Intelligent failure occurs when an entrepreneurial initiative falls short of its anticipated performance. It provides valuable new knowledge to the organisation and is recognised as an important factor in long-term corporate entrepreneurial success. This thesis is located within the domain of corporate entrepreneurship and entrepreneurial failure, and explores the various processes of intelligent failure. The specific aim of this thesis is to learn how organisations manage intelligent failure. Research takes an inductive approach with the predominant use of a qualitative methodology and, as part of a multiple case study strategy, research is carried out in six organisations operating in differing sectors within the UK. Findings indicate that the organisations often fail to manage intelligent failure. There is little evidence of a strategic approach to learning from failure and, where learning occurs, it is predominantly unstructured. This is significant because literature consistently argues that a structured process is required to manage learning from failure successfully. This research recognises that structured processes may be more effective than unstructured processes when looked at in isolation. However, this thesis argues that unstructured mechanisms do have inherent value. Therefore, when organisations develop failure management processes, a dual path may be considered, which might extract value from both systems as is contextually appropriate. This may enable organisations to maximise their ability to learn from failure. This thesis adds to existing management theory in the corporate entrepreneurship domain. In specifically focusing on the structured and unstructured forms within the process of intelligent failure, this thesis addresses a gap in current literature. It also adds to existing literature that centres on the practical management of the learning from failure process.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:716754 |
| Date | January 2016 |
| Creators | Casely, William Robert |
| Contributors | Bessant, John ; Karanika, Katerina |
| Publisher | University of Exeter |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10871/27620 |
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