The Multi-Actor Multi-Criteria Analysis has been a successful methodology to integrate multiple stakeholders in the decision-making process. Because MAMCA evaluates different alternatives based on the objectives of the stakeholders, decision-makers can increase the support for the alternative they will choose. Still, the application of the methodology can be complex to popularize this approach. The MAMCA software was therefore published in order to facilitate the use of the methodology. The development of that tool offers also new opportunities. Currently, the goal is to extend the MAMCA software as a mass participation tool, hence maximizing participation involvement.

In order to facilitate the application of the methodology, the new MAMCA software was published. This contribution highlights how the MAMCA methodology was integrated into the software and how the data is being visualized. We focus on enhancing the concept of “Participation” in the development. A new data structure has been developed and an easier user interface makes the tool more accessible. An easy-understand evaluation method is integrated into the software. The interaction experience between participants is improved. Overall, the new MAMCA software is aimed to have a better performance in workshop settings.
Original languageEnglish
Title of host publicationDecision Support Systems X: Cognitive Decision Support Systems and Technologies
EditorsJosé María Moreno-Jiménez, Isabelle Linden, Fatima Dargam, Uchitha Jayawickrama
PublisherSpringer
Pages43-56
Number of pages14
ISBN (Print)9783030462239
DOIs
Publication statusPublished - 18 May 2020
EventEWG-DSS 6th International Conference on Decision Support System Technology -
Duration: 27 May 202029 May 2020

Publication series

NameLecture Notes in Business Information Processing
Volume384 LNBIP
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356

Conference

ConferenceEWG-DSS 6th International Conference on Decision Support System Technology
Abbreviated titleICDSST 2020
Period27/05/2029/05/20

    Research areas

  • MAMCA, MCDM, Data visualization, Human-computer interaction

ID: 52104298