that are important for the transition are considered in relation to each other. Intervention, on the other hand, requires a more specific perspective depending on the type of intervention (e.g., policy, protocol, technological artifact, change of law, subsidy, campaign, etc.). System change therefore requires consideration at several scale levels, also known as macro, meso and micro levels.

By way of illustration: A transition to CO2-neutral mobility requires changes from people in their daily lives (i.e. at the micro level, eg, different choices in means of transport, different time schedules, different weekend outings, etc.), from organisations (i.e. at meso level, eg, Shell will have to embrace a different business model, car manufacturers have to make adjustments, energy suppliers have to move to other markets, etc.), and at a national and international level (i.e. at the macro level, eg, the infrastructure of charging stations must be built, legislation must reduce CO2-emission, etc.). This may mean that the systemic conditions for an intervention to be effective are considered (e.g., charging station infrastructure is conditional for the adoption of electric vehicles); that systemic effects of the intervention are anticipated (e.g., increased sales of electric vehicles will affect Shell's earnings, which will intensify lobbying at political level); or whether it concerns systemic interventions (e.g., electric driving services that use networks).

Understanding a socio-technical system requires knowledge from different disciplines and from different stakeholders; a transdisciplinary approach. A choice will always have to be made for determining system boundaries and for the types of knowledge that we wish to consult when exploring a system. We do this based on our values, our worldview and assumptions. In addition, it is important for intervening that different interventions are viewed together. To this end, complementary to existing approaches such as top-down policy, a network approach is proposed in which different organisations and stakeholders learn and experiment together. System change methods therefore also include methods such as reflexivity and dialogue, in which differences in values ​​and perspectives are discussed and which promote transdisciplinary work (Popa et al., 2015).

Based on a wide range of systems theories, such as complex systems theory and cybernetics, methods are developed from different disciplines to understand and manage system change (e.g., transition management, organisational design, systemic design). KEMs in this category help to embrace complexity and steer a long-term course. They answer questions such as: what drives system change? How do we organise system change processes? How and where can we best intervene in the system to speed up the desired transition? And how can conditions be created that enable social systems to change themselves (continuously)?

Berkhout, F., Smith, A., & Stirling, A. (2003). Socio-technical regimes and transitions contexts. SPRU. University of Sussex, Science and Technology Policy Research.

Checkland, P. (1999). Systems Thinking, Systems Practice. Chichester: John Wiley.

De Sitter, L. U. (1994). Synergetisch produceren: Human Resources Mobilisation in de produktie: een inleiding in structuurbouw. Assen, Nederland: Koninklijke van Gorcum B.V.

Geels, F. W. (2002). Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case study. Research Policy, 31(8-9), 1257-1274.

Geels, F. W. & Schot, J. (2007). Typology of sociotechnical transition pathways. Research Policy, 36(3), 399-417.

Grin, J., Rotmans, J., & Schot, J. W. (2010). Transitions to sustainable development: New directions in the study of long term transformative change. (Routledge studies in sustainability transitions; Vol. 1). New York: Routledge Taylor & Francis Group.

Hekkert, M. P., Suurs, R. A. A., Negro, S. O., Kuhlmann, S., & Smits, R. E. H. M. (2007). Functions of innovation systems: a new approach for analysing technological change. Technological Forecasting and Social Change, 74(4), 413-432.

Hummels, C. C. M., Trotto, A., Peeters, J. P. A., Levy, P., Alves Lino, J., & Klooster, S. (2019). Design research and innovation framework for transformative practices. In: Strategy for change (pp. 52-76). Glasgow: Glasgow Caledonian University.

Irwin, T. (2015). Transition design: a proposal for a new area of design practice, study, and research. Design and Culture, 7(2), 229-246.

Jones, P. (2014). Systemic Design Principles for Complex Social Systems. In G. Metcalf (Ed.), Social Systems and Design (Vol. 1, pp. 91-128). Tokyo: Springer.

Kemp, R., Schot, J. & Hoogma, R. (1998). Regime shifts to sustainability through processes of niche formation: the approach of strategic niche management. Technology analysis & strategic management, 10(2), 175-198.

Manzini, E. (2016). Design culture and dialogic design. Design Issues, 32(1), 52-59.

Markard, J., Raven, R., & Truffer, B. (2012). Sustainability transitions: An emerging field of research and its prospects. Research policy, 41(6), 955-967.

Meadows, D. H., Randers, J., & Meadows, D. (2004). Limits to growth: the 30-year update. Vermont, USA: Chelsea Green Publishing.

Popa, F., Guillermin, M., & Dedeurwaerdere, T. (2015). A pragmatist approach to transdisciplinarity in sustainability research: From complex systems theory to reflexive science. Futures, 65, 45-56.

