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.
Highlights
Decision-making problems are commonly based on multiple criteria and require to account for trade-offs between them before reaching a comprehensive evaluation of the alternatives under consideration (Roy 2010)
We propose a comparison of multiple criteria decision analysis (MCDA) software for scoring and ranking with a specific focus on output variability, which has not been conducted so far, according to the authors’ knowledge
The proposed tool can be used by decision analyst as an exploratory strategy during the MCDA process, aiding high-level DMs and stakeholders to explore the implications that different strategies to develop the Composite Indicator (CI) can have on the results
Summary
Decision-making problems are commonly based on multiple criteria and require to account for trade-offs between them before reaching a comprehensive evaluation of the alternatives under consideration (Roy 2010). This comprehensive evaluation can be reached using methods that belong to the multiple criteria decision analysis (MCDA) domain Environment Systems and Decisions (2021) 41:82–109 key steps that can have crucial implications on the results These are the normalization and the aggregation. It is notable to point out that CI development can be approached in a tiered manner In this case, simpler models are developed first, constrained by limited resources and capital expenditures. It has been shown that a multitude of normalization and aggregation methods exists (see OECD (2008), Jahan and Edwards (2015) and Rowley et al (2012) for an overview) and the combination of a certain normalization and aggregation leads to a certain index
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
