Sorting-Based Menu Categories

Several researchers have conducted sorting experiments or pairwise comparisons with a database of menu items in order to form coherent menu categories. However, these experiments have all contained one or more of the following potential weaknesses: (1) they used only one particular database; (2) they used too few sorting subjects; (3) they uncritically used only one scaling technique to form the clusters; or (4) they did not conduct an experimental comparison of the categories formed. In the present research, sorting experiments were conducted with 48 subjects and four 48-item databases: clothes, furniture, occupations, and sports. Latent partition analysis and hierarchical clustering (Ward's method and group average linkage) were used to form menu categories. These were placed into a “pull-down” menu system in two conditions; (1) titles chosen by each individual subject; and (2) titles chosen by the investigator. Two other conditions were added: (3) categories and titles formed by software design experts; and (4) categories and titles formed by each subject for his or her own work. Two within-subjects menu experiments were performed. The sorting-based categories with investigator titles were superior to the expert categories in selection times, selection errors, ”goodness of fit” ratings, and memory recall errors. A detailed analysis showed that the expert categories contained more “miscategorization” errors and vague category titles than the sorting-based categories, while both conditions contained overlapping categories.