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Record W6894003912 · doi:10.5281/zenodo.8153138

Purchase Intention of Organic Food Products among Generation Y in Malaysia: A Quantitative Study

2022· article· en· W6894003912 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsOrganic productGovernment (linguistics)Food processingFood productsFood industrySnowball samplingPopularityBaby foodProduction (economics)

Abstract

fetched live from OpenAlex

Farming of crops, cattle, and fish are all a part of the food industry, which is essential to the expansion of a country's economy. The food business classifies the food manufacturing process as including both conventional or traditional food and organic food. Producing organic food is growing in popularity as consumers all over the world become more aware of the advantages of leading a healthier lifestyle. The organic food industry in the US is currently the biggest and has the highest sales when compared to other food categories. Similarly, the Malaysian government has supported and encouraged the production of organic food since the late 1980s. Malaysia's research into organic food products is still in its early stages when compared to those of other countries. The Malaysian organic food business is actually understudied right now, with concentration narrowed to a few states and segments. The purpose of this study is to determine Generation Y's intentions to buy organic food products throughout all fourteen states in Malaysia. The relationship between financial and non-financial elements and Generation Y's purchase aspirations is also examined in this study. This study is organised based on the Theory of Reasoned Action (TRA). This study is mostly positivist and employs a quantitative research design. 390 participants from Malaysian public and private universities were chosen for the study using judgemental and snowball sampling techniques. The data were analysed using multiple regression. The results of the study shows that both financial and non-financial factors have a significant influence on people's intentions to purchase organic food. The results even more strongly support the TRA. For businesses, marketers, and food producers, the research findings are helpful since they expand the body of knowledge on purchase intention. The stakeholders would then be able to target, draw in, and fulfil the needs of Generation Y consumers by using efficient marketing strategies.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.233
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2022
Admission routes1
Has abstractyes

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