Raven, R., van den Bosch, S., & Weterings, R. (2010). Transitions and strategic niche management: towards a competence kit for practitioners. International Journal of Technology Management, 51(1), 57-74.

Rotmans, J., Kemp, R. & van Asselt, M. (2001). More evolution than revolution. Transition management in public policy. Foresight, 3(1), 15-31.

Schot, J., & Geels, F. W. (2008). Strategic Niche Management and Sustainable Innovation Journeys: Theory, Findings, Research agenda, and Policy. Technology Analysis & Strategic Management, 20(5), 537-554.

Sevaldson, B. (2011). Gigamapping: visualization for complexity and systems thinking in design. Paper presented at the Nordic Design Research Conference, Helsinki.

Snowden, D. J., & Boone, M. E. (2007). A leader's framework for decision making. Harvard Business Review, 85(11), 68-76.

Stirling, A., Lobstein, T., & Millstone, E. (2007). Methodology for obtaining stakeholder assessments of obesity policy options in the PorGrow project. Obesity Reviews, 8, 17-27.

As early as the 1970s, the Club of Rome explored the limits of our world systems and their limitations on human numbers and human activity. This resulted in the report Limits to Growth in which computer simulations showed that there is a limit to economic growth and population growth (Meadows et al., 2004). Instead of economic growth, governments should focus on resilience and adaptation. The COVID-19 crisis could not clarify more how important it is to our society that we develop systems that are resilient: that can adapt or can transform as soon as the environment requires it. This requires innovation capabilities from organisations, but also system properties of society itself, such as diversity and flexibility. We therefore need methods that answer questions such as: how can we increase the adaptivity of a system? How can we better develop transdisciplinary action research in this context? How can we better monitor and understand system change in the long term? How can we organise the government, private sector, science and society as a learning system?

Adaptive systems This cluster deals with the conditional properties of socio-technical systems that promote adaptive system behaviour and guide desired changes:

• What are general and sector-specific conditions under which societal systems are able to adapt to changing circumstances and innovate responsibly?

• How do we deal with challenges in ‘chaos’ where there are various interests that compete with each other about where to go within a system? What is a suitable participation model? Which actors should be involved in which phase?

• How can we guide the demolition and completion of existing structures? How can we link existing initiatives and systems?

• How can we develop open structures and interventions that increase the adaptability of a system?

Transdisciplinary action research A common criticism of the field of systems thinking is its emphasis on understanding system changes that have already occurred in the past and sharing this knowledge among scientists, rather than exploring what a systemic approach could mean for the future and sharing it with social actors (Ackoff, 2004). In recent decades, we have therefore seen an emergence of transdisciplinary action research. Through active experimentation and the development and implementation of initiatives, this research contributes to knowledge about how systems behave and how we can influence or guide them. A transdisciplinary lens ensures integration of knowledge from both the scientific and the societal domain. This concerns research questions such as:

• What are effective leverage points for conducting innovation experiments?

• What are suitable methods for designing system interventions that focus on the social and emotional dimensions of change, for example influencing mental models, paradigm changes, and human relationships?

• How do we stimulate transdisciplinary action research and make science more entrepreneurial?

Monitoring system change and making long-term estimates One point of concern is that changes in society and the economy are moving faster than science can keep up with. In addition, we would like to understand long-term system change. This leads to questions such as:

• How can we better monitor system change?

• How can we understand long-term change and develop indicators for change?

• How can we develop better cost-benefit studies for transitions?

• How can we better understand the coordination between system changes in different domains?

• How can we use different qualitative and quantitative methods to monitor system change and understand it in the long term?

System awareness, reflexivity & learning together The basis of effective system change and societal transitions is a structured form of learning together about our perspective on the system, about what we learn about that system, and about our role in intervening in the system. The following questions play a role in this:

• How do we involve different system actors in the system perspective? How can we guide actors in understanding different world views and perspectives? How do we make them aware of the qualities of resilient systems such as flexibility and diversity?

• How can we make tensions within a social system productive? How do we avoid polarisation that limits learning?

• How can we help system actors develop skills that encourage dialogue and adaptive leadership?

• How do we help system actors to be reflexive about how they interact with system changes in progress?

• How do we stimulate knowledge transfer between system actors? How do we create a learning system?

• What are new forms of public, private, civil cooperation?

Measuring progress, effect and impact on transition issues is essential to demonstrate whether the predetermined goals have been achieved, and whether this can be traced back to the interventions that have been carried out. This not only concerns the direct effects (output), but also which expected and unexpected changes take place (outcome), why they have changed, and what the impact of these changes are on the systems (impact). While monitoring progress, information can be systematically and / or continuously collected and analysed. Because monitoring takes place during the project, it is possible to make timely adjustments if things do not go according to plan. Effect measurements complement monitoring activities and provide in-depth and objective insights into the relevance, efficiency, effectiveness, impact and sustainability of the intervention at specific times.

