MétaCan
Menu
Back to cohort
Record W4285390787 · doi:10.5539/jsd.v15n4p136

The Influencing Factors of Consumers’ Purchase Intention toward Green Products: A Case of Consumers in Saudi Arabia

2022· article· en· W4285390787 on OpenAlexvenueno aff
Hiam G. Almohammadi, Nadia A. Abdulghaffar

Bibliographic record

VenueJournal of Sustainable Development · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsTheory of planned behaviorGreen marketingMarketingBusinessConsumption (sociology)Green consumptionConceptual modelConceptual frameworkStructural equation modelingControl (management)Consumer behaviourAdvertisingPsychologyProduction (economics)EconomicsSociologyMathematicsSocial science

Abstract

fetched live from OpenAlex

Traditional consumption patterns are considered to be among the leading causes of global environmental degradation. Green marketing has emerged as a possible solution to these harmful effects on the environment; it aims to provide services and products that have a positive impact on the ecosystem and that satisfy consumers’ needs. This study investigates the factors that have an influence on consumers’ intentions to purchase green products in Saudi Arabia. Attitudes toward green products (AGP), perceived behavioral control (PBC), subjective norms (SN), environmental concern (EC), environmental knowledge (EK), and green purchase intention (GPI) are examined. A questionnaire is used as a method of data collection to gain information from 251 consumers in Saudi Arabia. The conceptual model is constructed based on planned behavior theory (TPB) to support the framework of the current study. SPSS version 22.0 software was used to investigate the collected data. The study reveals that a consumer’s attitude, environmental concern, and environmental knowledge are the main factors that influence the intention to buy green products in Saudi Arabia. Perceived behavioral control and subjective norms do not significantly support this purchase intention.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.016
GPT teacher head0.221
Teacher spread0.205 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sustainable DevelopmentSame topicEnvironmental Sustainability in BusinessFrench-language works237,207