The Impact of Service Quality and Cultural Beliefs on Intention to Use Financial Services: The Moderating Role of Trust
Bibliographic record
Abstract
In the context of developed countries and in several Middle Eastern countries, the problem of motivating consumers to make use of banking services has been resolved. However, in Yemen, majority of the citizens are non-bank users. This fact leads to a major issue and negatively affects the economy of the country. In this regard, the present study aims to shed a light on the factors that have the potential to influence Yemeni citizen’s use of the country’s banking system like service quality and Yemeni culture. For this purpose, 850 questionnaires were distributed to part-time university going students. Data collected was analyzed with the help of correlation and multiple regression analysis to determine the factors prediction of the behavioral intention to use Yemeni banking system. The results showed the positive and significant effect of service quality and the significant and negative effect of culture on the consumers’ use of Yemeni banking system. Moreover, hierarchical regressions were used to test the effect of trust as a moderator variable. Student’s trust had a statistically moderating the relationship between cultural belief and intention but in the negative direction. The study contributes to the academic understanding of the behavioral intention of consumers in the context of Yemen and to the practitioners and policy makers use of the effective strategy to attract customers to the country’s banking system.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".