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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:由基于Web的基于网络决策支持系统中的决策者感知决策质量

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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:在将来,组织的可能性和成功的可能性将大大取决于所做的每决策的质量。众所周知,组织中的大多数决策都是组合的。目的是随时支持决策者,已经研究了基于网络的基于网络决策支持系统(GDSS)。包含自动谈判机制的基于Web的GDS量,例如论证已经稳步增加。通常,这些系统/型号通过数学校样,轮次或秒数来评估(达到)解决方案。然而,在决策质量方面,这些技术并不是很有信息。在这里,我们提出了一种打算预测决策者的满意度(决策质量的感知)的模型,专门用于处理多标准问题。我们的模式考虑了:会议结果,决策者的意图,期望和情感成本等方面。为了在预测决策者的满意度方面验证拟议的模型,我们开发了一种基于Web的GDS的原型,以便在参与者进行联合决定的情况下使用。决策过程包括一组5轮,其中参与者可以(重新)沿着过程配置他/她的偏好。满意模型确定了预测参与者的满意度并允许理解(如文学中所述)的纳入认知和情绪变量对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:集团决策支持系统;决策满足;决策质量;结果;情感计算;

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