Aspiration performance and railroads' patterns of learning from train wrecks and crashes

We link two influential organizational learning models—performance feedback and experiential learning—to advance hypotheses that help explain how organizations' learning from their own and others' experience is conditioned by their aspiration-performance feedback. Our focus is on learning from failure; this kind of learning is essential to organizational learning and adaptation, and a necessary complement to studies of learning from success. Our analysis of U.S. Class 1 freight railroads' accident costs from 1975 to 2001 shows that when a railroad's accident rate deviates from aspiration levels, the railroad benefits less from its own operating and accident experience and more from other railroads' operating and accident experiences. These findings support the idea that performance near aspirations fosters local search and exploitive learning, while performance away from aspirations stimulates nonlocal search and exploration, providing a foundation for constructing more-integrated models of organizational learning and change.