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Record W2809703623 · doi:10.3390/joitmc4030024

Factors Affecting the Buying Intention of Organic Tea Consumers of Bangladesh

2018· article· en· W2809703623 on OpenAlex
Razia Sultana Sumi, Golam Kabir

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Open Innovation Technology Market and Complexity · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBusinessSafeguardingMarketingProduct (mathematics)Organic productGlobalizationScale (ratio)AdvertisingAgricultureGeographyEconomics

Abstract

fetched live from OpenAlex

In the modern era of globalization, consumers become aware and concerned about their health as well as natural resources and the environment. Technological improvement and economic growth are continuously exploiting the earth’s resources, resulting in an overwhelming burden on earth's ecology. Confirming a state of equilibrium between economic growth and safeguarding the environment becomes a challenge for business people and marketers. Though people worldwide are becoming interested in buying organic food, the concept of organic farming is relatively new in Bangladesh. The tea industry has started off with producing organic tea on a very limited scale. In this study, the researchers tried to examine the buying intention of organic tea among the consumers of Bangladesh. The study demonstrated that trust and perceived price significantly affect the buying intention of organic tea consumers along with product attributes, health consciousness, and environmental concern. Marketers may consider the stated factors to create an influence on the selection process of organic tea by consumers.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score0.485

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.061
GPT teacher head0.273
Teacher spread0.211 · 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