Consumers' product evaluations in emerging markets
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate, in an emerging market, the simultaneous effects of country of design (COD), country of manufacture (COM), and brand image on consumers' perceptions of bi‐national products. A comprehensive model broadens country‐of‐origin literature by incorporating brand image and the concepts of fit and congruity borrowed from brand extension research. Perceptual (in) coherences that might exist among COD, COM, and the brand are incorporated. Design/methodology/approach Tunisia is the emerging market studied. A total of 389 respondents evaluated different product combinations (COD/COM/brand) in two categories. Relationships between constructs are tested using structural equation modelling. Findings Consumers are sensitive to the COD (more so for public than for private goods) and also value the COM of branded products. The transfer of the COD image to brand image is significant. It is very high for one product category (cars). Brand/COM congruity is also important since product evaluations decrease when consumers perceive incoherence in a manufacturing location. Research limitations/implications The paper used limited informational cues for products' descriptions and concentrate on fairly complex durable goods. Research design should be expanded. Practical implications Perceived COD competencies can benefit brand image through strong COD‐brand associations. In emerging markets, COD (through brand image) and COM effects are important for understanding consumers' perceptions of publicly versus privately used branded products. Originality/value The major contribution consists of a simultaneous examination of the effects of COD, COM, brand, and of their inter‐relationships. Investigating bi‐national products and related consumer behaviour in emerging markets is of particular interest as it corresponds to the reality of these markets.
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 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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".