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Record W2204792678 · doi:10.5539/ass.v12n1p1

Consumers’ Perceptions of Green Marketing in the Hotel Industry

2015· article· en· W2204792678 on OpenAlexvenueno aff
S. Punitha, Yuhanis Abdul Aziz, Azmawani Abd Rahman

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsDynamismNonprobability samplingMarketingGreen marketingBusinessPerceptionHotel industryMarketing managementSample (material)AdvertisingTourismSociologyPolitical sciencePsychology

Abstract

fetched live from OpenAlex

<p>This paper attempts to explore the evolution of green marketing in the hotel industry. This study is guided by three research questions: (1) to explore the level of understanding of local and international tourists on green marketing; (2) to gather tourists’ points of view if marketers have failed or they have never really tried to adopt the concept; and (3) to examine the level of awareness of tourists relating to green practices embraced by hotels. Purposive sampling using the Maximum Variation Sampling (MVS) technique is used to capture a wide range of perspectives in selecting the respondents. The discussion reveals that the concept has evolved hastily in developed countries while it is an emerging trend in developing countries like Malaysia. While some hotels have already begun to respond to environmental concerns in the country, the lack of promotions and advertisements have become part of the causes of knowledge non-appearance. This paper further concludes that green marketing concept should not just be adopted as a marketing tactic, but has to be considered with much greater dynamism, as it has ecological and social elements within it.<strong></strong></p>

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.262
Teacher spread0.241 · 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.

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

Citations22
Published2015
Admission routes1
Has abstractyes

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