The purpose of this study was to identify the factors that influence the use and understanding of unit pricing. Furthermore, a comparison between a city with a mandated unit pricing program (Seattle, Washington) and a city with a voluntary unit pricing program (Portland, Oregon) was made. The intent was to see if there was more use or understanding of unit pricing in a mandated city. The relationship between the preference for a certain brand and use of unit pricing was also investigated. Weighted indexes were constructed for use in the computation of individual scores. This researcher cross-classified the variables of sex, income level, level of education, age, and store location with the variables of use scores and understanding scores on a measure of unit pricing. One hundred and twenty consumers (60 in Seattle and 60 in Portland) were interviewed in twelve selected stores. Stores were selected to represent various income tracts of each city. Data collected in this manner served as a base for this research. The data were analyzed with the use of analysis of variance (ANOVA), the Chi-Square Test of Independence, and the Pearson Product Moment test for correlation (r). The sample consisted of 120 consumers: 23 males (19%) and 97 females (81%) were interviewed. Thirty-one percent of the sample were 18-29 year olds. The majority of respondents were Caucasion (89%) and of middle income. For analysis purposes the researcher combined seven income groups into three categories. The categories and their proportions of the same were: 1) high income group (above $25,000 per year) 23 percent of the sample; 2) middle income group ($8,000 to $25,000 per year) 51 percent of the sample; and 3) low income group (below $8,000 per year) 18 percent of the sample. The majority of respondents had at least some college and were well educated. Hypotheses 1 and 2, relating to use and understanding of unit pricing between two cities, could not be rejected at the .05 level of significance. The tests did not reveal a difference between cities, nor a difference by stores within cities. For understanding of unit pricing, the data revealed a difference by stores within cities, but not a difference between cities. Hypotheses 3 through 12 related to use and understanding of unit pricing between two cities, for the combined samples. Scores for use and understanding were cross-tabulated with each of five variables: age, level of education, sex, income level, and store location. In both cases, scores were seen to be dependent on all variables except sex of the respondent. High use of unit pricing was displayed by college graduates who were 18-29 years old, and who were interviewed in high income stores. High-use consumers had incomes ranging from $8,000 to $25,000 annually. Lowest users of unit pricing were low income consumers with grade school education, 60 years old or older and interviewed in low income stores. High understanding of unit pricing was displayed by consumers 18-29 years of age and with some college education. They were interviewed in middle income stores and had incomes of $8,000 to $25,000 per year (middle income). Low understanding consumers were again aged 60 or older, were high school graduates with low annual incomes of $8,000 or less. They were interviewed in low income stores. Hypothesis 13 related to brand preference scores and the degree of correlation with use scores. A moderate negative correlation was identified ( -.42) using the Pearson "r" test. As brand-preference increased, use of unit pricing decreased somewhat. A similar correlation was true of understanding correlated with brand preference, a negative correlation of -.28. Use scores and understanding scores showed a positive correlation of +.58. Hypothesis 14 tested consumer awareness of his/her use of unit pricing. Seattle consumers perceived greater use of unit pricing and reported more frequent use than did Portland consumers.