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Record W7038406416

The Growing Organic Market: Factors that Influence Consumers' Evaluation and Choice

2011· dissertation· en· W7038406416 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2011
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsnot available
Fundersnot available
KeywordsHyporeflexiaNucleofectionArticular cartilage damageLiquationFusible alloyGestational period
DOInot available

Abstract

fetched live from OpenAlex

The growth of organic products has been considerable over the last decade. The annual growth rate of organic food from 1995 to 2007 in the United States has been around 19% (Monier, Hassan, Nichèle, & Simioni, 2009), and in Canada of 20% (Anders & Moeser, 2008); making of this industry a relevant area of study. This research examines whether and to what extent brand and consumer characteristics influence consumers’ attitude toward and choice of organic food products. It considers the impact of brand history (organic versus non-organic brand) and brand credibility (low versus high), as well as the impact of consumer factors, such as scepticism, concern for the environment, price sensitivity, and knowledge. The results of a laboratory study show that the organic brand was better evaluated in terms of quality perceptions than the non-organic brand. This study was also able to demonstrate that, among consumers with high price sensitivity, quality perceptions towards organic products were amplified for the organic brand and diminished for the non-organic brand compared to their low price sensitivity counterparts. Consumer knowledge influences overall evaluation of the brands, being the organic one the best rated; and with respect to concern for environment and scepticism, significant effects were not found. Suggestions for future research and managerial implications are also discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.254
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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