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Record W2747094835 · doi:10.5539/ass.v13n9p100

What Motivates Consumers to Purchase Organic Food in Malaysia?

2017· article· en· W2747094835 on OpenAlexvenueno aff

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)MarketingConsumption (sociology)ConsciousnessStructural equation modelingKuala lumpurPsychologyAdvertisingFood productsFood consumptionBusinessConsumer behaviourFood scienceSociologyEconomicsAgricultural economicsMathematicsSocial science

Abstract

fetched live from OpenAlex

The aim of this study is to investigate the consumer motivational factors that influence their attitude to purchase of organic food in Malaysia. Consumer motivational factors involved past experience, health consciousness and personal values were examined in this study. Data from 421 organic food consumers were obtained through a survey conducted in Kuala Lumpur and Petaling Jaya or better known as Klang Valley, Malaysia. The structural equation modelling was used for data analysis and four hypotheses were tested. The findings showed that all four hypotheses were accepted. Health consciousness had the greatest positive influence on consumer attitude of organic food, followed by past experience and personal values. Purchase of organic food products was significantly affected by consumer attitude of the products. The contribution of this paper is twofold. First and from a theoretical perspective, it offers both development and validation of Theory of Planned Behaviour and Hierarchy of Effect model. Second and from a pragmatic perspective, the findings proposed useful information to organic food providers in developing and implementation of effective strategies to enhance consumption of organic food.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
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 studies0.0010.001
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0000.000
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 head0.014
GPT teacher head0.250
Teacher spread0.237 · 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

Citations34
Published2017
Admission routes1
Has abstractyes

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