The use of the right KEMs depends, among other things, on the intended goal and the context in which the transition takes place. Interventions with a clearly specified end goal require a different M&E method than interventions that focus on structural change where the desired end goal is (still) unknown. This also applies to the environment in which the change takes place. Changes in complex and dynamic systems cannot be monitored with methods that are based only on and depend on protocoled data, structure, and certainty. This also requires new methods. For this chapter, the M&E methods are described on the basis of a conceptual framework that describes the dynamics of monitoring and adjustment. In this context, we distinguish methods aimed at targeted M&E and methods aimed at learning M&E. Targeted M&E methods often start with predetermined goals, where progress is monitored via measurable indicators that are selected at the start. The strength of these methods lies mainly in justifying the project goals and demonstrating relationships between activities within the intervention and the results. Learning monitoring methods can better deal with uncertainty about the approach in advance and the unexpected effects during the process, whereby the strategy can be adapted to the changes during the intervention.

Targeted M&E methods Methods based on targeted M&E are mainly used to justify projects and interventions. By setting the goal before the start of the project, indicators are chosen that can demonstrate whether the goals are being achieved. It is therefore important to have a clear and unambiguous picture of the expected effects of the intervention in advance. These methods are highly regarded in science. However, these methods are often not suitable for interim assessment of assumptions and adjustment during the process. The randomised controlled trial (RCT) is an example of a project evaluation method that provides insights into the direct relationship between activity and outcome, because the effects of the intervention are compared with the effects in a comparable population (the control group) without intervention (Donaldson et al. al., 2015). However, experiments with a randomised and controlled design are often time consuming, cumbersome and static. Small-scale experiments with randomisation - as applied in Rapid Cycle Experiments - can quickly gain insight into which parts of an intervention work, in order to further develop and optimise the intervention on that basis (Johnson et al., 2015).

On the basis of a Social Cost-Benefit Analysis (SCBA) an accurate estimate can be made in advance of the expected effects of the intervention. This method maps the positive and negative effects and is therefore used to justify policy measures. The method focuses on the welfare effects of the measures, and in addition to the economic effects, an estimate can also be made of the so-called soft effects, such as the impact on culture, happiness and well-being. SCBAs place high demands on the quality of information and research methods that are used as input, making this method of limited use for unstructured and incomplete datasets and projects with uncertain outcomes. Certainly within transition issues of a complex nature, these are aspects that surface more often (Koopmans et al., 2016). After the intervention, variants of the SCBA can be used as evaluation measurements, such as the cost-effectiveness analysis. Surveys and the registration of indicators provide a good picture of improvements and changes after the intervention. An example of this is the Care Monitor, which provides insight into the performance of health care based on a broad set of predefined indicators (van den Berg et al., 2011).

Learning M&E methods Transition challenges often concern complex changes in systems in which both the required approach and the expected effects of this approach are difficult to estimate in advance. Transition issues therefore often require an M&E method that is dynamic and adaptive. Within various disciplines, methods have been developed that are in line with the uncertain nature of transition issues and that move with the changes in the transition. For example, the popular Agile working method has in recent decades spread from software development to industry, and is now increasingly emerging in digital and non-digital projects in science. Recent developments from data science in the field of AI and big data also make new methods available for M&E. With the help of data-driven predictive analyses, real-time insight can be generated on the effects of the interventions. More about the opportunities and challenges of these methods is described in the section with challenges and research questions.

Within the behavioural sciences we see methods emerging that attempt to combine dynamic monitoring with scientific justification that we know from randomised trials. For example, N-of-1 studies (or Single Case Design) can monitor the direct effects of interventions on behaviour, based on repeated quantitative measurements within an individual over time (McDonald et al., 2017). An important advantage is that the intervention can be further developed and adjusted during the measurements. Another advantage is that the baseline can be different for each participant. This gives you insight into individual differences, the effect of the context, and you can minimise the statistical disadvantages of distribution in the target group. However, N-of-1 studies are mainly suitable for digital behavioural interventions, and are very dependent on the intervention adherence of the participants. Still, this is a promising method for transition issues with a behavioural change component. Other promising methods that identify effective mechanisms in design propositions and interventions are MOST (Multiphase Optimisation Strategy; Collins et al., 2007) and CIMO-logic (Denyer et al., 2008).

Reflexive Monitoring in Action (RMA) is a participatory M&E method developed to monitor the progress of system innovations (Van Mierlo et al., 2010). It facilitates the development of learning processes during transitions and thus stimulates the determination of the direction of the transition. The determination of the goal, approach and indicators is moving along with the progress of the process. Although the specific monitoring tools differ per topic or ambition, it is important that these activities are an integral part of the transition. Examples of methods that can be used in RMA include Theory of Change, Learning History and Most Significant Change Method. The monitoring activities are seen as project activities, where each monitoring cycle consists of the steps ‘observe’, ‘analyse’, ‘reflect’ and ‘adapt activities’. Because reflexive monitoring is an adaptive method, direction can be changed during the project, and unexpected effects can be identified. However, the participatory nature of reflexive monitoring is very important. In order to bring about institutional change, it is essential that all stakeholders participate in this.

