Abstract
Maturity models have been successfully used in a number of areas, such as software development and supply chain management, and their success has made them appealing for other areas, including knowledge management. This study questions the validity of the existing maturity models in knowledge management and attempts to build one using a transparent development process. However, the research leads to unexpected results; it demonstrates that building a maturity model for knowledge management is problematic, and questions the very framework and the hierarchy of parameters of the process maturity as well. These findings were enabled by employing a combination of two methods: machine learning using knowledge-based expert system (also referred to as inductive or case-based reasoning, CBR) and correlation analysis, of which the former is new to this type of research.
Original language | English |
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Pages | 1-39 |
Number of pages | 39 |
Publication status | Published - 22 Jun 2017 |
Event | 17th Annual Conference of the European Academy of Management 2017 - Glasgow, United Kingdom Duration: 21 Jun 2017 → 24 Jun 2017 http://euramonline.org/annual-conference-2017-2.html |
Conference
Conference | 17th Annual Conference of the European Academy of Management 2017 |
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Abbreviated title | EURAM 2017 |
Country/Territory | United Kingdom |
City | Glasgow |
Period | 21/06/17 → 24/06/17 |
Internet address |
Keywords
- knowledge management
- maturity models
- knowledge management systems