Facilitating multidisciplinary decision making

By Bob Dick

bob-dick
Bob Dick (biography)

Imagine this scenario. You are confronted by a wicked problem, such as the obesity epidemic. You know it’s a wicked problem – many previous attempts to resolve it have failed.

Suppose that you wish to develop a plan to remedy obesity. You have identified as many relevant areas of expertise and experience as you can and approached appropriate people – researchers, health practitioners, people with political influence, and so on.

You bring them together to pool their expertise—only to find that you now have another problem. Encouraging them to work collaboratively is more difficult than you expected. They talk in jargon. Their understanding is narrow. Their commitment is to their own discipline. Some of their understanding is tacit. Some of them are argumentative. And more. What are you to do?

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Eight strategies for co-creation

By Arnim Wiek

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Arnim Wiek (biography)

Co-creation aims at genuine and meaningful interaction among researchers, service providers, policy makers, consumers, and other key stakeholders. It is also known as co-production, co-design and co-construction. Co-creation is often a buzzword with fuzzy meanings of who collaborates with whom, when and how (processes) and to what end (outcomes) in addressing sustainability and other complex problems. Yet there is emerging evidence on best practices of co-creation. Although this evidence is mostly based on individual case studies or comparisons of small sets of cases, the following eight strategies provide valuable guidance for researchers and practitioners.

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Six types of unknowns in interdisciplinary research

By Gabriele Bammer

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Gabriele Bammer (biography)

What types of unknowns are tackled in interdisciplinary research?  I draw on my experience directing a program of research on the feasibility of prescribing pharmaceutical heroin as a treatment for heroin dependence. Analysis of this case revealed six different types of unknowns:

  1. Disciplinary unknowns
  2. Unknowns of concern to stakeholders
  3. Unknowns marginalised by power imbalances
  4. Unknowns in the overlap between disciplines
  5. New problem-based unknowns
  6. Intractable unknowns.

Read moreSix types of unknowns in interdisciplinary research

Can co-creation achieve better outcomes for people and communities?

By Deborah Ghate

deborah-ghate
Deborah Ghate (biography)

The language of ‘co-processes’ is much in vogue in policy, practice and academic communities worldwide. In commerce, product design and politics, the power of the crowd has long been recognised, but can co-processes be harnessed for the public good? The answer, right now, appears to be ‘maybe’.

What are co-processes and what are they for?

The briefest survey of the literature on co-processes confirms there is substantial variation in how they are defined and what methods or techniques they include. A confusing multiplicity of related terms exists—co-construction, co-production, co-design, co-innovation, co-creation—all are in regular use, sometimes interchangeably, and often defined at an unhelpful level of abstraction (for more on this topic see the blog post by Allison Metz on Co-creation, co-design, co-production, co-construction: same or different?). Nevertheless, however we define co-processes, participatory methods, boundary-spanning and inclusivity to varying degrees are foundational principles that can be detected in most accounts. Beyond that, the stated purposes and proposed outcomes vary considerably.

Read moreCan co-creation achieve better outcomes for people and communities?

Knowledge synthesis and external representations

By Deana Pennington

Deana Pennington (biography)

Over a decade ago I became interested in the role of external artifacts in enabling knowledge synthesis across disciplinary perspectives, where external artifacts are any simplified physical representation of real phenomena that enable human manipulation of complex concepts. A simulation model is one example of an external artifact. In general every simplified representation of reality is a model, whether that representation occurs in our heads (mental models), on paper (conceptual models) or in a sophisticated computer-based simulation model. And so I embarked on a research agenda to understand the role of data, models, and other forms of external representations in enabling integration and synthesis across perspectives.

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Responding to stakeholders – lessons learnt

By Klaus Hubacek and Christina Prell

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Klaus Hubacek (biography)
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Christina Prell (biography)

Being responsive to stakeholder interests and suggestions is important for successful participatory modeling. We share lessons from an exciting, five year project in the UK entitled the Sustainable Uplands. The project sought to bring together a variety of groups ranging from academics, policy makers, residents, conservationists, and different ‘end user’ groups that all, in some way, held a stake in upland park areas in the UK.

