A Study on the Relationship Between Decision-making Speed and Kansei Through Data Visualization

Abstract

Data visualization is the processing of data, directed at a person, content, and purpose, to simplify decision-making for the person. In practice, does data visualization affect people's decision-making time? In this study, we formulate questions using tables and graphs for three data groups, with varying amounts of information. Twenty subjects are asked to answer the questions from least to most of information, and the time taken to answer them is measured. Following the experiment, the attributes of the subjects, including gender, age, occupation are obtained via a questionnaire. The experiment reveals that as information increases in the tabular format, the answering slows proportionally. In contrast, in the graph format, the responses do not slow down proportional to the increase in information. The relationship between the subjects’ attributes and the speed of answering is determined and some significant differences are found. Six patterns of relationship between the answering time for the tables and graphs are obtained. Subsequently, the relationship between these attributes and “change of flow from data to action (hereinafter called “the decision-making process”)” are examined in Kansei engineering, and the data visualization is found to be potentially effective at speeding up the decision-making process.