What makes scenarios useful to decision makers in effectively planning for the future? Here I discuss three aspects of scenarios:
use and defensibility.
Goals of scenarios
Since predicting the future is not possible, it’s important to know that scenarios are not predictions. Instead, scenarios stimulate thinking and conversations about possible futures. Continue reading →
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).
Agent-based modelling is particularly effective where understanding is more important than prediction. This is because agent-based models can represent the real world in a very natural way, making them more accessible than some other types of models. Continue reading →
Community member post by Siobhan Bourke and Emily Lancsar
How can researchers interested in complex societal and environmental problems best understand and deal with uncertainty, which is an inherent part of the world in which we live? Accidents happen, governments change, technological innovation occurs making some products and services obsolete, markets boom and inevitably go bust. How can uncertainty be managed when all possible outcomes of an action or decision cannot be known? In particular, are there lessons from the discipline of economics which have broader applicability? Continue reading →
Community member post by Dan Stokols, Maritza Salazar, Gary M. Olson, and Judith S. Olson
How can cross-disciplinary research teams increase their capacity for generating and integrating novel research ideas and conceptual frameworks?
A key challenge faced by research teams is harnessing the intellectual synergy that can occur when individuals from different disciplines join together to create novel ideas and conceptual frameworks. Studies of creativity suggest that atypical (and often serendipitous) combinations of dissimilar perspectives can spur novel insights and advances in knowledge. Yet, many cross-disciplinary teams fail to achieve intellectual synergy because they allot insufficient effort to generating new ideas. Here we describe a brainstorming tool that can be used to generate new ideas in cross-disciplinary teams. Continue reading →
Community groups are often consulted by researchers, government agencies and industry. The issues may be contentious and the relationship vexed by distrust and poor communication. Could an inventory capture the fundamental sources of community frustration and highlight scope for improvement in respect, transparency, fairness, co-learning, and meeting effectiveness from a community perspective?
The trust and empowerment inventory presented below is based on the main sources of community frustration that I have witnessed over two decades as a public health physician and researcher liaising with communities about environmental health risks and it is likely to have broader relevance. Key issues include not being listened to; not being fully informed; Continue reading →
What are conceptual models? How can conceptual modelling effectively represent complex topics and assist communication among people from different backgrounds and disciplines?
This blog post describes ConML, which stands for “Conceptual Modelling Language”. ConML is a specific modelling language that was designed to allow researchers who are not expert in information technologies to create and develop their own conceptual models. It is useful for the humanities, social sciences and experimental sciences. Continue reading →