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

Caulkins JP, Feichtinger G, Grass D, Hartl RF, Kort PM, and Seidl A (2017) Interaction of Pricing, Advertising and Experience Quality: A Dynamic Analysis. European Journal of Operational Research, 256 (3). pp. 877-885.

Watanabe C, Naveed K, Neittaanmäki P, and Fox B (2017) Consolidated challenge to social demand for resilient platforms- lessons from Uber's global expansion. Technology in Society, 48. pp. 33-53.

Thurner, S., ed. (2017) 43 Visions for Complexity. Exploring Complexity, 3 . World Scientific, Singapore. ISBN 978-981-3206-84-7

Thurner S (2017) Data driven dark ages. In: 43 Visions for Complexity. Exploring Complexity, 3 . World Scientific, Singapore, pp. 73-74. ISBN 978-981-3206-84-7

Kharrazi A, Akiyama T, Yu Y, and Li J (2016) Evaluating the evolution of the Heihe River basin using the ecological network analysis: Efficiency, resilience, and implications for water resource management policy. Science of the Total Environment, 572. pp. 688-696.

Jessie D and Saari DG (2016) From the Luce Choice Axiom to the Quantal Response Equilibrium. Journal of Mathematical Psychology, 75. pp. 3-9.

Manzoor T, Rovenskaya E, and Muhammad A (2016) Game-theoretic insights into the role of environmentalism and social-ecological relevance: A cognitive model of resource consumption. Ecological Modelling, 340. pp. 74-85.

Aseev S and Manzoor T (2016) Optimal Growth, Renewable Resources and Sustainability. IIASA Working Paper. WP-16-017, IIASA, Laxenburg, Austria

Aseev SM, Krastanov MI, and Veliov VM (2016) Optimality Conditions for Discrete-Time Optimal Control on Infinite Horizon. Reseach Unit ORCOS, Vienna University of Technology

Dobrinsky R, Adarov A, Bornukova K, Havlik P, Hunya G, Kruk D, and Pindyuk O (2016) The Belarus Economy: The Challenges of Stalled Reforms. wiiw Research Report No.413. The Vienna Institute for International Economic Studies, Vienna, Austria

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