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

Lucia Reis Peixoto Roselli () and Adiel Teixeira Almeida ()
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Lucia Reis Peixoto Roselli: Universidade Federal de Pernambuco
Adiel Teixeira Almeida: Universidade Federal de Pernambuco

A chapter in Information Systems and Neuroscience, 2020, pp 121-132 from Springer

Abstract: 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.

Keywords: NeuroIS; Decision neuroscience; Holistic evaluation; Decision support system; Recommendation rule; FITradeoff method; Multi-Criteria Decision-Making/Aiding (MCDM/A) (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/978-3-030-60073-0_14

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