Improving consumers’ eating habits: what if a brand could make a difference?
Bibliographic record
Abstract
Purpose This research sheds light on behavioral change by demonstrating the transformative power of a brand on the process of eating behavioral change. The selected brand isThree Times a Day(a culinary blog whose mission is to encourage a healthier diet). This study aims to identify food-related behavioral changes as a result of consumers’ relationship with this brand and identify antecedents to such changes. Design/methodology/approach A netnography of the brand online community and 14 individual in-depth interviews were conducted. Findings Netnography results identify four categories of behavioral changes emerging from the relationship with the brand (e.g. choosing healthier/more varied foods, developing an interest in cooking and adopting a healthier lifestyle). Analysis of the individual interviews substantiate the role of brand attachment as a driver of positive change and identify three antecedents: brand-self connection (through past, actual and ideal self), brand exposure and satisfaction of individual needs (i.e. autonomy, competence and relatedness). Research limitations/implications Results enrich the literature on behavioral change and highlight the positive role of a brand in the context of improving eating habits. Findings extend the understanding of the consequences of attachment beyond its influence at the attitudinal level by focusing on concrete consumer behavior. Social implications It is recognized that despite good intentions, individuals keep making poor food choices. This important issue is associated with several diseases and increasing social costs. This research explores how to influence consumers in adopting better eating habits. Originality/value This study is one of the first to examine the power of a food-related brand to enhance positive eating practices and improve diet.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".