Participatory modelling – Integration and Implementation Insights

Participatory scenario planning

December 13, 2022December 6, 2022

authors_maike-hamann_tanja-hichert_nadia-sitas — 1. Maike Hamann (biography)
2. Tanja Hichert (biography)
3. Nadia Sitas (biography)

By Maike Hamann, Tanja Hichert and Nadia Sitas

Within the many different ways of developing scenarios, what are useful general procedures for participatory processes? What resources are required? What are the strengths and weaknesses of involving stakeholders?

Scenarios are vignettes or narratives of possible futures, and when used in a set, usually depict purposefully divergent visions of what the future may hold. The point of scenario planning is not to predict the future, but to explore its uncertainties. Scenario development has a long history in corporate and military strategic planning, and is also commonly used in global environmental assessments to link current decision-making to future impacts. Participatory scenario planning extends scenario development into the realm of stakeholder-engaged research.

Leadership in participatory modelling

September 23, 2021February 2, 2021

By Raimo P. Hämäläinen, Iwona Miliszewska and Alexey Voinov

moasaic_authors_raimo-hamalainen_iwona-miliszewska_alexey-voinov — 1. Raimo P. Hämäläinen (biography)
2. Iwona Miliszewska (biography)
3. Alexey Voinov (biography)

What can leadership discourse in the business literature tell us for leadership in participatory modelling?

Here we explore:

the difference between leadership and management in participatory modelling
different leadership styles and participatory modelling
three key leadership issues in participatory modelling: responsibility for best practices and ethics, competences, and who in the participatory modelling team should lead.

How does leadership differ from management in participatory modelling?

Four patterns of thought for effective group decisions

April 15, 2022July 30, 2019

By George P. Richardson and David F. Andersen

authors_george-richardson_david-andersen — 1. George P. Richardson (biography)
2. David F. Andersen (biography)

What can you do if you are in a group that is trying to deal with problems that are developing over time, where:

root causes of the dynamics aren’t clear;
different stakeholders have different perceptions;
past solutions haven’t worked;
solutions must take into account how the system will respond; and,
implementing change will require aligning powerful stakeholders around policies that they agree have the highest likelihood of long-term success?

The fields of systems thinking and system dynamics modelling bring four important patterns of thought to such a group decision and negotiation:

Agent-based modelling for knowledge synthesis and decision support

April 15, 2022June 25, 2019

By Jen Badham

The most familiar models are predictive, such as those used to forecast the weather or plan the economy. However, models have many different uses and different modelling techniques are more or less suitable for specific purposes.

Here I present an example of how a game and a computerised agent-based model have been used for knowledge synthesis and decision support.

The game and model were developed by a team from the Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), a French agricultural research organisation with an international development focus. The issue of interest was land use conflict between crop and cattle farming in the Gnith community in Senegal (D’Aquino et al. 2003).

Synthesis of knowledge about participatory modeling: How a group’s perceptions changed over time

August 24, 2022July 3, 2018

By Rebecca Jordan

How do a group’s perceptions change over time, when members across a range of institutions are brought together at regular intervals to synthesize ideas? Synthesis centers have been established to catalyze more effective cross-disciplinary research on complex problems, as described in the blog post ‘Synthesis centers as critical research infrastructure‘, by Andrew Campbell.

I co-led a group synthesizing ideas about participatory modeling as one of the activities at the National Socio-Environmental Synthesis Center (SESYNC). We met in Annapolis, Maryland, USA, four times over three years for 3-4 days per meeting. Our task was to synthesize what is known about participatory modeling tools, processes, and outcomes, especially in environmental and natural resources management contexts.

What’s in a name? The role of storytelling in participatory modeling

August 24, 2022June 13, 2017

By Alison Singer

That which we call a rose,
by any other name would smell as sweet.

That Shakespeare guy really knew what he was talking about. A rose is what it is, no matter what we call it. A word is simply a cultural agreement about what we call something. And because language is a common thread that binds cultures together, participatory modeling – as a pursuit that strives to incorporate knowledge and perspectives from diverse stakeholders – is prime for integrating stories into its practice.

