The impact of a western country of reference (COR): The effect on Jordanian youth consumer
Bibliographic record
Abstract
This study sought to empirically test the novel Country-of-Reference (COR)-effect by investigating the impact of Westernization on Jordanian youth’s purchasing behavior. The constructs examined were (Social-Identity) Self-Discrepancy, eWOM, and Herd Behavior in relation to Western COR and subsequently, purchase behavior. The data was collected in two phases; semi-structured in-depth interviews and online surveys. 12 interviews were conducted in total, following the saturation principle. Moreover, 232 questionnaire responses were gathered, through convenience sampling and snowballing techniques. The study substantiated the existence of strong links between (social identity) self-discrepancy, eWOM, herding behavior, and Western COR. In addition, proved Western COR’s mediating role between the variables and purchase behavior. Conclusively, all the proposed hypotheses were corroborated qualitatively and quantitatively. Researchers looking to further study the COR-effect should consider possible time, budget, and language restraints. As well as extend the literature to varying age groups and geographical areas. Moreover, it might be interesting to explore the COR concept in diverse industries and through a comparative research approach. This research paper analyzed a new notion of understanding consumer behavior. More specifically, it is the first to assess the role Westernization plays in Jordanian youth consumers’ consumption behaviors. Further, the findings presented in this study can aid businesses and boost the economy, through encouraging “shop local” communication strategies.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".