Overview

ASA’s innovations in methodology and exploratory applications to case studies respond to IIASA’s Strategic Plan 2011-2020, which, in particular, emphasizes the need for “innovation and exploration ... to cope with rapid changes and new crises and opportunities”, suggesting that “A new infusion of advanced systems analysis models and techniques in the exploratory and innovative research projects … will help IIASA to achieve international recognition as the leader in systems analysis and integrated assessments on a global scale.”

ASA’s mission

ASA’s mission is to develop, test, and make available new quantitative and qualitative methods from areas including mathematics, statistics, operations research, and management science for addressing problems arising in the policy analysis of complex socio-environmental systems. 

Thereby, ASA’s activities advance IIASA’s ability to conduct research to improve human and societal well-being, as well as environmental quality by allowing for solving problems that cannot be addressed by existing tools and by enabling solving problems more efficiently.

Why are new methods needed? 

We live in a VUCA world: 

  • V stands for Volatility
  • U stands for Uncertainty
  • C stands for Complexity, and
  • A stands for Ambiguity 

The term “VUCA” was coined by U.S. Army analysts to describe the changing geo-political landscape in the late 1980s - early 1990s. It then spread to the business world, where it is currently popular for describing a challenging environment, in which corporate decision makers must develop strategies that will bring success in spite of the challenges.

The VUCA challenge is equally relevant to policy making, national and international. 

What should advanced systems analysis be capable of?

In our view, systems analysis would move to the next level of relevance to real-life policy in a VUCA-world, if it could advance in several major directions, including finding effective and efficient ways to benefit from the multiplicity of models, to take maximal advantage of big and small data, to account for uncertainty, interconnectednes, non-linearity, and heterogeneity of agents, to recognize the multi-objective nature of decision making, to add more realism to model assumptions on agents’ behavior, and to contribute to the actual policy design. 

ASA’s research

The above listed challeneges are relevant to a vast array of particular instances of socio-environmental systems. Specifically, we consider (this list is certainly not exhaustive)

  • Ecosystems and natural resource management, food-water-energy systems, and climate;
  • Economic systems linked with population, technology and the environment;
  • Global and regional trade networks, networks of virtual (embodied) water and emissions, supply chains, multi-sector and multi-regional production;
  • Systems supporting national well-being

To be able to develop and advance the above listed capabilities, we employ

  • Optimization theory, including stochastic optimization and control theory, game theory, multi-objective analysis;  
  • Complexity science and network theory;  
  • Dynamic systems and simulations, including agent-based modeling (ABM);
  • Data analysis and machine learning;
  • Qualitative systems modeling, scenario planning, and foresight techniques;
  • Participatory modeling and stakeholders dialogue.

Some selected highlights in the current research cycle (2016-2020) are

  • Advancement of the methodology of stochastic optimization to address problems of catastrophic risk management including the applications to insurance;
  • Exploration of the usefulness of network analysis, including approaches based on information theory, to study the resilience of natural systems (ecosystems) and man-made systems (virtual water and emission flows, trade etc.);
  • Development of network-based policies to mitigate financial systemic risk (including the ‘systemic risk tax’);
  • Pioneering the creation and application of large-scale simulators of national economies representing realistic behavior rules of agents (economic ABMs);
  • Exercising stakeholder engagement processes to support sense-making and consensus-building by policy makers on issues of strategic importance for their countries/regions. 

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Last edited: 07 February 2019

CONTACT DETAILS

Elena Rovenskaya

Program Director

Advanced Systems Analysis

Acting Program Director

Evolution and Ecology

T +43(0) 2236 807 608

PUBLICATIONS

Hunt J , Zakeri B, Lopes R, Barbosa P, Nascimento A, Castro N, Brandão R, Schneider P, et al. (2020). Existing and new arrangements of pumped-hydro storage plants. Renewable and Sustainable Energy Reviews 129: e109914. DOI:10.1016/j.rser.2020.109914.

Yegorov Y, Wirl F, Grass D, Eingruber M, & Feichtinger G (2020). On the Matthew effect on Individual Investments into Skills in Arts, Sports and Science. IIASA Working Paper. Laxenburg, Austria: WP-20-009

Saviolidis NM, Davíðsdóttir B, Ilmola-Sheppard L, Stepanova A, Valman M, & Rovenskaya E (2020). Realising blue growth in the fishing industry in Iceland and Norway: Industry perceptions on drivers and barriers to blue growth investments and policy implications. Marine Policy 117: e103967. DOI:10.1016/j.marpol.2020.103967.

Molina C , Akçay E, Dieckmann U , Levin S, & Rovenskaya E (2020). Combating climate change with matching-commitment agreements. Scientific Reports 10: e10251. DOI:10.1038/s41598-020-63446-1.

Liang S, Yu Y, Kharrazi A , Fath B , Feng C, Daigger GT, Chen S, Ma T, et al. (2020). Network resilience of phosphorus cycling in China has shifted by natural flows, fertilizer use and dietary transitions between 1600 and 2012. Nature Food 1 (6): 365-375. DOI:10.1038/s43016-020-0098-6.

Makarov V, Bakhtizin A, Beklaryan G, Akopov A, Rovenskaya E, & Strelkovskii N (2020). Agent-based modelling of population dynamics of two interacting social communities: migrants and natives. Ekonomika i matematicheskie metody 56 (2): 5-19. DOI:10.31857/S042473880009217-7.

Feichtinger G, Grass D, Kort PM, & Seidl A (2020). On the Matthew effect in research careers: Abnormality on the boundary. IIASA Working Paper. Laxenburg, Austria: WP-20-008

Luo Y, Pang L, Zhao Y, Guo C, Zhang L, & Zheng X (2020). Gender difference in the association between education and schizophrenia in Chinese adults. BMC Psychiatry 20 (1) DOI:10.1186/s12888-020-02700-2.

Strelkovskii N & Orlov S (2020). Program Packages Method for Solution of a Linear Terminal Control Problem with Incomplete Information. In: Stability, Control and Differential Games. pp. 213-223 Springer. 10.1007/978-3-030-42831-0_19.

Orlov S & Strelkovskii N (2020). Calculation of Elements of a Guiding Program Package for Singular Clusters of the Set of Initial States in the Package Guidance Problem. Proceedings of the Steklov Institute of Mathematics 308 (S1): 163-177. DOI:10.1134/S0081543820020133.

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