Impact of employee job satisfaction and commitment on customer perceived value
Bibliographic record
Abstract
Purpose The purpose of this paper is to analyse the impact of employee job satisfaction and affective commitment as perceived by customers on customer perceived value, more specifically its benefits dimensions. Design/methodology/approach A total of 652 panellists from a large Canadian polling firm self-administer a web-based questionnaire. To measure customer perceived value, a formative index is used which contributes to topical literature through a unique methodology. Hypotheses are tested using a structural equation model. Findings An analysis of the direct, indirect and total effects confirms the unique positive impact of employee job satisfaction and affective commitment, as perceived by customers, on the emotional, social, relationship and epistemic benefits, as well as on the formative index of customer perceived value. Practical implications Customer perceptions of employee attitudes (job satisfaction and affective commitment) represent a unique opportunity for banks to differentiate their value proposition in a hypercompetitive market. Originality/value This study is the first to consider customer perceptions of employee job satisfaction and affective commitment in relation to a formative index of customer perceived value and its related benefits dimensions.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".