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.
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.
Last edited: 08 September 2016
Komendantova N ORCID: https://orcid.org/0000-0003-2568-6179, Schinko T, & Patt A (2019). De-risking policies as a substantial determinant of climate change mitigation costs in developing countries: Case study of the Middle East and North African region. Energy Policy 127: 404-411. DOI:10.1016/j.enpol.2018.12.023.
Xu Z, Chau SN, Ruzzenenti F, Connor T, Li Y, Tang Y, Li D, Gong M, et al. (2019). Evolution of multiple global virtual material flows. Science of the Total Environment 658: 659-668. DOI:10.1016/j.scitotenv.2018.12.169.
Li Z, Wang Z, Liu X, Fath B, Liu X, Xu Y, Hutjes R, & Kroeze C (2019). Causal relationship in the interaction between land cover change and underlying surface climate in the grassland ecosystems in China. Science of the Total Environment 647: 1080-1087. DOI:10.1016/j.scitotenv.2018.07.401.
Palokangas T (2019). Emission permit trading with a self-interested regulator. Environmental Economics and Policy Studies DOI:10.1007/s10018-019-00236-8. (In Press)
Folberth C, Baklanov A, Balkovic J, Skalsky R, Khabarov N, & Obersteiner M (2019). Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning. Agricultural and Forest Meteorology 264: 1-15. DOI:10.1016/j.agrformet.2018.09.021.
Schinko T ORCID: https://orcid.org/0000-0003-1156-7574, Bohm S, Komendantova N ORCID: https://orcid.org/0000-0003-2568-6179, Jamea El M, & Blohm M (2019). Morocco’s sustainable energy transition and the role of financing costs: a participatory electricity system modeling approach. Energy, Sustainability and Society 9 (1): 1-17. DOI:10.1186/s13705-018-0186-8.
Charkovska N, Halushchak M, Bun R, Nahorski Z, Oda T, Jonas M, & Topylko P (2019). A high-definition spatially explicit modelling approach for national greenhouse gas emissions from industrial processes: reducing the errors and uncertainties in global emission modelling. Mitigation and Adaptation Strategies for Global Change DOI:10.1007/s11027-018-9836-6. (In Press)
Tellez Leon Elizabeth & Ibarra R (2019). Are all types of capital flows driven by the same factors? Evidence from Mexico. Empirical Economics DOI:10.1007/s00181-019-01624-5. (In Press)
Savaget P, Geissdoerfer M, Kharrazi A, & Evans S (2019). The theoretical foundations of sociotechnical systems change for sustainability: A systematic literature review. Journal of Cleaner Production 206: 878-892. DOI:10.1016/j.jclepro.2018.09.208.
Wang S, Fath B, & Chen B (2019). Energy–water nexus under energy mix scenarios using input–output and ecological network analyses. Applied Energy 233-23: 827-839. DOI:10.1016/j.apenergy.2018.10.056.
International Institute for Applied Systems Analysis (IIASA)
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