Services marketing practices in diverse cultures: Canada compared to Qatar
Bibliographic record
Abstract
Purpose The service marketing literature has traditionally argued that the marketing practices of service firms that operate in diverse cultures should also differ. This paper aims to investigate this argument by examining the marketing practices of service firms in two highly diverse countries “Canada and Qatar” in the context of a contemporary conceptual framework. Design/methodology/approach Survey data were collected in both countries using a self-administered questionnaire that was used in previous contemporary marketing practice (CMP) studies. The data analysis was conducted in two stages. First, descriptive statistics were used to determine cross-national differences in the intensity of use of various CMP activities in Qatar compared to Canada. Second, cross-national differences in various combinations of marketing practices were identified using a cluster analysis. Findings The results indicate that service firms in both countries have more similarities than differences and that the overall patterns of marketing practices are similar. In addition, the firms’ marketing practices reflect aspects of all four marketing approaches rather than just one. Research limitations/implications The study was conducted in only two countries, thus generalisability of its findings and conclusions may not be possible. Practical implications The results of this study can help marketers to better understand the changing marketing environment and identify new marketing solutions when operating in different environments. Originality/value This study enhances the literature on service marketing and expands the application of the CMP framework to a new context that has not been addressed in previous studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".