The Effect of Demographic Characteristics on Antecedents and Consequences of Customer Satisfaction in Banking Industry
Bibliographic record
Abstract
Satisfaction is a key variable in services marketing that determines the development of long-term relationships. The purpose of current study is to determine the effects of demographic characteristics on antecedents and consequences of customer satisfaction in banking industry. Statistical population was bank customers in the area of Tehran. An analysis of variance (ANOVA) was used for data analysis. Data was collected on customer characteristics, sending a questionnaire to 551 customers of governmental and private bank branches in Tehran, Iran. Finding reveals that gender influences loyalty. Age has a significant impact on trust. Additionally, customer’s education influenced widely switching costs. Customer satisfaction, trust and switching costs have been influenced by customer job. Finally, customer income influences customer satisfaction, complaints, trust and loyalty. Key words: Customer satisfaction; Banking industry; Demographic characteristics; Iran La satisfaction est une clevariable dans le marketing des services, qui determine le developpement de relations a long terme. Le but de la presente etude est de determiner les effets des caracteristiques demographiques sur les antecedents et les consequences de la satisfaction client dans le secteur bancaire. Population statistique a ete clients de la banque dans la region de Teheran. Une analyse de variance (Anova) a ete utilise pour l'analyse des donnees. Les donnees ont ete recueillies sur les caracteristiques des clients, l'envoi d'un questionnaire a 551 clients de succursales de banques publiques et privees a Teheran, en Iran. Trouver revele que la loyaute des sexes influences. L'âge a un impact significatif sur la confiance. de plus, l'education a la clientele a influence considerablement les couts de commutation. couts satisfaction de la clientele, la confiance et de commutation ont ete influences par poste client. Enfin, les revenus des clients influe sur la satisfaction des clients, des plaintes, la confiance et la loyaute. Mots-cles: Satisfaction du client; Industrie bancaire; Caracteristiques demographiques; Iran
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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 | 0.007 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".