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Predicting satisfaction: Perceived decision quality by decision-makers in Web-based group decision support systems

机译:预测满意度:决策者对基于Web的群体决策支持系统中的决策质量的感知

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摘要

In future, the organizations' likelihood to endure and succeed will depend greatly on the quality of every decision made. It is known that most decisions in organizations are made in group. With the purpose of supporting decision-makers anytime and anywhere, Web-based Group Decision Support Systems (GDSS) have been studied. The amount of Web-based GDSS incorporating automatic negotiation mechanisms such as argumentation has been steadily increasing. Usually, these systems/models are evaluated through mathematical proofs, number of rounds or seconds to propose (reach) a solution. However, those techniques are not very informative in terms of the decision quality. Here, we propose a model that intends to predict the decision-makers' satisfaction (perception of the decision quality), specifically designed to deal with multi-criteria problems. Our model considers aspects such as: meeting's outcomes, decision-maker's intentions, expectations and emotional cost. To validate the proposed model in terms of its ability to predict decision-makers' satisfaction, we developed a prototype of a Web-based GDSS to be used in a case study where the participant had to make a joint decision. The decision process consisted in a set of 5 rounds, where the participant could (re) configure his/her preferences along the process. The satisfaction model ascertained its ability to predict the participants' satisfaction and allowed to understand that (as is stated in the literature) the inclusion of cognitive and emotional variables is essential to evaluate satisfaction more accurately. (C) 2019 Elsevier B.V. All rights reserved.
机译:将来,组织能否持久和成功的可能性将在很大程度上取决于每个决策的质量。众所周知,组织中的大多数决策都是集体制定的。为了随时随地为决策者提供支持,已经研究了基于Web的群体决策支持系统(GDSS)。基于Web的GDSS结合了诸如议论之类的自动协商机制的数量一直在稳步增长。通常,这些系统/模型是通过数学证明,轮次或秒数来评估(提出)的方法。但是,这些技术在决策质量方面不是非常有用。在这里,我们提出了一个模型,该模型旨在预测决策者的满意度(对决策质量的感知),专门用于处理多准则问题。我们的模型考虑了以下方面:会议的成果,决策者的意图,期望和情感成本。为了验证该模型在预测决策者满意度方面的能力,我们开发了基于Web的GDSS原型,该模型可用于案例研究中,参与者必须做出共同决策。决策过程包括5个回合,参与者可以在此过程中(重新)配置自己的偏好。满意度模型确定了其预测参与者满意度的能力,并允许理解(如文献所述)认知和情感变量的包含对于更准确地评估满意度至关重要。 (C)2019 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Neurocomputing》 |2019年第21期|399-417|共19页
  • 作者单位

    Polytech Porto, Inst Engn, GECAD, Res Grp Intelligent Engn & Comp Adv Innovat & Dev, P-4200072 Porto, Portugal|Univ Minho, ALGORITMI Ctr, P-4800058 Guimaraes, Portugal;

    Univ Porto, Fac Psychol & Educ Sci, P-4200135 Porto, Portugal;

    Polytech Porto, Inst Engn, GECAD, Res Grp Intelligent Engn & Comp Adv Innovat & Dev, P-4200072 Porto, Portugal;

    Polytech Porto, CIICESI, Sch Technol & Management, Felgueiras, Portugal;

    Polytech Porto, Inst Engn, GECAD, Res Grp Intelligent Engn & Comp Adv Innovat & Dev, P-4200072 Porto, Portugal;

    Univ Minho, ALGORITMI Ctr, P-4800058 Guimaraes, Portugal;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Group decision support systems; Decision satisfaction; Decision quality; Outcomes; Affective computing;

    机译:团队决策支持系统;决策满意度;决策质量;结果;情感计算;

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