Customer satisfaction, value for money and repurchase intent in the context of system delivery projects: a longitudinal study
Bibliographic record
Abstract
Purpose Drawing upon the relational exchange theory, the longitudinal relationship between various stages of project management customer satisfaction, value for money and repurchase intent are examined. Design/methodology/approach Using a survey questionnaire, data were gathered over four consecutive quarters (N = 2,537). The statistical methods included exploratory factor analysis, confirmatory composite analysis (CCA) and partial least squares structural equation modeling (PLS-SEM). Findings Project management was perceived as a three-dimensional construct (proposal, installation, commissioning/start-up). There was a significant longitudinal relationship between project stages and satisfaction in the complete data set. The results varied on the quarterly basis. The relationship customer satisfaction/repurchase intent was significant in the whole data set and during all quarters. This was the case for the relationships between value for money and customer satisfaction and between value for money and repurchase intent. The effect sizes were small between project management stages and customer satisfaction, small to medium for the value for money construct and large for the customer satisfaction construct. Originality/value An important implication is the significant relationship between the stages of project management and satisfaction. However, the effect sizes were small, however. The importance of the effect size in comparison to the significance of the relationships is highlighted especially when the sample size is large. The paper also confirms the linear relationship between satisfaction and repurchase intent. The nature of the relationship between customer satisfaction and loyalty is based on a moderate exchange relationship in the relational exchange continuum. The study contributes to the relational exchange theory in the context of project management.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".