Table 1 Comparison of three logics of experimentation
From: Understanding how city networks are leveraging climate action: experimentation through C40
| Â | Controlled experimentation | Darwinian experimentation | Generative experimentation |
|---|---|---|---|
Characteristics | -Search for valid inferences about cause and effect -Setting controlled as much as possible -Findings aim for external validity -Deductive | -Oriented towards variation through many trials -Identifies ‘best practices’ but also expects many failures -Variation more important than control -Inductive | -Iterative refinement of prototype with goal of ‘success’ -Discovery and design of new solutions -‘Success’ often depends on meeting stakeholder expectations -Abductive |
Allowance for failure | High (researcher should not influence outcome) | Very high (few variations will be successful) | Low (researcher should strive for success) |
Innovations vs. routine | Both | Both | Innovations |
Observational vs. interventional | Intervention at the beginning | More observational than interventional | Continuous improvement of intervention |
Examples | -Randomised control trials -Natural and quasi-experiments | -Parallel experimentation and benchmarking -Rapid experimentation -Simulation experiments | -Design experiments -Exploratory pilot projects -Problem-driven iterative adaptation |