To an extent, that’s what every modeling activity does, whether it’s through translating an individual’s story into a fuzzy cognitive map, or into an agent-based model. But I would argue that the drive to quantify everything can sometimes make us lose the richness that a story can provide.

Citizen science and participatory modeling

August 24, 2022February 2, 2017

By Rebecca Jordan and Steven Gray

authors_rebecca-jordan_steven-gray — 1. Rebecca Jordan (biography)
2. Steven Gray (biography)

As investigators who engage the public in both modeling and research endeavors we address two major questions: Does citizen science have a place within the participatory modeling research community? And does participatory modeling have a place in the citizen science research community?

Let us start with definitions. Citizen science has been defined in many ways, but we will keep the definition simple. Citizen science refers to endeavors where persons who do not consider themselves scientific experts work with those who do consider themselves experts (around a specific issue) to address an authentic research question.

Dealing with deep uncertainty: Scenarios

October 25, 2022January 5, 2017

By Laura Schmitt Olabisi

What is deep uncertainty? And how can scenarios help deal with it?

Deep uncertainty refers to ‘unknown unknowns’, which simulation models are fundamentally unsuited to address. Any model is a representation of a system, based on what we know about that system. We can’t model something that nobody knows about—so the capabilities of any model (even a participatory model) are bounded by our collective knowledge.

One of the ways we handle unknown unknowns is by using scenarios. Scenarios are stories about the future, meant to guide our decision-making in the present.

Uncertainty in participatory modeling – What can we learn from management research?

August 24, 2022November 10, 2016

By Antonie Jetter

I frequently struggle to explain how participatory modeling deals with uncertainty. I found useful guidance in the management literature.

After all, participatory modeling projects and strategic business planning have one commonality – a group of stakeholders and decision-makers aims to understand and ultimately influence a complex system. They do so in the face of great uncertainty that frequently cannot be resolved – at least not within the required time frame. Businesses, for example, have precise data on customer behavior when their accountants report on annual sales. However, by this time, the very precise data is irrelevant because the opportunity to influence the system has passed.

Model complexity – What is the right amount?

August 24, 2022November 3, 2016

By Pete Loucks

How does a modeler know the ’optimal’ level of complexity needed in a model when those desiring to gain insights from the use of such a model aren’t sure what information they will eventually need? In other words, what level of model complexity is needed to do a job when the information needs of that job are uncertain and changing?

Simplification is why we model. We wish to abstract the essence of a system we are studying, and estimate its likely performance, without having to deal with all its detail. We know that our simplified models will be wrong. But, we develop them because they can be useful. The simpler and hence the more understandable models are the more likely they will be useful, and used, ‘as long as they do the job.’

ICTAM: Bringing mental models to numerical models

August 24, 2022September 22, 2016

By Sondoss Elsawah

How can we capture the highly qualitative, subjective and rich nature of people’s thinking – their mental models – and translate it into formal quantitative data to be used in numerical models?

This cannot be addressed by a single method or software tool. We need multi-method approaches that have the capacity to take us through the learning journey of eliciting and representing people’s mental models, analysing them, and generating algorithms that can be incorporated into numerical models.

More importantly, this methodology should allow us to see in a transparent way the progression on this learning journey.

Participatory processes and participatory modelling: The sustainable procedure framework

August 24, 2022September 15, 2016

By Beatrice Hedelin

How can we resolve debates about participatory processes between proponents and skeptics? What role can participatory modelling play in improving participatory processes?

Proponents argue for the merits of participatory processes, which include learning; co-production of knowledge; development of shared understanding of a problem and shared goals; creation of trust; and local power and ownership of a problem.

Sceptics point to evidence of inefficient, time-consuming, participatory processes that escalate conflict and mistrust. They also highlight democratic problems; lack of transparency; and powerful actors that benefit in relation to weaker ones such as the unorganized, poor, and uneducated.