Related to reflexive monitoring is the Measure Knowing Act system, developed for the Delta Programme (Loeber & Laws, 2016). Structured reflection moments stimulate ‘learning during the intervention’. It is possible to respond to new developments, to slow down or accelerate activities and to adapt the strategy based on changes in systems. Adjustment takes place on the basis of four main questions: is the project on schedule (budget and time), is the project on track (are goals being achieved), is there an integrated approach, and is there broad participation of stakeholders?

Adjustment and accountability Targeted M&E methods provide a scientifically based insight into the relationship between the activities in the project and the visible results. However, adjustment during the process is minimal. Learning M&E methods allow for adjustment and uncertainty, but how do we know whether this adjustment is an improvement? How ‘statistically’ reliable are the first insights that serve as input for iteration and can bring about adjustment of the approach? It is important to find a balance between M&E methods with sufficient scientific rigor and useful and applicable methods for monitoring changes in complex systems. Should new methods be developed for this, or is adaptation of existing methods sufficient? And how important is it to substantiate all decisions ‘statistically’?

Research questions that can be posed:

• How can we test assumptions in the design process in an insightful but non-burdensome manner, in such a way that this provides us with an evidence-based foundation for further development of the intervention?

• How can we test the designed intervention, in such a way that it provides us with useful information about changes at system level and context level, and about the generalisability of the intervention (effectiveness of underlying working mechanisms), without hindering the design process and the further development of the intervention or freezes for a long time?

Quantification of impact and the role of the selected indicators A change within systems often involves more than just direct and expected effects. How do we map these indirect and external effects? Indirect effects often only come into the picture late and are difficult to quantify or monetise. For example, what is the value of happiness or the knowledge generated during transition issues? We know that these aspects have an important effect on economic growth and our prosperity, but how do you map them out? In addition, the choice of indicators or M&E tools can also determine the form and direction of the interventions. We see that development strategy is determined by measurable indicators or KPIs, such as ‘attention span’ at companies such as Netflix and Google. But is this the right strategy, and how important are data / indicators that cannot (yet) be measured? New developments in this area will also determine the nature of interventions.

Research questions that can be posed:

• How can we formulate output, outcome and impact indicators that are relevant to the transition goal and intermediate goals that are tailored to the mission as much as possible?

• What is the effect of the measurable and available indicators on the form and direction of our interventions?

• How can we test the effectiveness and efficiency of our design process?

Applying new datasets and new data-driven methods The developments in AI and big data analytics offer many opportunities for transition issues. With the help of these methods, learning and real-time insight can be obtained into the (potential) effects of the contribution of interventions to the transition, as well as into possible relevant external developments. A first step has been taken with the development of a data-driven Foresight analysis method (Goetheer et al., 2020), in which AI and big data and the use of different types of data sources can support the decision-making of transitions. These methods can also be used to gain more insight into the expected effects in advance (data-driven predictive modeling). However, new data sources must be used (such as citizen science data, open source, or data from non-protocol studies), which are by definition diverse, unstructured and incomplete. In the next steps, we need to find out which data is available or can be created, how to use it, which methods fit these datasets, and how to deal with these limitations in the quality and reliability of data.

Research questions that can be posed in this regard:

• Which methods should we apply and / or develop to obtain the correct estimates (prognosis) and classifications (diagnosis, screening, monitoring) from new types (diverse, new, unstructured, incomplete) data?

• How do we identify the relevant data sources and data types for monitoring and evaluating transitions, including validating data / information?

• How do you design a hybrid data-driven M&E method, linked to innovation intelligence?

• How do you ensure that information generated by AI and big data is explainable, understandable and accepted?

• How do we deal with privacy-sensitive data and the decline in the willingness of the population to participate in registrations and studies?

Collins, L. M., Murphy, S. A., & Strecher, V. (2007). The multiphase Optimization Strategy (MOST) and the Sequential Multiple Assignment Randomized Trial (SMART): New Methods for More Potent eHealth Interventions. American Journal of Preventive Medicine, 32(5), S112-S118.

Denyer, D., Tranfield, D., & van Aken, J. E. (2008). Developing design propositions through research synthesis. Organisation Studies, 29(3), 393-413.

Donaldson, S. I., Christie C. A., & Mark, M. M. (2015). Credible and actionable evidence: The foundations for rigorous and influential evaluations. Thousand Oaks, CA: Sage.

