<p>Complex socio-technical systems, like command and control work in military operations and rescue operations, are becoming more and more common in the society, and there is a growing urge for more useful and effective systems. Qualitative data from complex socio-technical systems can be challenging to analyse. This thesis probes one way of enhancing existing analysis methods to better suit this task.</p><p>Our case study is carried out at FOI (the Swedish Defence Research Agency). One of FOI’s tasks is to analyse complex situations, for example military operations, and they have developed an approach called the Reconstruction – exploration approach (R&E) for analysing distributed tactical operations (DTOs). The R&E approach has a rich contextual approach, but lacks a systematic analytic methodology.</p><p>The assignment of this thesis is to investigate how the R&E approach could be enhanced and possibly merged with other existing cognitive analysis methods to better suit the analysis of DTOs. We identified that the R&E approach’s main weaknesses were the lack of structure and insufficient way of handling subjective data, which contributed to difficulties when performing a deeper analysis. The approach also needed a well-defined analysis method for increasing the validity of the identified results.</p><p>One way of improvement was to integrate the R&E approach with several cognitive analysis methods based on their respective individual strengths. We started by analysing the R&E approach and then identified qualities in other methods that complemented the weaknesses in the R&E approach. Finally we developed an integrated method.</p><p>The Critical Decision Method (CDM) appeared to be the most suitable method for integration with the R&E approach. Nevertheless, the CDM did not have all the qualities asked for so we chose to use functions from other methods included in our initial analysis as well; ETA and Grounded theory.</p><p>The integration resulted in a method with a well-defined method for analysis and the possibility to handle subjective data. This can contribute to a deeper analysis of DTOs.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:liu-4750 |
| Date | January 2005 |
| Creators | Lindström, Maria, Ljungwald, Lena |
| Publisher | Linköping University, Department of Computer and Information Science, Linköping University, Department of Computer and Information Science, Institutionen för datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, text |
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