My research focuses on the interaction of cognitive, institutional, and ecological processes to understand collective action problems. I study these interactions to understand the conditions for sustainable outcomes in various applications in the past, present and future, and from local to global scales.
I am a social scientist with a background in mathematics. I use computational models, such as agent-based models, in combination with laboratory and field experiments, surveys, case study analysis, and stakeholder workshops. To address my research questions.I have worked on quite a number of topics as you can see from my publications, all related to the field of collective action.
The National Science Foundation of the USA funds most of my research since 2004. Prior to that I was funded by the European Union, the Swedish Research Council, and the Resilience Alliance. Currently I work on the following topics:
Water, energy and food systems are increasingly interconnected. To meet sustainability targets transitions in those systems are needed to reduce greenhouse gas emissions, provide sufficient clean fresh water, and nutritious food. A transition of the physical infrastructure will require changes in behavior, norms and regulations, but the dynamics of the physical infrastructure and human behavior are not synced. We are developing models combining insights from the social science and engineering to explore transition pathways that are socially just and enable robustness of water, energy and food systems in the long term. Current focus is on the governance of decentralized energy systems, especially on the role of solar energy. Previous work included two NSF projects: One on water governance of Mexico city (PI Eakin) and one on resilience of water-energy-road networks (PI Seager).
As part of ASU’s Interplanetary Initiative, CBIE is exploring the challenges related to shared resource governance for a future habitat on Mars. A game is developed where players need to choose between investing in the shared infrastructure and individual accomplishments to earn points to win the game. Basically the research is about decision making under uncertainty. What makes groups successful in terms of their personalities, group dynamics and communication. You can play the game at https://portofmars.asu.edu/.
As part of a NASA grant (PI Siddiqi) we are exploring whether and how to apply sustainability frameworks to the governance of lunar surface. Over a dozen nations have expressed plans for engaging in robotic and human missions to the Moon. The Artemis campaign explicitly aims for sustainable exploration, and its current plans include crewed and robotic operations on the lunar surface. With growing interest in lunar surface exploration and goals of sustainability, it is important and timely to explore what lunar surface sustainability means. This research aims to develop a novel framework for evaluating lunar surface sustainability. Specifically, it will 1) develop a set of definitions of sustainability relevant to the lunar exploration context, 2) formulate guiding principles for governance for multi-actor exploration, 3) construct quantitative metrics for evaluating sustainability of lunar surface activities
There have been anecdotes that field experiments on commons dilemmas in communities have led to behavioral changes. In a project led by International Food Policy Research Institute we are testing whether performing field experiments on crop choice and groundwater together with a community wide debriefing lead to a measurable change in ground water use. The experiments are done in India and Colombia. The potential outcome is a practical tool for NGOs to stimulate behavioral change.
Watch related PBS documentary here.
There is an increase in the use of computational models, such as agent-based models, in the social and life sciences, but typically only results are shared in publications. Model code is not provided with publications, which hinders the cumulative nature of scientific discovery. The website comses.net is an ongoing attempt to build cyber-infrastructure where scholars can archive their models using best practices. In this way we preserve well documented model code on which other scholars can build on.
