Application of Automated Facial Expression Analysis and Qualitative Analysis to Assess Consumer Perception and Acceptability of Beverages and Water
| dc.contributor.author | Crist, Courtney Alissa | en |
| dc.contributor.committeechair | Duncan, Susan E. | en |
| dc.contributor.committeemember | Rudd, Rick D. | en |
| dc.contributor.committeemember | Dietrich, Andrea M. | en |
| dc.contributor.committeemember | O'Keefe, Sean F. | en |
| dc.contributor.department | Food Science and Technology | en |
| dc.date.accessioned | 2017-10-20T06:00:15Z | en |
| dc.date.available | 2017-10-20T06:00:15Z | en |
| dc.date.issued | 2016-04-27 | en |
| dc.description.abstract | Sensory and consumer sciences aim to understand the influences of product acceptability and purchase decisions. The food industry measures product acceptability through hedonic testing but often does not assess implicit or qualitative response. Incorporation of qualitative research and automated facial expression analysis (AFEA) may supplement hedonic acceptability testing to provide product insights. The purpose of this research was to assess the application of AFEA and qualitative analysis to understand consumer experience and response. In two studies, AFEA was applied to elucidate consumers emotional response to dairy (n=42) and water (n=46) beverages. For dairy, unflavored milk (x=6.6±1.8) and vanilla syrup flavored milk (x=5.9±2.2) (p>0.05) were acceptably rated (1=dislike extremely; 9=like extremely) while salty flavored milk (x=2.3±1.3) was least acceptable (p<0.05). Vanilla syrup flavored milk generated emotions with surprised intermittently present over time (10 sec) (p<0.025) compared to unflavored milk. Salty flavored milk created an intense disgust response among other emotions compared to unflavored milk (p<0.025). Using a bitter solutions model in water, an inverse relationship existed with acceptability as bitter intensity increased (rs=-0.90; p<0.0001). Facial expressions characterized as disgust and happy emotion increased in duration as bitter intensity increased while neutral remained similar across bitter intensities compared to the control (p<0.025). In a mixed methods analysis to enumerate microbial populations, assess water quality, and qualitatively gain consumer insights regarding water fountains and water filling stations, results inferred that water quality differences did not exist between water fountains and water filling stations (metals, pH, chlorine, and microbial) (p>0.05). However, the exterior of water fountains were microbially (8.8 CFU/cm^2) and visually cleaner than filling stations (10.4x10^3 CFU/cm^2) (p<0.05). Qualitative analysis contradicted quantitative findings as participants preferred water filling stations because they felt they were cleaner and delivered higher quality water. Lastly, The Theory of Planned Behavior was able to assist in understanding undergraduates' reusable water bottle behavior and revealed 11 categories (attitudes n=6; subjective norms n=2; perceived behavioral control n=2; intentions n=1). Collectively, the use of AFEA and qualitative analysis provided additional insight to consumer-product interaction and acceptability; however, additional research should include improving the sensitivity of AFEA to consumer product evaluation. | en |
| dc.description.degree | Ph. D. | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:7617 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/79718 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | automated facial expression analysis | en |
| dc.subject | milk | en |
| dc.subject | Water | en |
| dc.subject | qualitative | en |
| dc.subject | theory of planned behavior | en |
| dc.subject | emotion | en |
| dc.subject | affect | en |
| dc.subject | bitter | en |
| dc.title | Application of Automated Facial Expression Analysis and Qualitative Analysis to Assess Consumer Perception and Acceptability of Beverages and Water | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Food Science and Technology | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Ph. D. | en |