Visible to the public Biblio

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2019-02-25
Lesisa, T. G., Marnewick, A., Nel, H..  2018.  The Identification of Supplier Selection Criteria Within a Risk Management Framework Towards Consistent Supplier Selection. 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). :913–917.
The aim of the study is to evaluate the consistency of supplier risk assessment performed during the supplier selection process. Existing literature indicates that current supplier selection processes yield inconsistent results. Consistent supplier selection cannot be accomplished without stable risk assessment performed during the process. A case study was conducted in a train manufacturer in South Africa, and document analysis, interviews and questionnaires were employed to source information and data. Triangulation and pattern matching enabled a comparative study between literature and practice from which findings were derived. The study suggests selection criteria that may be considered when performing supplier risk assessment during the selection process. The findings indicate that structured supplier risk assessment with predefined supplier selection criteria may eliminate inconsistencies in supplier assessment and selection.
2015-05-05
Koch, S., John, M., Worner, M., Muller, A., Ertl, T..  2014.  VarifocalReader #x2014; In-Depth Visual Analysis of Large Text Documents. Visualization and Computer Graphics, IEEE Transactions on. 20:1723-1732.

Interactive visualization provides valuable support for exploring, analyzing, and understanding textual documents. Certain tasks, however, require that insights derived from visual abstractions are verified by a human expert perusing the source text. So far, this problem is typically solved by offering overview-detail techniques, which present different views with different levels of abstractions. This often leads to problems with visual continuity. Focus-context techniques, on the other hand, succeed in accentuating interesting subsections of large text documents but are normally not suited for integrating visual abstractions. With VarifocalReader we present a technique that helps to solve some of these approaches' problems by combining characteristics from both. In particular, our method simplifies working with large and potentially complex text documents by simultaneously offering abstract representations of varying detail, based on the inherent structure of the document, and access to the text itself. In addition, VarifocalReader supports intra-document exploration through advanced navigation concepts and facilitates visual analysis tasks. The approach enables users to apply machine learning techniques and search mechanisms as well as to assess and adapt these techniques. This helps to extract entities, concepts and other artifacts from texts. In combination with the automatic generation of intermediate text levels through topic segmentation for thematic orientation, users can test hypotheses or develop interesting new research questions. To illustrate the advantages of our approach, we provide usage examples from literature studies.