Goetheer, A., Gutknecht, R., Geurts, A., Schirrmeister, E., Meissner, S., Bakker, B., & Warnke, P. (forthcoming). Data supported foresight. Creating a new foundation for future anticipation by leveraging the power of AI and Big Data to go beyond current practice.

Johnson, K., Gustafson, D., Ewigman, B., Provost, L., & Roper, R. (2015). Using rapid-cycle research to reach goals: Awareness, assessment, adaptation, acceleration. AHRQ Publication No. 15-0036. Rockville (MD): Agency for Healthcare Research and Quality.

Koopmans C. C., Heyma, A., Hof B., Imandt, M., Kok, L., & Pomp, M. (2016). Werkwijzer voor kosten-batenanalyse in het sociale domein. (SEO-rapport; nr. 2016-11A). Amsterdam: SEO.

Loeber, A., & Laws, D. (2016). Reflecterend in de Delta: naar een systematiek voor monitoring en evaluatie in het Deltaprogramma gericht op lerend samenwerken. Amsterdam: Universiteit van Amsterdam.

McDonald, S., Quinn, F., Vieira, R., O’Brien, N., White, M., Johnston, D. W., & Sniehotta, F. F. (2017). The state of the art and future opportunities for using longitudinal n-of-1 methods in health behaviour research: a systematic literature overview. Health Psychology Review, 11(4), 307-323.

Van Mierlo, B., Regeer, B., Van Amstel, M., Arkensteijn, M., Beekman, V., Bunders, J., De Cock Buning, T., Elzen, B., Hoes, A.C., & Leeuwis, C. (2010). Reflexieve monitoring in actie: Handvatten voor de monitoring van systeeminnovatieprojecten. Oisterwijk: Box press.

Due to the long horizon and the unpredictable nature of (changes to) systems, it is particularly relevant for transition issues to monitor and (intermittently) evaluate the effects of interventions. In this way, knowledge is gained about the possible effects of the manner in which the intervention was taken, which can be directly fed back into the process, in order to support iterative further development and adjustment. Interventions often take place in an uncertain, complex and dynamic environment, where the ultimate effects also depend on other factors and systems, such as breakthroughs and innovations abroad. It is therefore important to gain insight into the changes (direction, speed, and impact) during the intervention. Although these measurements mainly take place during and after an intervention, it is very important to think about monitoring and effect measurements (M&E) especially before the start of the project. For correct monitoring and effect measurement it is important to have a clear and unambiguous picture of the end goals, to select and develop the right indicators for this, and to link the methods to this. This allows you to develop insight into the course of the project and the associated uncertainties. Due to the complex and dynamic nature of transition issues, it must be possible to adjust the adaptive approach, including policy mix and methods, during the process on the basis of progress.

KEMs in this category help to monitor the process, measure the effects and contribution of interventions, and monitor the impact on the system. They provide important information to adjust the intervention during the process. In addition, it is important that the M&E are transparent, and thereby contribute to maintaining and increasing support and involvement. In this chapter, we paint a picture of different KEMs that can be deployed within mission-driven transitions to measure progress and impact. We discuss various goal-oriented and learning KEMs, and identify the main challenges for these methods. The KEMs in this category answer questions such as: how can we measure and analyse the effects of an intervention on the entire system, in the short and long term? How do we also get a picture of the unpredictable and unintended effects and dynamics? How can we analyse the value created by the interventions and changes? Which interventions and instruments work and don’t work, and under what conditions?

In order to clarify the possible role of KEMs in the missions, it is important to understand the nature and process of the development of new and further development of existing KEMs.

KEMs are often developed, tested and trialled in research at knowledge institutions. KEM development is - especially in the first step - the result of fundamental, methodological research, based on theoretical models and considerations. However, the practice in which KEMs are applied is unruly. This often creates variations on existing methods; the methods are further developed by using them in specific contexts. KEMs are therefore never ‘finished’ and must be continuously tested for (context-dependent) usability, effectiveness, validity, etc.

In contrast to technology, research into and further development of methods therefore preferably takes place in their application in concrete innovation processes. By studying the effect of the interventions that are realised with a specific KEM, insights are gained that help to validate the method, to better contextualise it and to combine methods.

KEMs build bridges between domains in order to arrive at integrated solutions. This cross-over nature of KEMs requires a multidisciplinary joining of forces in the field of KEM research and development. The complex and multidisciplinary issues posed by the missions therefore offer excellent opportunities to work on KEM development. This KEM research agenda is therefore intended as a basis for programming methodological issues within the KIAs of the mission themes. In research and innovation programmes, transition challenges will be central, in which existing methods are applied and thus further developed, or new strategies and methods are developed. The programmes can draw on this agenda and the research questions identified in it as the most urgent questions to address in the short term.

