MCDA Index Tool: an interactive software to develop indices and rankings

Marco Cinelli (), Matteo Spada, Wansub Kim, Yiwen Zhang and Peter Burgherr
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Marco Cinelli: Singapore-ETH Centre (SEC), Swiss Federal Institute of Technology (ETH) Zürich
Matteo Spada: Paul Scherrer Institut (PSI), Laboratory for Energy Systems Analysis
Wansub Kim: Singapore-ETH Centre (SEC), Swiss Federal Institute of Technology (ETH) Zürich
Yiwen Zhang: Singapore-ETH Centre (SEC), Swiss Federal Institute of Technology (ETH) Zürich
Peter Burgherr: Paul Scherrer Institut (PSI), Laboratory for Energy Systems Analysis

Environment Systems and Decisions, 2021, vol. 41, issue 1, 82-109

Abstract: Abstract A web-based software, called MCDA Index Tool ( https://www.mcdaindex.net/ ), is presented in this paper. It allows developing indices and ranking alternatives, based on multiple combinations of normalization methods and aggregation functions. Given the steadily increasing importance of accounting for multiple preferences of the decision-makers and assessing the robustness of the decision recommendations, this tool is a timely instrument that can be used primarily by non-multiple criteria decision analysis (MCDA) experts to dynamically shape and evaluate their indices. The MCDA Index Tool allows the user to (i) input a dataset directly from spreadsheets with alternatives and indicators performance, (ii) build multiple indices by choosing several normalization methods and aggregation functions, and (iii) visualize and compare the indices’ scores and rankings to assess the robustness of the results. A novel perspective on uncertainty and sensitivity analysis of preference models offers operational solutions to assess the influence of different strategies to develop indices and visualize their results. A case study for the assessment of the energy security and sustainability implications of different global energy scenarios is used to illustrate the application of the MCDA Index Tool. Analysts have now access to an index development tool that supports constructive and dynamic evaluation of the stability of rankings driven by a single score while including multiple decision-makers’ and stakeholders’ preferences.

Keywords: Index development; Composite indicator; Software; MCDA; Normalization; Aggregation (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s10669-020-09784-x

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