Xenocentrism and Consumer Buying Behavior: A Comparative Analysis of Malaysian vs. Nigerian Consumers
Bibliographic record
Abstract
Across the globe, xenocentrism has emerged as a critical concept for understanding the behavior of consumers towards the purchase of local and foreign products. In line with this context, and based on samples collected from Malaysia and Nigeria, this study analyzed the direct effects of xenocentrism on the buying behavior of consumers towards imported products with perceived product quality, purchase intention, and product attitude as the variables used to measure consumers’ buying behavior. XSCALE was used to measure xenocentrism, and the research model was analyzed with the partial least squares form of structural equation modeling. A total of 400 responses were gathered from Malaysia, whereas 453 responses were gathered from Nigeria. Findings from the investigation show that xenocentrism has a positive influence on perceived product quality (Malaysia = 46.7%, Nigeria = 35%), purchase intention (Malaysia = 46%, Nigeria = 47.3%), and product attitude (Malaysia = 39.2%, Nigeria = 38.4%), Based on these findings, this study concluded that xenocentrism is a valid construct for assessing the purchase behavior of consumers in Malaysia and Nigeria towards foreign products competing in their local markets. On the same note, the findings from this research can be used to develop sustainable marketing strategies suitable for xenocentric consumers across Malaysia and Nigeria (in particular), and the entire developing economies (in general).
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".