Working on this agenda has made it clear that in the Netherlands we have a number of strong research communities in the KEM categories covered in this agenda. These communities have organised themselves to a greater or lesser extent and also enjoy international prestige in their specific domain. Connecting these strong research groups to private parties offers interesting opportunities for tackling the missions and forming consortia for PPP projects.

Societal or socio-technical systems are complex dynamic systems. This means that changes take place continuously: new services are developed, new technologies are introduced to the market, decisions are made to do things differently, mutual task agreements are changed, or new players enter the market. In this sense, complex systems are always in motion. However, the degree of change and how the change is managed can differ greatly. Transitions can be driven internally (i.e. by players and incentives of the system itself) or more externally controlled, and their coordination can be vision-driven or take place more "emergently" (Berkhout et al., 2003). After studying different transitions, Schot and Geels (2007) define five stereotypical transition paths that can be followed by a system. These range from 'the path of reproduction' in which system interactions keep the regime (or the current structure of the system - the prevailing frames of thought, institutions and infrastructure) dynamically stable, to 'the path of reconfiguration' in which innovations increasingly challenge the architecture of the regime, or 'the path of substitution' where an innovation developed (and proven) parallel to the system breaks through to the regime. We are talking here about innovations, of a social or technological nature, that introduce a different practice with other necessary institutions and infrastructure.

To illustrate, if we consider the current practice of personal transportation, we can say that the socio-technical system around it is currently following the ‘path of reconfiguration.’ Electric vehicles, which entail different infrastructure and institutions than petrol or diesel vehicles, are increasingly challenging the status quo. All this, of course, under pressure from global institutions, governments, scientists and the population, who are increasingly asking for more sustainable alternatives.

We can divide methods that support the realisation of system change into four subcategories: methods that 1) explore and model a system according to a chosen system perspective and conceptual framework in order to understand the dynamics, 2) support strategic action in the development of experiments and interventions, 3) helping to organise the process of intervention development as a system change in itself, and 4) facilitating and stimulating dialogue & reflexivity in the process. These methods are closely intertwined. In order to understand a complex system, it is stated that intervention is crucial (Snowden & Boone, 2007). And because an objective perspective on socio-technical systems does not exist, dialogue and reflexivity is an essential element in choosing a system perspective (Checkland, 1999).

1) Methods for modeling the system (understanding dynamics) To determine the strategy to influence a desired system change, it is necessary to understand what the current playing field looks like. On the basis of a chosen system lens or conceptual framework, questions are asked such as: who are important players (in terms of power or importance), what are the important thinking frameworks, how is value exchanged, and which innovations are being worked on? The connections and relationships between these system elements and their effect on the dynamics of the system are particularly important here. Methods are offered for this from various disciplines.

• Multi-Level Perspective: this method states that we can understand transitions as interactions between 'the landscape' (ie, developments in the field of politics, culture, worldviews, and paradigms), 'the regime' (ie, the prevailing conceptual frameworks, institutions and infrastructure) and 'niches' (ie, places in which deviating practices take place). From this conceptual framework, innovative movements and conservative forces are analysed by means of historical analysis and qualitative research (Geels, 2002).

• Process method TIS analysis: This method falls within the perspective of technology-innovation systems (TIS). The network of interacting agents in the economic field who operate within a particular institutional infrastructure and are involved in the generation, diffusion and use of technology. The process method studies the mechanisms underlying technology change over time, by means of data analysis on events at the micro level (e.g. meeting reports and organisational reports) or system level (newspaper archives and journals) (Hekkert et al., 2006).

• Gigamapping: This method falls within the pluralistic systemic design approach, in which a conceptual lens is always pragmatically chosen on the basis of the properties of a complex issue. This can concern ecological, technological, societal, personal, cultural, political and legal, economic as well as demographic lenses and micro and macro perspectives. Based on a mixed-method approach with, for example, stakeholder interviews, user observations, and dialogue sessions, different perspectives and the resulting elements and relationships are brought together in a gigamap (Sevaldson, 2011).

2) Methods to develop and choose interventions (how to intervene) Managing system change is complex. And methods that help to develop interventions and provide a reference for making strategic choices are needed. What is our shared vision of how change will come about? Which interventions do we see as most effective? Which initiatives exist and should we try to scale up?

• Leverage points: The concept of leverage points indicates places in a complex system where a small change can lead to a major impact in a system (Meadows, 1999). Meadows determined twelve leverage points in order of effectiveness, whereby we can exert influence at the least effective level through constants, parameters, and numbers (such as subsidy or standards). The most effective levels are about the mindset or paradigm from which the system arises and the power to transcend paradigms.

• Transition design: Transition design is a framework that promotes a design-driven societal transition for a sustainable future, based on a concept for a completely new lifestyle that is developed locally and on a human scale, while being globally networked in the exchange of information and technology. The framework includes four key areas (i.e., vision for the transition, theory of change, attitude and mindset, and new ways of design) for which narrative, knowledge, skills and actions can be developed (Irwin, 2015).

