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Title: Exploring decision processes behind food choices : an eye tracking approach
Author: Perkovic, Sonja
ISNI:       0000 0004 6422 1128
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2017
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This doctoral dissertation makes a twofold contribution to the understanding of psychological processes behind food choice. First, it explores whether cognitive shortcuts, known as heuristics, based on seemingly irrational beliefs can lead to rational behaviours when applied in the right context. One such heuristic, the organic = healthful heuristic, is explored. It is the belief that organic products are more healthful than conventional products. There is no conclusive evidence supporting this belief, also known as the halo effect, where positive attitudes towards organic products transfer to beliefs about specific properties such as healthfulness. Here I propose statistical learning as an alternative explanation to the halo effect, and test this in three studies. Study 1 shows that food products from healthful food categories are more likely to be organic. Study 2 shows that consumer perceptions of the healthfulness and the number of organic products across food categories are accurate. Study 3 shows that consumers perceive organic products as more healthful when the statistical structure justifies this inference. These findings show that consumers correctly use organic products as a cue for healthfulness because they are, on average, 30% more healthful than conventional products. Second, this doctoral dissertation develops a new information search measure which complements existing measures to better describe consumer search processes. One area, which is currently not covered by existing measures, is when information search consists of equal amounts of attribute- and alternative-wise search sequences. I propose a new measure, the Systematicity of Search Index (SSI), which explores information search in terms of systematicity or the proportion of non-random search. Study 4 demonstrates the usefulness of the measure and shows that the SSI can shed light on processes not captured by the existing measures for analysing information search.
Supervisor: Bown, Nicola ; Kaptan, Gulbanu Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available