Software
Over the last couple of years, specifically during my time with Singapore-ETH Centre (SEC) and as a Marie Skłodowska-Curie Fellow, I led and maintain projects to develop software that can be used to support Multiple Criteria Decision Analysis (MCDA).
The MCDA-MSS (https://mcda.cs.put.poznan.pl) is a web software that provides a simple answer to the question: What is the most relevant MCDA methods for my problem?
Usage: how much the software is actively used by the users. It counts how many different questions were used to proceed in the identification of the suitable MCDA method(s).
Views: an estimation of how many users we have monthly.
The MCDA Index Tool (http://www.mcdaindex.net/) is a web software that provides a practical and straightforward guide for the construction of indices and rankings. In particular, it contains a set of steps that can help developing indices by learning and assessing the quality of the outputs. Key features include robustness assessment of the outcomes (i.e., 31 different combinations to develop the index) and a wide range of results visualization.
Access the MCDA Index Tool here.
Download the MCDA Index Tool manual here.
Download the MCDA Index Tool journal paper here.
Technical team: Yiwen Zhang, Wansub Kim
Affiliated Ph.D. project: Patrick Gasser
Supervisors: Dr. Peter Burgherr; Dr. Matteo Spada
A Matlab tool (https://bitbucket.org/ensadpsi/ciao-tool/src/master/) to assess implicit weights in Composite Indicators (CI) and balance their influence. CIAO Tool supports advanced statistical analysis of CI, including:
Perform a detailed examination of the linear and nonlinear relationships among (i) the set of indicators and (ii) between the indicators and the CI;
Assess how the indicators are “balanced” within the CI, i.e. to what extent the influence of each indicator matches its assigned weight;
Tune the weights of the indicators so that the influence of each one matches pre-defined importance values.
Download CIAO Tool here.
Download the CIAO Tool manual here.
CIAO Tool was the main project of David Lindén from KTH in Stockholm, who did his master thesis and internship with us at Singapore-ETH Centre (Singapore) and Paul Scherrer Institut (Switzerland).
Supervisors: Dr. Peter Burgherr; Dr. Matteo Spada
In collaboration with: Competence Centre on Composite Indicators and Scoreboards (COIN), Joint Research Centre, European Commission (Dr. William Becker)
Acknowledgments for MCDA Index Tool and CIAO Tool
The research was conducted at the Future Resilient Systems (FRS) at the Singapore-ETH Centre (SEC), which was established collaboratively between ETH Zürich and Singapore’s National Research Foundation (FI 370074011) under its Campus for Research Excellence And Technological Enterprise (CREATE) program. These projects have also been supported by the Technology Assessment Group of the Laboratory for Energy Systems Analysis at the Paul Scherrer Institute (PSI) in Switzerland. Marco Cinelli acknowledges that these projects have received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 743553.
Acknowledgments for MCDA-MSS
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 743553, from the Swiss National Science Foundation under grant agreement No IZSEZ0_193662, from the Polish Ministry of Science and Higher Education under the Diamond Grant project (Grant No. DI2018 004348), and from the Polish National Science Center under the SONATA BIS project (Grant No. DEC-2019/34/E/HS4/00045).