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Record W4396840562 · doi:10.5539/jas.v16n6p80

Analysis of the Influencing Factors of Farmers’ Willingness to Participate in the Integration of Tea and Tourism—An Empirical Study of Tea Farmers in Emeishan City

2024· article· en· W4396840562 on OpenAlexvenueno aff
Mei Lan Fang, Zhu Man

Bibliographic record

VenueJournal of Agricultural Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
Fundersnot available
KeywordsTourismBusinessMarketingRevenuePublicityWillingness to payEconomicsGeography

Abstract

fetched live from OpenAlex

This paper is based on a questionnaire survey of 277 tea farmers and the operating enterprises of Jia’e Tea Valley in Emeishan City. Using the theory of deconstructive planning behavior, the influencing factors of the willingness of tea farmers to participate in the integration of tea and tourism are analyzed. In order to unleash the enthusiasm and initiative of tea farmers, promote the organic integration of tea industry and tourism, increase their income, and promote rural revitalization. The results indicate that (1) Behavioral attitudes, subjective norms, and perceived behavioral control have a significant impact on the willingness of tea farmers to participate in the integration of tea and tourism, but the influence of tea tourism integration concepts on tea farmers’ behavioral attitudes is not significant. (2) Individual characteristics such as age, education level, family labor force, and per capita disposable income have a significant impact on tea farmer behavior attitudes, subjective norms, and perceived behavioral control, and have a significant indirect impact on the willingness to participate in tea tourism integration. Therefore, this article suggests that grassroots organizations should play a guiding role and increase publicity on the necessity and feasibility of integrating tea and tourism; Give full play to the leading role of village and community cadres, as well as the exemplary and driving role of tea farmers in the same village; Efforts will be made to enhance the recognition and trust of tea farmers in the enterprises they rely on, increase revenue expectations, expand participation channels, reduce participation thresholds and risks, and make tea farmers feel that they can make progress and gain through tea tourism integration, thereby enhancing their enthusiasm and initiative in participating in tea tourism integration.

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)0.002
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.299
Teacher spread0.268 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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