Mental models: theory and application in human factors
Human Factors
The persistence and transfer of learning in industrial settings
Management Science
Localization of Knowledge and the Mobility of Engineers in Regional Networks
Management Science
Organizational Learning: Creating, Retaining, and Transferring Knowledge
Organizational Learning: Creating, Retaining, and Transferring Knowledge
Deliberate Learning and the Evolution of Dynamic Capabilities
Organization Science
Problem-Solving Oscillations in Complex Engineering Projects
Management Science
Organizing and the Process of Sensemaking
Organization Science
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We analyze longitudinal data on British fertility clinics to examine the impact of “selection at the gate,” i.e., the attempts of organizations to improve the success rate of their output by selecting promising cases as input. In contrast to what might be expected, we argue that more stringent input selection is likely to lead to lower overt performance compared with those firms that admit difficult cases, because the latter develop steeper learning curves. That is, difficult cases enable greater learning from prior experience because they promote experimentation, communication among various actors, and the codification of new knowledge. Our results confirm this prediction and provide clear evidence that organizations with more difficult cases in their portfolios gradually begin to display performance figures that compare favorably with those of firms that do select at the gate.