Profiling E-buyers in Saudi Arabia: Demographic, Experiential, and Attitudinal Factors
Bibliographic record
Abstract
The purpose of this research study is to develop profiles of adopters and non-adopters of internet shopping in Saudi Arabia based on their demographic variables and internet usage patrons and to investigate consumers’ attitude towards online shopping and perception and formation of attitude by using Fishbein and Ajzin (1980) Theory of Reasoned Action (TRA). A profile of internet shopping adopter and non-adapters was drawn. Among the investigated demographic variablesand internet usage patterns, only educational level and previous experience on online purchase were found to differ significantly among consumers. Therefore, demographic variables and internet usage patterns are of limited use to profile Saudi Arabian consumers in terms of attitude towards internet shopping. Key words : Profile; Internet Shopping; E-Commerce; Saudi Arabia; Consumer Behavior Resume: Le but de cette etude est d'elaborer des profils d'adoptants et de non-adoptants des achats sur Internet en Arabie Saoudite en fonction des variables demographiques et des modeles d'utilisation d'Internet et d'etudier l'attitude des consommateurs envers les achats en ligne, leur perception et la formation de l'attitude, en utilisant la Theorie de l'action raisonnee (TAR) de Fishbein et Ajzin (1980). Un profile des adoptants des achats sur Internet et des non-adoptants a ete tire. Parmi les variables demographiques etudies et les modeles d'utilisation d'Internet, il n'y a que le niveau d'education et l'experience precedente de l'achat en ligne sont averes tres differents chez les consommateurs. Par consequent, les variables demographiques et les habitudes d'utilisation d'Internet sont d'un usage limite pour definir le profile des consommateurs de l'Arabie Saoudite en termes d'attitude envers les achats sur Internet. Mots-cles: Profile; Achat Sur Internet; E-Commerce; Arabie Saoudite; Habitude Des Consommateurs
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".