The moderating effect of normative commitment on the service quality-customer retention relationship
Bibliographic record
Abstract
Purpose – Limited attention has been given to the effects of normative commitment (NC) in a marketing relationship. This paper investigates the effects of service quality and normative commitment on customer retention in a consumer-retailer relationship. Design/methodology/approach – Two distinct studies; a longitudinal experiment and a SEM model were conducted to tease out the normative commitment-service quality interaction on customer switching intentions in services. Findings – Both studies supported the existence of a significant normative commitment-service quality interaction on switching, in addition to the main effects of both variables. Research limitations/implications – The longitudinal experiment has the limitation of being a simple test of theory in a controlled setting. Study II validates this theory in a real-world retail services setting, but there are questions about the extent to which the relationship may hold in other service sectors. The results indicate that the effect of service quality on customer loyalty is moderated by normative commitment. This may also allow us to think about customer commitment in a new way in that it could be a construct rooted in attitude confidence rather than attitude. Practical implications – The findings allow practitioners to recognize that the development of obligation-based normative commitment can give them a basis for successful competition against other firms, even those that may outperform them on other salient attributes, including basic service quality. Originality/value – This is one of a very small number of studies in the discipline that have examined the effects of normative commitment and the first that has demonstrated that normative commitment moderates the service quality-service customer retention relationship. This opens the door for the possibility that other forms of commitment may moderate the relationship between service quality and customer retention.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.057 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".