Collective Learning in Organizations—Opportunities and Constraints: Case Study of an Avalanche Blocking a Railway Line

Abstract

Damaged infrastructures cause costly delays and losses. In this study, a collective learning framework (CLF) and the theory of loops of learning are applied to a case study to develop a conceptual model on how lessons learned may be put to more effective use. Structures for systematic learning from events may serve as important tools in proactive adaptation for a more resilient infrastructure in future. This article studies an avalanche blocking a railway and an adjacent road in northern Sweden, which involves several interdependencies of critical infrastructures and actors. To enhance resilience future risk assessment and SWOT analyses should include the effects from a changing climate on the vulnerabilities of interdependence among multiple stakeholders and infrastructures. Knowledge‐sharing foremost resulted in single‐loop learning, leading to incremental changes. Respondents expressed an understanding of the importance of double‐loops feedback but sensed that they lacked incentives from top levels in the organization for future reporting of experiences. This lack of incentives may impede establishing collective memory. The findings of this study can be used to improve policy recommendations, and support building resilience through products of learning.