• Multi-criteria mapping: This method helps to identify different perspectives and map various policy options for system changes. By means of a structured interview technique and a computer analysis, all options are viewed in a symmetrical way by different actors. They look at both social and technological aspects (Stirling et al., 2007).

3) Methods for organising transitions It is impossible as an outsider to realise system change without establishing relationships with the system. This means that actors or companies that want to steer system change must strategically consider how they enter into and shape the relationship with the existing system. How do you form a network with a shared mission? How do you organise the process? How do you divide roles and build new structures of cooperation? And how, as a network of stakeholders, can you, as it were, pilot system change by experimenting together with new resources and processes?

• Transition arena as a method in which a selective group (an innovation network) with diverse perspectives and roles works on a future vision and transition path for a specific transition (Loorbach, 2014).

• Sociotechnics: Sociotechnics shows how you can integrally change (networks of) organisations so that they can make their social contribution. For this you have to start with the structure (the way in which tasks are divided and linked). What exactly better structures entail differs per concrete context - and sociotechnology offers a tool for designing and redesigning structures per context (de Sitter, 1994).

• Transformative Practices: This is a design-driven approach that helps multi-stakeholder teams to research, design and innovate complex systemic societal challenges. By consciously playing with different configurations of people and mediations (through products, systems, environments, services, policy instruments), the personal and social ethics and related behaviour of (groups of) people transforms.

4) Methods to learn together from change As stated earlier, complex dynamic systems cannot be controlled. We must learn to ‘dance’ with systems. Learning from Eastern philosophies, we need to use our Western knowledge - often based on reductionist paradigms - in our practices to guide transitions. This requires reflexivity. How can we learn as effectively as possible from our actions, during our actions?

• Pragmatic Reflexivity: Traditional reflexive approaches aim at generating consensus. Pragmatic reflexivity, on the other hand, is an open, transformative and action-oriented collective process of reframing the issue and underlying values, ideologies and power structures. The methodology consists of collaborative experiments and social learning with both scientific and extra-scientific expertise (Popa et al., 2015).

• Dialogic design: This is a method as part of co-design in which different stakeholders bring in their specific ideas, skills and culture and can take action. The problems and tensions that can arise as a result are discussed using a dialogue technique, in which actors apply listening skills, change their minds and converge to a shared perspective (Jones, 2014; Manzini, 2016).

In this final chapter, we briefly discuss the application of KEMs and their possible role in the Mission-Driven Innovation Policy. In doing so, this chapter provides insight into the way in which this agenda can be implemented and can also form the basis for methodological challenges in research programming.

Transition challenges are complex and comprehensive, and require thoughtful use of KEMs in tackling them and in the development of interventions and / or innovations. Several KEM categories will often be relevant to a challenge and methods from several categories will be required to achieve a successful process and result.

There are a number of KEMs that already house these combinations in themselves due to their generic character; they therefore belong in several categories. Examples are reflexive monitoring (see categories System change and Monitoring and effect measurement) and transition arenas (see categories System change and Participation and co-creation). Both (groups of) methods were discussed in two categories in this agenda. Each category does have its own view of the method and that perspective presents different challenges / research questions.

Vision formation, participation and value creation Framing a joint innovation task (shared vision development) can only lead to successful interventions if it finds support among stakeholders. By devoting attention in a co-creation process with the stakeholders to creating a basis for shared values ​​(shared meaning), a perspective of a future desirable for each party can be developed to help create this support.

Participation and experimental environments In the process of co-creation in multi-stakeholder settings, experimental environments offer a relatively ‘safe’ environment, because the feasibility and scalability of initiatives can be tested in a flexible way so that learnings can be immediately fed back into the development process. It is also possible to explore in experimental environments how participation and co-creation can work for settings in which these methods are new, as is now seen in the Policy Labs (exploration of citizen participation in government).

Institutional change and behavioural change The context in which behaviour is established is colored by institutions, among other things. In addition, the rhetoric of institutional change is often that it provides incentives to individuals in the hope of behavioural change. Institutions and behaviour are therefore almost inseparable. Current behaviour is related to current institutions and the effectiveness of institutional change always depends on behavioural change. For example, the effectiveness of imposing additional taxes on meat, with the aim of reducing meat consumption, ultimately depends on whether people actually change their behaviour.

System change and monitoring KEMs aimed at learning about the system and system change are inextricably linked with KEMs to monitor the same system and the effects of interventions. Through reflexive monitoring, insight into the progress of system change can be used to adjust the goal and strategy of the change. In addition, the use of the right monitoring methods can help to map and understand the long-term effects of interventions on system changes.

