| Summary: | In decision theory the process of selecting the best option is called preferential
choice. Many personal, business, and professional preferential choice decisions
are made every day. In these situations, a decision maker must select the optimal option among multiple alternatives. In order to do this, she must be able
to analyze a model of her preferences with respect to the objectives that are important to her. Prescriptive decision theory suggests several ways to effectively
develop a decision model. However, these methods often end up too tedious
and complicated to apply to complex decisions that involve many objectives
and alternatives.
In order to help people make better decisions, an easier, more intuitive way
to develop interactive models for analysis of decision contexts is needed. The
application of interactive visualization techniques to this problem is an opportune solution. A visualization tool to help in preferential choice must take into
account important aspects from both fields of Information Visualization and
Decision Theory. There exists some proposals that claim to aid preferential
choice, but some key tasks and steps from at least one of these areas are often
overlooked. An added missing element in these proposals is an adequate user
evaluation. In fact, the concept of a good evaluation in the field of information
visualization is a topic of debate, since the goals of such systems stretch beyond
what can be concluded from traditional usability testing. In our research we
investigate ways to overcome some of the challenges faced in the design and
evaluation of visualization systems for preferential choice.
In previous work, Carenini and Lloyd proposed ValueCharts, a set of visualizations and interactive techniques to support the inspection of linear models
of preferences. We now identify the need to consider the decision process in its
entirety, and to redesign ValueCharts in order to support all phases of preferential choice. We present our task-based approach to the redesign of ValueCharts
grounded in recent findings from both Decision Analysis and Information Visualization. We propose a set of domain-independent tasks for the design and
evaluation of interactive visualizations for preferential choice. We then use the
resulting framework as a basis for an analytical evaluation of our tool and alternative approaches. Finally, we use an application of the task model in conjunction with a new blend of evaluation methods to assess the utility of ValueCharts.
|
|---|
