Interactive Visualization for Group Decision Analysis

Abstract

Identifying the best solutions to large infrastructure decisions is a context-dependent multi-dimensional multi-stakeholder challenge in which competing objectives must be identified and trade-offs made. Our aim is to identify and explore features in an interactive visualization tool to help make group decision analysis more participatory, transparent, and comprehensible. We extended the interactive visualization tool ValueCharts to create Group ValueCharts. The new tool was introduced in two real-world scenarios in which stakeholders were in the midst of wrestling with decisions about infrastructure investment. We modeled the alternatives under consideration, for both scenarios, using prescribed criteria identified by domain experts. Participants in both groups were given instructions on how to use the tool to represent their preferences. Preferences for all participants were then displayed and discussed. The discussions were audio-recorded and the participants were surveyed to evaluate usability. The results indicate that participants felt the tool improved group interaction and information exchange and made the discussion more participatory. They expressed that visualizing individual preferences improved the ability to analyze decision outcomes based on everyone’s preferences. Additionally, the participants strongly concurred that the tool revealed disagreements and agreements and helped identify sticking points. These results suggest that a group decision tool that allows group members to input their individual preferences and then collectively probe into any differences makes the process of decision-making more participatory, transparent, and comprehensible and increases the quality and quantity of information exchange.

Help or Hinder? Evaluating the Impact of Fairness Metrics and Algorithms in Visualizations for Consensus Ranking

“…Visualization systems have been designed to aid decision-makers in inspecting multiple stakeholders' preferences to reach a consensus decision [2,11,17,20,22,25,33,40,42,47,54,55]. A subset of these tools consider the setting, like ours, in which stakeholder preferences are encoded as rankings [11,23,33].…”

The effects of visualization on judgment and decision-making: a systematic literature review

“…On the other hand, reasoning and judgment refer to the evaluation of a set of alternatives (Reani et al 2019), without actions necessarily being attached as for decision-making. Such efforts are cognitively demanding and complex when compared to more elementary tasks, such as a choice between options (Tuttle and Kershaw 1998), and include the rigorous evaluation of alternatives across a range of attributes, which is characteristic for strategic decisions (Bajracharya et al 2014). For this reason, I include studies that examine the influence of visualizations on some form of decision or judgment outcome.…”

Objective Evaluation of Subjective Metrics for Interactive Decision-Making Tasks by Non-experts

“…(2) There is a lack of clear references for identifying an appropriate baseline for comparative assessment. As a first step towards a more rigorous approach to the evaluation of tools for multiattribute choice tasks, Dimara et al [4] propose a combination of objective and subjective metrics for comparing parallel coordinates, scatterplot, and tabular visualizations, three commonly used elementary visualization techniques: accuracy and time-on-task as objective metrics; technique preference, satisfaction, confidence, easiness, and attachment as subjective metrics. Dimara et al report that, for decision-making, the three techniques are comparable across the metrics with "a slight speed advantage for the tabular visualization".…”

“…In this article, we are concerned with the problem of objectively evaluating and comparing interaction techniques designed for tasks that are inherently subjective. There is a growing research interest in addressing this issue in the field of interactive visualization [2,4,5]. In this area, evaluation generally consists of assessing the usability of the technique as in [31], or evaluating the capacity of the technique to support data exploration for analytical tasks such as retrieving a particular value [10].…”