Semester of Graduation
Summer, 2020
Degree
Master of Science (MS)
Department
The Department of Agricultural Economics & Agribusiness
Document Type
Thesis
Abstract
Around one-third of food produced for human consumption is wasted every year, partially caused by consumer's unwillingness to purchase ugly food. We explore opportunities to favorably support consumer's considerations for ugly food by analyzing survey responses from 1099 U.S. adults. We find that without any marketing strategies applied, a great discount has to be provided to sell ugly food. By using appropriate marketing strategies, consumer's attitudes and willingness to pay for ugly food can be changed positively. However, the effects of ugly food marketing attributes are heterogeneous among consumers with different attitudes towards ugly food. Consumers with negative attitudes towards ugly food tend to be the ones who are prudent and careful decision-makers and less likely to accept ugly foods on normal or even discounted market prices. By mixing ugly food with standard ones, however, we can still manage to improve their acceptance and willingness to pay to food bundles with ugly food included. Consumers with neutral attitudes toward ugly food are more likely to be practical who care about their own real-world benefits, and their willingness to pay for ugly food can be changed when recognized superior attributes are applied, such as selling ugly food in the farmers market. Consumers with positive attitudes to ugly food are more likely to prosocial and altruistic. They are more responsive to the applied marketing attributes and more likely to pay a premium price for ugly food when appropriate marketing strategies are adopted.
Recommended Citation
Li, Ran, "Hopeless Ugly Food? Estimating Heterogeneous Treatment Effects of Marketing Strategies on Consumer Attitude and WTP via Machine Learning Approaches" (2020). LSU Master's Theses. 5195.
https://repository.lsu.edu/gradschool_theses/5195
Committee Chair
Qi Danyi
DOI
10.31390/gradschool_theses.5195
Included in
Agricultural and Resource Economics Commons, Marketing Commons, Social Statistics Commons