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Success Factors in Business-Managed IT - A Case Study Analysis at a Large German Industrial Company

Published in SKILL 2018-Studierendenkonferenz Informatik, 2018

The terminology of Business-Managed IT refers to Shadow-IT systems which are operated overtly in the business units (BUs) and with the awareness from the IT department. They are a common phenomenon in corporations and usually emerge if the formal IT organization is unable to provide the BUs with solutions that meet their requirements. Because of this, Business-Managed IT is a highly significant area for an exploratory study, and both academia and practitioners can benefit from knowledge on how such systems can be successfully managed. In this present research, a case study analysis of five Business-Managed IT systems at a large German industrial company was conducted. Interviews with stakeholders involved in these systems were transcribed and analyzed to derive Critical Success Factors (CSFs) for Business-Managed IT. After a careful analysis of the data, a total of nine CSFs for Business-Managed IT systems were obtained. They fall into three dimensions: Project Dimension, Organizational Dimension and System Dimension.

Recommended citation: Bachfischer, Matthias. "Success Factors in Business-Managed IT-A Case Study Analysis at a Large German Industrial Company." SKILL 2018-Studierendenkonferenz Informatik (2018). https://dl.gi.de/bitstream/handle/20.500.12116/28985/SKILL2018-07.pdf?sequence=1&isAllowed=y

Offensive Comment Classification on German Language Microposts

Published in 14th Conference on Natural Language Processing KONVENS 2018, 2018

In this paper, we present two deep-learning based classifier systems for the identification of offensive comments in German Language microposts: A bidirectional LSTM model and a CNN model. Our objective is to compare the performance of these two systems with a traditional, machine-learning based SVM classifier and to evaluate our approach on Task 1 (binary classification) of the GermEval 2018 shared task.

Recommended citation: Bachfischer, M., Akujuobi, U., & Zhang, X. (2018, September). KAUSTmine-Offensive Comment Classification on German Language Microposts. In 14th Conference on Natural Language Processing KONVENS 2018. https://ids-pub.bsz-bw.de/files/8490/Ruppenhofer_Siegel_Wiegand_GermEval2018_Proceedings.pdf#page=39

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