Our process was iterative, tacking back and forth between field work, consultations among the research team, consultations with non-academic stakeholders, and modeling. Not only were our models heavily influenced by what stakeholders told us were important values and considerations regarding upland areas, but these also informed how we went about gathering the data.

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Designing applied research for impact

By Andrew Campbell

andrew-campbell
Andrew Campbell (biography)

How can we get the three critical groups in transdisciplinary research—researchers, end users of research, and funders of research—to work together in designing applied research for impact? As Roux and colleagues (2010) pointed out:

A key characteristic of transdisciplinary research is that the domains of science, management, planning, policy and practice are interactively involved in issue framing, knowledge production and knowledge application.”

A critical challenge is that each of the three groups is likely to have different perspectives on the goals of a given research project or program and how to achieve them, and therefore likely to define success differently.

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Modeling as empowerment

By Laura Schmitt Olabisi

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Laura Schmitt Olabisi (biography)

Who can make systems change? The challenges of complexity are intensely felt by those who are trying to make strategic interventions in coupled human-environmental systems in order to fulfill personal, societal, or institutional goals. The activists, leaders, and decision-makers I work with often feel overwhelmed by trying to deal with multiple problems at once, with limited time, resources, and attention. We need tools to help leaders cut through the complexity so that they can identify the most effective strategies to make change.

This is where participatory system dynamics modelers like myself come in.

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Transdisciplinarity: Learning together to teach together

By BinBin Pearce, Carolina Adler and Christian Pohl

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BinBin Pearce (biography)

Are there innovative methods that enable students to frame and confront the complexity of real-world problems in the context of sustainable development? Which learning approaches help students engage with design thinking to understand a particular system, and also to start thinking about responsible solutions? Which approaches enable students to reflect on their own actions, as well as become aware of the importance of diverse stakeholder perspectives and how these play out in real-world contexts?

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Should water scientists be advocates?

By Patricia Gober

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Patricia Gober (biography)

Efforts to improve the use of models to support policy and practice on water resources issues have increased awareness of the role of advocacy and public engagement in the modeling process. Hydrologists have much to learn from the recent experience of climate scientists who have discovered that scientific knowledge is not independent of the political context in which it is used but rather is co-produced by scientists and society.

Despite a strong consensus among climate scientists in the Intergovernmental Panel on Climate Change’s (IPCC) 2013 report that “warming of the climate system is unequivocal,” approximately one-third of the USA’s population still does not believe that global temperatures have risen over the past 100 years and does not trust the things that scientists say about the environment.

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Looking over the horizon for team effectiveness

By Stephen M. Fiore

Stephen M. Fiore (biography)

How can we better understand how to improve team effectiveness, as well as help society more broadly? In the last decade, there has been a great deal of growth of interdisciplinary research on teams, thanks to organizations like the Interdisciplinary Network for Group Research and the developing field of the Science of Team Science.

New areas

The study of teams has long been making important contributions to business organizations, the military, and healthcare and is now branching out to scientific research teams, cyber security teams, and even spaceflight teams. Each of these domains is of significant societal relevance for the 21st century. They represent important topics for what is called use-inspired basic science.

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La modélisation participative, un lieu privilégié pour l’interdisciplinarité? / Participatory modeling: An ideal place for interdisciplinarity?

By Pierre Bommel

bommel
Pierre Bommel (biography)

An English version of this post is available

La modélisation participative cherche à impliquer un groupe de personnes dans la conception et la révision d’un modèle. L’objectif à terme consiste à mieux caractériser les problèmes actuels et imaginer collectivement comment tenter de les résoudre. Dans le domaine de l’environnement en particulier, il apparaît nécessaire que les acteurs concernés se sentent impliqués dans la démarche de modélisation, afin qu’ils puissent exprimer leurs propres points de vue, mais aussi pour mieux s’engager dans des décisions collectives. De ce fait, pour aborder la gestion intégrée des ressources, il est nécessaire de mettre les acteurs au centre des préoccupations de recherche, à la fois lors de la phase la conception du modèle mais aussi pour l’exploration de ces scénarios.

Read moreLa modélisation participative, un lieu privilégié pour l’interdisciplinarité? / Participatory modeling: An ideal place for interdisciplinarity?