Handbook of Organization Measurement
Customer Satisfaction
construct.customer_satisfaction
§3The math on what we know
Synthesized priors from the live registry: pooled r, studies (k), total N, top study grade, and heterogeneity. Rows flagged for heterogeneity or single-study evidence are directional, not settled — read them as a central tendency.
What drives customer satisfaction
| Predictor | r | k | N | Grade | Confidence |
|---|---|---|---|---|---|
| Employee Turnover | −0.22 | 2 | 14,174 | A | — |
| Collective Turnover | −0.15 | 2 | 4,270 | A | coherent |
| Employee Engagement | +0.33 | 1 | 3,199 | A | single study |
| Service Climate | +0.25 | 1 | 9,363 | A | single study |
What customer satisfaction predicts
| Outcome | r | k | N | Grade | Confidence |
|---|---|---|---|---|---|
| Firm Performance | +0.10 | 1 | 50 | A | single study |
§4As a model node
Where customer satisfaction sits when you drop it into a model — what feeds it, what it moves. Read left to right as a small, actionable causal claim.
Inputs (drivers)
- Employee Turnover−0.22
- Collective Turnover−0.15
- Employee Engagement+0.33
- Service Climate+0.25
→
Customer Satisfaction
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Outputs (outcomes)
- Firm Performance+0.10