Group decision support systems for current times: Overcoming the challenges of dispersed group decision-making

Carneiro, João; Alves, Patrícia; Marreiros, Goreti; Nováis, Paulo

doi:10.1016/j.neucom.2020.04.100

Cited by 21 publications

(11 citation statements)

References 84 publications

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“…This will also mean that the results will not be independently reproducible by different teams in the same organization. The potential biases identified here could be moderated through the use of technologies for decision-making in a collaborative context, including Group Decision Support Systems (GDSS) [56] that, for example, support the prioritization process through anonymous voting by collaborators, and facilitate negotiation to reach consensual agreements [57].…”

Section: Research Limitationsmentioning

confidence: 99%

OurRank: A Software Requirements Prioritization Method Based on Qualitative Assessment and Cost-Benefit Prediction

Rojas¹,

Olivares-Rodríguez

Álvarez

et al. 2022

IEEE Access

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Requirements prioritization is an activity aimed at determining the essential requirements to include in a software release. Although there are several prioritization methods to systematize this task, there are still unresolved challenges. Existing methods do not guarantee that requirements prioritization meets stakeholder expectations and goals. This is because most prioritization methods operate by considering only quantitative information, making it difficult to formally capture stakeholder interests and perspectives that can rather be made explicit in qualitative terms. Likewise, methods including qualitative information only consider elements associated with benefit estimation, that is, positive aspects of the project, but neglect costs or negative aspects. As a result, the prioritization process is driven by a partial view of constraints. Such methods also fail at capturing and combining expert knowledge that decision-makers can bring into the decision-making process. In this research, we propose a novel method for software requirements prioritization, which facilitates incorporating experts' qualitative assessment at the outset of the prioritization process and considers both benefit and cost constraints. Details of the method are presented, together with a case study describing a real application scenario. Recommendations and guidelines regarding the application of the method are proposed based on the results of the case study.INDEX TERMS Cost-benefit prediction, qualitative prioritization criteria, prioritization method, requirements prioritization.

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Section: Research Limitationsmentioning

confidence: 99%

OurRank: A Software Requirements Prioritization Method Based on Qualitative Assessment and Cost-Benefit Prediction

Rojas¹,

Olivares-Rodríguez

Álvarez

et al. 2022

IEEE Access

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“…As summarized in Table 1, GDM problems with large-scale alternatives are seldom considered recently. This is mainly because when there are lots of alternatives, the collection of experts' preference information is not an easy issue [6,7]. Especially considering that high-level experts are usually engaged in work, they do not have enough time and vigour to complete the evaluation task.…”

Section: Motivationmentioning

confidence: 99%

A DES-based group decision model for group decision making with large-scale alternatives

Liu

Chen

2021

Appl Intell

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To solve group decision making problems with large-scale alternatives, this paper proposes a dynamic ensemble selection (DES) based group decision model by using historical decision data. The historical decision data of a group of experts are collected from the same multi-criteria decision framework and are mixed to train a set of base classifiers (BCs) to learn group preferences. For each new alternative, the predictions derived from BCs are used to determine its similar historical alternatives from historical data, and the BC with the highest accuracy in predicting the similar historical alternatives is identified as the best individual BC for the new alternative. By iteratively comparing the accuracy of an ensemble of randomly selected BCs and the best individual BC in predicting the similar historical alternatives of the new alternative, a novel DES method is developed to select a competent subset of BCs for the new alternative. The developed DES method effectively avoids the error-independence assumption to a certain extent. Based on the similar historical alternatives determined by the ensemble of selected BCs, a group decision optimization model is developed to learn criterion weights from their assessments on criteria and ensemble predictions derived from the selected BCs. With the learned criterion weights, the understandable group decision result is generated for the new alternative. Case study validates the superiority of the proposed model in diagnosing thyroid nodules using group capabilities. Empirical comparisons on thirty real datasets examine the competence of the proposed DES method against five representative DES methods.

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“…Moreover, group decision making let the participants boost their ability to learn and stimulate their cognitive level (Carneiro et al, 2020). Therefore, the adoption of three multiple perspectives in this research (i.e., of students, FEP committees, and schools) enhances decision-making effectiveness.…”

Section: Introductionmentioning

confidence: 97%

Optimizing Placement of Field Experience Program: An Integration of MOORA and Rule-Based Decision Making

Okfalisa¹,

Hafsari²,

Nawanir³

et al. 2021

JST

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The lack of optimality in the Field Experience Program (FEP) placement has affected universities’ educational services to the stakeholders. Bringing together the stakeholders’ needs, university capacities, and participants’ willingness to quality and quantity is not easy. This study tries to optimize the placement of FEP by considering the interests of multiple perspectives through the application of Multi-Objective Optimization on the Basic of Ratio Analysis (MOORA) and Rule-Based methods in the form of a decision-making model. MOORA ranked the students based on the FEP committee’s perspective and other criteria, such as micro-teaching grades, final GPAs, study programs, number of credits, and student addresses. Meanwhile, the school perspective was ordered based on its accreditations, levels, types, facilities, and performances. To achieve the optimal recommendation of FEP placement, the integration of MOORA and Rule-based intertwined the requirement of such perspectives. A prototype of the system recommendation is then acquired to simplify the decision-making model. As adjudications, a survey from twenty stakeholders evidenced around 86.92% of system user acceptances. The confusion matrix testing defines the accuracy of this method reaches 78.33%. This paper reveals that the recommendation model has been successfully increasing the effectiveness of decision making in FEP placement under the needs and expectations of the entire stakeholders.

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Group decision support systems for current times: Overcoming the challenges of dispersed group decision-making

Cited by 21 publications

References 84 publications

OurRank: A Software Requirements Prioritization Method Based on Qualitative Assessment and Cost-Benefit Prediction

OurRank: A Software Requirements Prioritization Method Based on Qualitative Assessment and Cost-Benefit Prediction

A DES-based group decision model for group decision making with large-scale alternatives

Optimizing Placement of Field Experience Program: An Integration of MOORA and Rule-Based Decision Making

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