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Characterizing consumer emotional response to milk packaging guides packaging material selection

Clark, Elizabeth A., Duncan, Susan E., Hamilton, Leah M., Bell, Martha Ann, Lahne, Jacob, Gallagher, Daniel L., O'Keefe, Sean F.
Food quality and preference 2021 v.87 pp. 103984
automation, computer software, consumer acceptance, dairy industry, decision making, emotions, food choices, glass, milk, motivation, packaging, packaging materials, paperboard, pigmentation, polyethylene, questionnaires, time series analysis
The decision-making process involved in food selection and consumption behaviors is confounded by mental integration of information, experiences, and emotions associated with the product (stimulus). The complex and fleeting but temporal nature of product-generated (PG) or product-associated (PA) emotions makes affectual experiences difficult to measure and interpret. This project aims to characterize the relationship between PA, and PG, emotions and consumer acceptability and purchase intent towards milk packaging. Participants (age: 18–65 years; n = 50; milk consumers) performed Single Target Implicit Association Tests (ST-IAT) to capture PA emotions for various types of milk packaging (n = 6; translucent high density polyethylene (HDPE), white HDPE, yellow HDPE, white polyethyleneteraphthalate (PET), paperboard, glass). Participants then interacted with individual packages for 30 s and their facial expressions were analyzed using automated facial expression analysis (AFEA) for implicit PG emotions. Explicit PG emotional response was assessed using a Check-All-That-Apply (CATA) questionnaire (43 emotional terms). ST-IAT did not identify significant PA emotions for packaged milk, but CATA data produced a reasonable description of approach/withdrawal motivation related to packaging pigmentation. Time series analysis of AFEA data provided evidence of significant differences in emotion intensity. The lack of difference between certain expressed emotions (e.g., happy and disgust) that maintain no related action units (AUs) indicate that AFEA software’s output may not be identifying AUs and determining emotion-based inferences in agreement with FACS. Ultimately, both PA and PG emotions are valuable for informing packaging, food, and dairy industries towards consumer products via their packaging.