Factors Influencing Impulse Buying Behavior Among Young Male Consumers in Saudi Arabia
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".