Aided Decision Processes in Dynamic Events: Measuring Decision Support Systems' Influence and Human Responsibility

Decision support systems (DSSs) increasingly assist human users who should consider their output and combine it with independently available information when making a decision. Some decision-making events are dynamic, requiring a series of decisions in interdependent stages. In them, users may not use DSS advice optimally, possibly compromising task performance and preventing the DSS from fulfilling its purpose. We report an experiment in which participants made decisions in dynamic events, observing the output from a DSS. They largely followed normative decision-making rules, but decisions were based on the DSS's perceived, and not necessarily the actual, accuracy. Participants mostly made up their minds in the first stage, and using the DSS typically lengthened the time to reach a decision. These findings should be considered when designing DSS and related regulations and operational processes so people can utilize the DSS's full potential.

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Publication Details

Journal
IEEE Transactions on Human-Machine Systems
Published
2025-04-08
DOI
https://doi.org/10.1109/thms.2025.3553015
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00

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article

Aided Decision Processes in Dynamic Events: Measuring Decision Support Systems' Influence and Human Responsibility

Yossef Saad, Joachim Meyer
IEEE Transactions on Human-Machine Systems
Big Data and Business Intelligence
article

Aided Decision Processes in Dynamic Events: Measuring Decision Support Systems' Influence and Human Responsibility

Yossef Saad, Joachim Meyer
article en

Abstract

Decision support systems (DSSs) increasingly assist human users who should consider their output and combine it with independently available information when making a decision. Some decision-making events are dynamic, requiring a series of decisions in interdependent stages. In them, users may not use DSS advice optimally, possibly compromising task performance and preventing the DSS from fulfilling its purpose. We report an experiment in which participants made decisions in dynamic events, observing the output from a DSS. They largely followed normative decision-making rules, but decisions were based on the DSS's perceived, and not necessarily the actual, accuracy. Participants mostly made up their minds in the first stage, and using the DSS typically lengthened the time to reach a decision. These findings should be considered when designing DSS and related regulations and operational processes so people can utilize the DSS's full potential.

IEEE Transactions on Human-Machine SystemsVol. 55(3)
Tel Aviv University (IL)
Israel Science Foundation
Peace, Justice and strong institutions
Openalex Percentile: Top 90%
Big Data and Business Intelligence
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