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Record W4385875626 · doi:10.5539/ijms.v15n2p36

Factors Influencing Impulse Buying Behavior Among Young Male Consumers in Saudi Arabia

2023· article· en· W4385875626 on OpenAlexvenueno aff
Kholoud Alqutub

Bibliographic record

VenueInternational Journal of Marketing Studies · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsImpulse (physics)Situational ethicsPurchasingMarketingClothingConsumer behaviourPsychologyAdvertisingBusinessSocial psychologyGeography

Abstract

fetched live from OpenAlex

Impulse buying is a prominent concept in the study of consumer behavior. Due to humans’ complex psychological nature, many industries focus on impulse buying and design their marketing strategies accordingly. This research investigates the personal factors that affect impulse buying behavior among young men in Saudi Arabia. This study also investigates the effect of situational variables, including family influence, time availability, money availability, and hedonic shopping, on the impulse buying behavior of men in the Saudi Arabian context, focusing on the Western region. The study specifically focuses on purchasing personal items such as perfumes, clothing, and shoes. A survey questionnaire was administered to a convenient sample of 385 males aged between 18 and 50 residing in Western Saudi Arabia. The collected response was analyzed using the statistical software SPSS. The findings of the study indicate that time availability, money availability, and hedonic buying positively influence impulse buying behavior among men living in Saudi Arabia. Notably, this study revealed that family factors had a detrimental consequence on impulsive buying behavior among Saudi men. However, this study had limitations, such as sample size and geographical focus, should be considered when interpreting results. Future research should aim to broaden scope by including a larger and more diverse sample to obtain a more inclusive understanding of impulse buying behavior in Saudi Arabia.

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)0.005
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 score0.011
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
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 science0.0010.001
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 head0.048
GPT teacher head0.313
Teacher spread0.265 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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