The Imperative of Interactive Service Marketing Strategy on Customers’ Satisfaction in the Contemporary Nigerian Banking Industry
Bibliographic record
Abstract
The internal crises in Nigerian banking industry between 2005 and 2009 manifested poor interactive relation with the customers among others; leading to failures of some banks and subsequent reforms that have recorded some improvements. This study is to examine the impact of improved interactive service marketing strategy on customers’ satisfaction in contemporary Nigerian banking industry. The customers’ satisfaction variables measured are service/product quality, market share, return on owners’ investment and customers’ loyalty. Sample size was determined using Taro Yeman’s formula. Pilot survey and Cronbach’s Alpha were used to confirm the validity and reliability of the study respectively and their variables of measures. Spearman’s rank correlation coefficient(r), simple regression and partial correlation analyses were the statistical tools used. Consequently the following major findings among others were obtained: (1) It was established that Interactive marketing strategy has positive and significant relationship with service/product quality; positive and moderate relationship with the market share; positive and weak relationship with return on owner’s investment and positive moderate relationship with customers’ loyalty. (2) There was positive and significant relationship between interactive service marketing strategy and customers’ satisfaction with technology moderating them. We conclude that interactive service marketing strategy is a significant tool to embrace in Nigerian contemporary banking industry. We recommend market orientation to banks in order to increase customers’ satisfaction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".