Research outcomes
Peer-reviewed journal articles
2022
JP 9. Cinelli, M.; Kadziński, M.; Burgerr, P.; Słowiński, R. Proper and improper uses of MCDA methods in energy systems analysis. Decision Support Systems, 2022. 163: 113848. https://doi.org/10.1016/j.dss.2022.113848
JP 8. Cinelli, M.; Kadziński, M.; Miebs, G.; Gonzalez, M.; Słowiński, R. Recommending Multiple Criteria Decision Analysis Methods with A New Taxonomy-based Decision Support System. European Journal of Operational Research, 2022. 302(2): 633-651. https://doi.org/10.1016/j.ejor.2022.01.011
2021
JP 7. Lindén, D.; Cinelli, M.; Spada, M.; Becker, W.; Gasser, P.; Burgherr, P. A framework based on statistical analysis and stakeholders’ preferences to inform weighting in composite indicators. Environmental Modelling & Software, 2021. 145; 105208, https://doi.org/10.1016/j.envsoft.2021.105208
JP 6. Cinelli, M..; Gonzalez, M.; Ford, R.; McKernan, J.; Corrente, S.; Kadziński, M.; Słowiński, R. Supporting Contaminated Sites Management with Multiple Criteria Decision Analysis: Demonstration of a Regulation-Consistent Approach. Journal of Cleaner Production, 2021. 316: 128347, https://doi.org/10.1016/j.jclepro.2021.128347
JP 5. Piaggio, D.; Castaldo, R.; Cinelli, M.; Cinelli, S.; Maccaro, A.; Pecchia, L. A framework for designing medical devices resilient to low-resource settings. Globalization and Health, 2021. 17: 64, https://doi.org/10.1186/s12992-021-00718-z
JP 4. Kadziński, M.; Martyn, K.; Cinelli, M.; Słowiński, R.; Corrente, S.; Greco, S. Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology. Knowledge-Based Systems, 2021. 218. 106879, https://doi.org/10.1016/j.knosys.2021.106879
2020
JP 3. Cinelli, M.; Spada, M.; Zhang, Y.; Kim, W.; Burgherr, P. MCDA Index Tool. An interactive software to develop indices and rankings. Environment Systems and Decisions. 2020. In press, https://doi.org/10.1007/s10669-020-09784-x
JP 2. Cinelli, M.; Kadziński, M.; Gonzalez, M.; Słowiński, R. How to Support the Application of Multiple Criteria Decision Analysis? Let us Start with a Comprehensive Taxonomy. Omega, 2020. 102261, https://doi.org/10.1016/j.omega. 2020.102261
JP 1. Kadziński, M.; Martyn, K.; Cinelli, M.; Słowiński, R.; Corrente, S.; Greco, S. Preference disaggregation for multiple criteria sorting with partial monotonicity constraints: application to exposure management of nanomaterials. International Journal of Approximate Reasoning, 2020. 117: 60-80, https://doi.org/10.1016/j.ijar.2019.11.007
Conference / Seminar oral presentations
Invited
The MCDA Methods Selection Software (MCDA-MSS): A Radar for Decision Analysts (co-authors Milosz Kadziński, Peter Burgherr, Michael A. Gonzalez, Roman Słowiński), INFORMS annual meeting, Indianapolis (USA), 16-19 October, 2022
Testing a novel Decision Support System to identify the most suitable MCDA method for energy systems analysis (co-authors Milosz Kadziński, Peter Burgherr, Grzegorz Miebs, Roman Słowiński), ESREL 2021, Virtual, 19-23 September, 2021
Supporting complex decision-making in multiple criteria-based projects with MCDA-MSS (co-authors Milosz Kadziński, Peter Burgherr, Roman Słowiński), International Conference on Operations Research 2021, Virtual, 31 August - 3 September, 2021
A New Decision Support System for Recommending Multiple Criteria Decision Analysis (MCDA) Methods (co-authors Milosz Kadziński, Grzegorz Miebs, Michael A. Gonzalez, Roman Słowiński), INFORMS annual meeting, Virtual, 7-13 November, 2020
Self-proposed
How can Multiple Criteria Decision Analysis (MCDA) support the remediation of contaminated sites? Insights from an U.S. EPA case study (co-authors Michael A. Gonzalez, Robert Ford, John McKernan, Salvatore Corrente, Miłosz Kadziński, Roman Słowiński), SETAC Europe, Virtual, 3-6 May, 2021