交互式数据与信息可视化:解析其特征及其对决策的影响

IF 2.4 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
Arif Perdana, D. A. Robb, Fiona H. Rohde
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引用次数: 2

摘要

背景:交互式数据和信息可视化(IDIV)通过向用户提供多种可视化表示、活动控制和分析来增强信息表示。与标准表示相比,用户可以更好地控制IDIV表示,因此,IDIV成为支持数据分析(DA)以及增强人类智力的更流行和相关的方法。因此,IDIV能够以更适合用户决策的格式提供信息。方法:综合以往文献,分析IDIV的特征及其对决策的影响。本研究采用叙事回顾的方法。我们对IDIV的概念化和提出的决策模型来源于信息系统(IS)和心理学学科的大量文献。结果:我们提出了一个以IS为中心的IDIV增强决策模型,该模型包含四个决策基础(即预测因子、调节因子、中介因子和结果)。与标准信息表示相比,IDIV具有丰富的特征,因此,制定模型对于理解IDIV如何影响决策过程、感知评估、决策结果和质量至关重要。结论:该决策模型可以为进一步的IDIV研究提供有意义的参考框架,并为IS理论化提供更大的特异性。总体而言,我们对IDIV的系统描述和解释做出了贡献,并讨论了未来IDIV在IS领域研究的潜在研究议程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive Data and Information Visualization: Unpacking its Characteristics and Influencing Aspects on Decision-making
Background : Interactive data and information visualization (IDIV) enhances information presentations by providing users with multiple visual representations, active controls, and analytics. Users have greater control over IDIV presentations than standard presentations and as such IDIV becomes a more popular and relevant means of supporting data analytics (DA), as well as augmenting human intellect. Thus, IDIV enables provision of information in a format better suited to users’ decision-making. Method : Synthesizing past literature, we unpack IDIV characteristics and their influence on decision-making. This study adopts a narrative review method. Our conceptualization of IDIV and the proposed decision-making model are derived from a substantial body of literature from within the information systems (IS) and psychology disciplines.  Results : We propose an IS centered model of IDIV enhanced decision-making incorporating four bases of decision-making (i.e., predictors, moderators, mediators, and outcomes). IDIV is specifically characterized by rich features compared with standard information presentations, therefore, formulating the model is critical to understanding how IDIV affects decision processes, perceptual evaluations, and decision outcomes and quality. Conclusions : This decision-making model could provide a meaningful frame of reference for further IDIV research and greater specificity in IS theorizing. Overall, we contribute to the systematic description and explanation of IDIV and discuss a potential research agenda for future IDIV research into IS.
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CiteScore
4.10
自引率
33.30%
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