Available at: https://digitalcommons.calpoly.edu/theses/968
Date of Award
MS in Agribusiness
Jennifer S. James
Women’s food purchasing and eating habits have been studied in detail, but are still not entirely understood. Prior research has sought to segment the female food shopper market, but typically use only demographic characteristics. In this study, fifty females were recruited in San Luis Obispo, CA from March 2012 to May 2012 to keep an electronic food-time diary for one week. By collecting information through surveys distributed using a smartphone application, SurveySwipe, the study investigated the amount of time expended for each meal, as well as the manner in which the meal was prepared or purchased, and the context surrounding the eating situation, for a period of seven days. A segmentation of these female food consumers was then formed in order to demonstrate that by using attitudinal and behavioral data, a unique segmentation scheme may be achieved, different than would have resulted using only demographic information.
For the data analysis, four principal components analyses were conducted followed by subsequent cluster analyses, followed by ANOVA and Chi-Square tests. Study participants were segmented in four distinct sets of clusters, or consumer groups. Of the four sets of clusters formed, one was created using solely demographic variables, whereas the other three used “food time” variables comprised of behavioral and attitudinal information. It may be inferred from the results that the behavior of the participants within each cluster was similar regarding a particular variable being tested, while it differed from the behavior of participants in other clusters (regarding the same variable being tested). Specifically, an abundance of key, significant differences were found with the “food time” variables.
The study supports the use of variables related to “food time” allocation and the context of the eating situation as they relate to the purchase, preparation, and consumption of food, instead of only demographic attributes. The results will be useful for food marketers and product developers seeking to understand how food fits into the lives of female consumers with diverse roles and behaviors, in addition to being valuable for segmenting a select market or targeting a particular customer type.