In all missions and in each of the four mission KIAs and the KIA Social Earning Capacity, many links and questions about methods can be discovered. In principle, methods from all eight KEM categories can be relevant for each mission and each mission theme. This has to do with the nature of the missions: they concern transitions of systems (system change) in which, for example, the bringing together and alignment of many stakeholders (participation and co-creation) and getting a grip on the effects of interventions to bring about the transitions (monitoring and effect measurement) will always play a role.

Yet we also see that a number of categories receive a lot of attention per theme. In order to provide tools for prioritising methodological challenges in the programming within the mission themes, the table below indicates per mission theme which KEM categories seem most relevant to achieving the mission objectives. It concerns a generic initial inventory; a proposal at theme level that can be further elaborated on the level of MJPs / MMIPs and research questions in consultation with the parties involved and in the forums surrounding the KIAs.

Authors Miguel Bruns Alonso - TU Eindhoven Mieke van der Bijl-Brouwer - TU Delft Paul Hekkert - Topsector Creatieve Industrie Caroline Hummels - TU Eindhoven Jos Kraal - TU Delft Kees Krul - TU Delft Geke Ludden - Universiteit Twente Tom van der Horst - TNO Linda Rindertsma - CLICKNL Paul Rutten - Hogeschool Rotterdam Nynke Tromp - TU Delft

An initiative of Bart Ahsmann - CLICKNL Hans de Bruijn - TU Delft/NWO Marco Hekkert - Universiteit Utrecht Paul Hekkert - Topsector Creatieve Industrie Tom van der Horst - TNO Janneke van Kersen - NWO Nico van Meeteren - Topsector Life Sciences and Health

Courtesy of Walter van Andel - Universiteit Antwerpen Flor Avelino - Erasmus Universiteit Rotterdam Tilde Bekker - TU Eindhoven Yvonne Benschop - Radboud Universiteit Frank Berkers - TNO Nancy Bocken - Maastricht University Wouter Boon - Universiteit Utrecht Hans de Bruijn - TU Delft Ellen van Bueren - TU Delft Eefje Cuppen - Universiteit Leiden Jaap Daalhuizen - DTU Kees Dorst - University of Technology Sydney Patrick van der Duin - Stichting Toekomstbeeld der Techniek Berry Eggen - TU Eindhoven Koen Frenken - Universiteit Utrecht Mathias Funk - TU Eindhoven Govert Gijsbers - TNO Arjen Goetheer - TNO Martijn Groenleer - Universiteit van Tilburg Maarten Hajer - Universiteit Utrecht Marko Hekkert - Universiteit Utrecht Sander Hermsen - Hogeschool Utrecht Bas Hillebrand - Radboud Universiteit Caroline Hummels - TU Eindhoven David Keyson - TU Delft Rolf Künneke - TU Delft Harro van Lente - Maastricht University Derk Loorbach - Erasmus Universiteit Rotterdam Walter Manshanden - NEO Observatory Panos Markopoulos - TU Eindhoven Sander Meijerink - Radboud Universiteit Koert van Mensvoort - TU Eindhoven Carl Moons - Universiteit Utrecht Maria Peeters - Universiteit Utrecht / TU Eindhoven Peter Pelzer - Universiteit Utrecht Reint Jan Renes - Hogeschool van Amsterdam Jan Rotmans - Erasmus Universiteit Rotterdam Etiënne Rouwette - Radboud Universiteit André Schaminée - Twynstra Gudde Johan Schot - Universiteit Utrecht Adriaan Slob - TNO Pieter Jan Stappers - TU Delft Marleen Stikker - Waag Martin Strobel - Maastricht University Roald Suurs - TNO Anne Fleur van Veenstra - TNO Emely de Vet - Wageningen University and Research Leentje Volker - Universiteit Twente William Voorberg - Erasmus Universiteit Rotterdam Dirk Vriens - Radboud Universiteit Ellen van der Werff - Rijksuniversiteit Groningen Laurens Zwakhals - RIVM

CLICKNL Programmaraad

Final Editing Linda Rindertsma - CLICKNL Ella Verkuijten - CLICKNL

This agenda provides a framework for multidisciplinary thinking about KEMs and lists the main categories of methods that can be used in tackling missions and transitions. By presenting the current state of research (existing methods) and the most pressing research questions (knowledge gaps), the agenda serves as a basis for research programming around the missions and as inspiration for research proposals that address methodological challenges.

Because this research agenda was developed in the context of the Mission-Driven Innovation Policy, a broad elaboration of the concept of KEMs was sought that does justice to all forms of social and societal innovation. On the basis of a starting document drawn up by the initiators, a request was made in which a broad field of Dutch scientists from the alpha, beta and gamma sciences was consulted about the scientific state of affairs and the required research into KEMs within their various fields. The multicolored input that was collected with this request has been processed by the authors into this agenda.