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Improvements in the FITradeoff Decision Support System for Ranking Order Problematic Based in a Behavioral Study with NeuroIS Tools

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Information Systems and Neuroscience (NeuroIS 2020)

Abstract

This research is performed using NeuroIS tools to improve the information systems (the Decision Support System) constructed for the FITradeoff method. In this study a neuroscience experiment is constructed with the support of an Eye-Tracking in order to investigate the decision-maker (DMs) behavior when they evaluate Multi-Criteria Decision-Making/Aiding (MCDM/A) problems. Therefore, based on the experiment results, a Recommendation Rule is proposed to support the analyst in the advising process performed with the DM and the importance of the holistic evaluation phase for the FITradeoff DSS is highlighted, suggesting that this phase should be included in the DSS constructed for ranking order problematic.

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Acknowledgements

This project was supported by the National Council for Scientific and Technological Development (CNPq) and Coordination for the Improvement of Higher Education Personnel (CAPES).

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Correspondence to Lucia Reis Peixoto Roselli .

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Appendices A

Appendices A

 

4 Criteria - different weights

5 Criteria - different weights

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Roselli, L.R.P., de Almeida, A.T. (2020). Improvements in the FITradeoff Decision Support System for Ranking Order Problematic Based in a Behavioral Study with NeuroIS Tools. In: Davis, F.D., Riedl, R., vom Brocke, J., Léger, PM., Randolph, A.B., Fischer, T. (eds) Information Systems and Neuroscience. NeuroIS 2020. Lecture Notes in Information Systems and Organisation, vol 43. Springer, Cham. https://doi.org/10.1007/978-3-030-60073-0_14

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