Leading to customer loyalty: a daily test of the service-profit chain
Bibliographic record
Abstract
Purpose – The purpose of this paper is to explore a dynamic version of the service-profit chain. The paper examines the relationship between daily leadership behaviors, daily job satisfaction and daily employee engagement on customer outcomes in a service-based context. Design/methodology/approach – Using multi-level, dyadic data from employees and customers, the paper used a diary (within-person) approach to investigate the proposed relationships on a daily basis. Data from employees ( n = 29) collected over five days were matched specifically to customer data ( n = 592) during the same time period. Findings – The findings suggest that daily transformational leadership behaviors positively affect daily job satisfaction and employee engagement, which subsequently affect beneficial customer outcomes (i.e. perceptions of quality, satisfaction and loyalty). Research limitations/implications – The relationship between employee attitudes and performance may have been underestimated in the past due to the way the relationship has been studied and that the inclusion of additional predictors better defines this relationship. Methodologically, the use of a daily diary study suggests that it may be much more advantageous to study the theorized relationship in its transient form (i.e. daily, weekly, etc.) versus as stable and enduring attitudes as leaders’ behaviors and employees’ level of engagement will change from day to day in most service-based contexts due to its dynamic nature. Practical implications – The results equip organizations with a clearer picture in delivering high-quality service and its associated beneficial customer outcomes (i.e. perceptions of quality, satisfaction and loyalty). Such insight may be used to influence leadership training that aims to create and maintain an engaged and productive workforce, ultimately providing increased bottom-line performance for the organization. Originality/value – By including additional linkages into a model that aids in predicting important customer outcomes allows us to better understand the relationship. In addition, by studying the relationships from a transient perspective, it provides important information to service organizations that operate in extremely dynamic environments.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".