Overview

ASA research ultimately aims to produce, practice, and prototype novel system-analytical approaches, methods and tools, which enable solving problems that cannot be addressed by existing tools, or which enable addressing problems more efficiently.

© Aprescindere | Dreamstime.com

© Aprescindere | Dreamstime.com

Referring to the methodological dimension of the IIASA’s mandate, the ASA Program’s overall mission is to advance systems analysis by substantiating the integration of systems methods and applied research on problems of global relevance and universal importance. Central to this mission is the exploratory development of mathematical methods and analytical techniques to investigate complex systems undergoing global change with a focus on an integrated, interdisciplinary approach. 

ASA’s research is organized around three mutually complementing and cross-fertilizing methodological research domains. 

Optimal behavior of systems






  • Focus on how decision making can be formalized in models, notably, under uncertainty and risks, and what consequences different decisions yield
  • Develop decision support tools and applications, which are traditionally based on the optimization of a utility describing decision-maker’s preferences
  • Employ and advance methods of the optimization theory, control theory, theory of dynamic systems, and other related fields
  • Applications to economic models, notably, long-term economic growth (also under environmental constraints) and resource management models

Interactions within systems






  • Focus on the role of indirect links and connectivity between individual systems within a larger networked system
  • Employ and advance methods of the graph theory, information theory, network analysis and other related fields are employed
  • Develop network-based modeling and assessment frameworks
  • Ecological and social applications
  • Some methodologies are also being transferred to other disciplinary areas, for example, to economics, energy policy, and resource management 

System transitions and resilience of systems





  • Focus on systems of systems, characterized by complex dynamics, decentralized decision-making, and significant uncertainties with the aim to study system’s resilience
  • Experiment with qualitative (e.g., soft systems mapping) and quantitative (e.g., agent-based modeling) methods and approaches to evaluate possible consequences of extreme shocks affecting the system under study and, based on that, system resilience
  • Develop novel methods of data analysis aiming to identify precursors of system flips and general patterns via learning from the past 

More info is available under the following links:

In accordance with its strategy, ASA is actively maintaining and expanding its network consisting of methodologists, applied scientists and decision-makers all over the world, and, based on it, develops international and interdisciplinary collaboration.




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Last edited: 08 September 2016

CONTACT DETAILS

Elena Rovenskaya

Program Director

Advanced Systems Analysis

T +43(0) 2236 807 608

PUBLICATIONS

Kautzky-Willer A, Thurner S, & Klimek P (2017). Use of statins offsets insulin-related cancer risk. Journal of Internal Medicine 281 (2): 206-216. DOI:10.1111/joim.12567.

Sato M, Kharrazi A, Nakayama H, Kraines S, & Yarime M (2017). Quantifying the supplier-portfolio diversity of embodied energy: Strategic implications for strengthening energy resilience. Energy Policy 105: 41-52. DOI:10.1016/j.enpol.2017.02.024.

Aseev S & Veliov V (2017). Another View of the Maximum Principle for Infinite-Horizon Optimal Control Problems in Economics. Operations Research and Control Systems, Vienna University of Technology

Franklin O, Han W, Dieckmann U, Cramer W, Brännström A, Pietsch S, Rovenskaya E, & Prentice IC (2017). Using natural selection and optimization for smarter vegetation models - challenges and opportunities. In: European Geosciences Union (EGU) General Assembly 2017, 23–28 April 2017, Vienna, Austria.

Puaschunder J (2017). Socio-Psychological Motives of Socially Responsible Investors. In: Global Corporate Governance. Eds. John, K., Makhija, A.K. & Ferris, S.P., Advances in Financial Economics, 19 . pp. 209-247 Bingley, UK: Emerald Publishing Limited. ISBN 978-1-78635-165-4 DOI:10.1108/S1569-373220160000019008.

Naveed K, Watanabe C, & Neittaanmäki P (2017). Co-evolution between streaming and live music leads a way to the sustainable growth of music industry – Lessons from the US experiences. Technology in Society DOI:10.1016/j.techsoc.2017.03.005. (In Press)

Haak DM, Fath B, Forbes VE, Martin DR, & Pope KL (2017). Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species. Journal of Environmental Management 190 (1): 243-251. DOI:10.1016/j.jenvman.2016.12.012.

Poledna S, Bochmann O, & Thurner S (2017). Basel III capital surcharges for G-SIBs are far less effective in managing systemic risk in comparison to network-based, systemic risk-dependent financial transaction taxes. Journal of Economic Dynamics and Control 77: 230-246. DOI:10.1016/j.jedc.2017.02.004.

Yu Y, Zhou L, Zhou W, Ren H, Kharrazi A, Ma T, & Zhu B (2017). Decoupling environmental pressure from economic growth on city level: The Case Study of Chongqing in China. Ecological Indicators 75: 27-35. DOI:10.1016/j.ecolind.2016.12.027.

Arimoto T, Barros LF, Bergmann M, Berkman PA, AL-Bulushi YBA, Colglazier WE, Copeland D, Chernukhin E, et al. (2017). A Global Network of Science and Technology Advice in Foreign Ministries. Science & Diplomacy (Submitted)

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313