<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The Negotiation Support Systems often implement multiple criteria decision aiding (MCDA) techniques for building a negotiation scoring system. Those formal models should meet the needs, motivations, expectations, and cognitive abilities of users. In this paper, we try to explore the effects of decision maker’s subjective perception of ease of use, time requirements, interface, preference representation, and efficiency of a particular MCDA method on the choice regarding the future use of this method. The multinomial logistic regression model is built and analysed. The analysis is based on data from online decision making experiments, where three MCDA methods were implemented, i.e. AHP, SMART, and TOPSIS. The study provides several interesting findings, concerning the behavioural aspects of multiple criteria decision aiding in software support systems. Most of the users recommended TOPSIS as the best one for supporting decisions in the future. This is a fast technique, for which we used an attractive graphical interface, suggesting that these factors play a crucial role in the users’ choices. However, the causative regression model showed that the user’s positive experience in using a particular method, i.e. its effectiveness in solving an exemplary numerical case, has the highest impact on the method’s choice for future use. The second most important factor is the adequacy in representing the user’s preferences by this method. We show, however, that the strengths of effects and their significance may vary across the methods. Understanding the decision maker’s evaluations of the MCDA techniques may help build a cognitive negotiation support system that satisfies the user’s expectations.</p>
</abstract>

The Negotiation Support Systems often implement multiple criteria decision aiding (MCDA) techniques for building a negotiation scoring system. Those formal models should meet the needs, motivations, expectations, and cognitive abilities of users. In this paper, we try to explore the effects of decision maker’s subjective perception of ease of use, time requirements, interface, preference representation, and efficiency of a particular MCDA method on the choice regarding the future use of this method. The multinomial logistic regression model is built and analysed. The analysis is based on data from online decision making experiments, where three MCDA methods were implemented, i.e. AHP, SMART, and TOPSIS. The study provides several interesting findings, concerning the behavioural aspects of multiple criteria decision aiding in software support systems. Most of the users recommended TOPSIS as the best one for supporting decisions in the future. This is a fast technique, for which we used an attractive graphical interface, suggesting that these factors play a crucial role in the users’ choices. However, the causative regression model showed that the user’s positive experience in using a particular method, i.e. its effectiveness in solving an exemplary numerical case, has the highest impact on the method’s choice for future use. The second most important factor is the adequacy in representing the user’s preferences by this method. We show, however, that the strengths of effects and their significance may vary across the methods. Understanding the decision maker’s evaluations of the MCDA techniques may help build a cognitive negotiation support system that satisfies the user’s expectations.

Towards cognitive decision support: A model of behavioural assessment of multi-criteria methods

Control and Cybernetics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The Negotiation Support Systems often implement multiple criteria decision aiding (MCDA) techniques for building a negotiation scoring system. Those formal...

Towards cognitive decision support: A model of behavioural assessment of multi-criteria methods

Online veröffentlicht: 23. Juni 2022

Seitenbereich: 145 - 168

Eingereicht: 01. Dez. 2020

Akzeptiert: 01. März 2021

DOI: https://doi.org/10.2478/candc-2021-0009

Schlüsselwörter
decision support, behavioural decision analysis, preference analysis, AHP, SMART, TOPSIS

© 2021 Ewa Roszkowska et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Towards cognitive decision support: A model of behavioural assessment of multi-criteria methods

Online veröffentlicht: 23. Juni 2022

Seitenbereich: 145 - 168

Eingereicht: 01. Dez. 2020

Akzeptiert: 01. März 2021

DOI: https://doi.org/10.2478/candc-2021-0009

Schlüsselwörterdecision support, behavioural decision analysis, preference analysis, AHP, SMART, TOPSIS

© 2021 Ewa Roszkowska et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
decision support, behavioural decision analysis, preference analysis, AHP, SMART, TOPSIS