Effects of organizational and serviceperson orientation on customer loyalty
Bibliographic record
Abstract
Purpose Within the service industry, the serviceperson enhances customer loyalty by increasing customer benefits and decreasing customer costs, but is also embedded within and influenced by the organizational context. Thus, the influence of a serviceperson's orientation may differ or even conflict with the organization's orientation. There are two purposes to this paper. The paper first aims to develop a conceptual model that clearly distinguishes between benefit‐ and cost‐based explanations of the effect of the serviceperson. The paper's second aim is to examine the impact of the organization on the serviceperson's ability to foster customer loyalty through interactions with customers. Design/methodology/approach A survey methodology is used and data gathered from managers and customers. Multi‐group structural equation modeling is employed to test partial mediation and partial moderation theses. Findings In line with social exchange theory, the paper finds that a serviceperson's customer orientation can reduce customer costs and increase customer benefits. Furthermore, consistent with the literature on strategic orientations, when the serviceperson's organization evinces a low competitive service orientation, it attenuates the direct effects of a serviceperson's customer orientation on customer loyalty, such that the direct effect no longer exists. Originality/value The paper shows how multiple direct and indirect pathways connect serviceperson customer orientation to customer loyalty. It also shows how the effect of serviceperson customer orientation on customer loyalty depends on the organizational context and specifically the extent to which the organization embraces a competitive service orientation. The moderating role of organizational context has implications both for social exchange theory specifically and theories of exchange, such as transaction cost analysis more generally.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".