ASA Program aims to discover, develop, and deploy new, more effective, and efficient ways of infusing systems science into policy and decision making for sustainable development.
Despite numerous success stories, many policies and decisions that currently aim to deal with global change are not sufficiently informed by cutting-edge science. Among the major barriers that prevent the effective input of science into policy are perceived shortfalls in agility, realism, and relevance of the current generation of methods and models from the standpoint of end users. To address these barriers, ASA strives to advance agile, realistic, and relevant systems analytical tools and methods, and facilitate a shared understanding of the capabilities and limits of these tools and methods with end users. Consequently, ASA’s efforts span the full range, from advancing research methods and tools of systems analysis to innovating at the interface between policy- and decision making, as well as with society at large.
ASA Program’s major objectives are:
- To innovate approaches and tools to analyze increasingly systemic, social-ecological risks and support decisions aimed at enhancing resilience and facilitating sustainability transitions and transformations.
- To further the capacity of agile, on-demand systems analysis underpinned by a suite of modeling frameworks of appropriate complexity.
- To mobilize multiple sources of data and the power of data science to diagnose and identify solutions to reduce vulnerabilities and risks.
- To advance feasible and effective ways of engagement with policymakers, the private sector, and citizens.
- To enhance trust and shared understanding of systems analysis methods and tools, in particular, through open science.
Models, tools, datasets
03 February 2023
25 January 2023
19 December 2022
05 December 2022
04 December 2022
28 November 2022
Atolia, M., Loungani, P., Maurer, H., & Semmler, W. (2023). Optimal control of a global model of climate change with adaptation and mitigation. Mathematical Control and Related Fields 13 (2) 583-604. 10.3934/mcrf.2022009.
Neuvonen, L., Wildemeersch, M. , & Vilkkumaa, E. (2023). Supporting strategy selection in multiobjective decision problems under uncertainty and hidden requirements. European Journal of Operational Research 307 (1) 279-293. 10.1016/j.ejor.2022.09.036.
Filippi, M.E., Barcena, A., Sakic Trogrlic, R., Cremen, G., Menteşe, E.Y., Gentile, R., Creed, M.J., Jenkins, L.T., Kalaycioglu, M., Poudel, D.P., Muthusamy, M., Manandhar, V., Adhikari, S., Rai, M., Dhakal, A., Barake, B., Tarbali, K., Galasso, C., & McCloskey, J. (2023). Interdisciplinarity in practice: Reflections from early-career researchers developing a risk-informed decision support environment for Tomorrow's cities. International Journal of Disaster Risk Reduction 85 e103481. 10.1016/j.ijdrr.2022.103481.
Wang, J., Ciais, P., Gasser, T. , Chang, J., Tian, H., Zhao, Z., Zhu, L., Li, Z., & Li, W (2023). Temperature Changes Induced by Biogeochemical and Biophysical Effects of Bioenergy Crop Cultivation. Environmental Science & Technology 10.1021/acs.est.2c05253. (In Press)