Prerequisites | Basic knowledge from Operations Research (linear programming) and from decision theory are expected. |
Bibliography |
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Content of teaching | In this lecture, classical Business Administration is applied to businesses in an information- and communicationtechnological environment. The process to extract relevant data for decision making from operational accounting systems receives special attention. In order to do so, topics such as activity-based costing and transaction costs models are addressed. The automization of the decision making process in businesses by data bases is another focus of the module. To solve such issues within a company, relevant methods such as decision theory and game theory are lectured. Finally, complex business relevant questions in a dynamically changing environment are adressed by presenting models and methods from system dynamics. |
Workload | The total workload for this course is approximately 150 hours (5 credits): Time of attendance
Self-study
Sum: 150h 00m |
Aim | The student is able to
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Exam description | Assessment consists of a written exam of 1 hour length following §4 (2), 1 of the examination regulation and by submitting written papers as part of the exercise following §4 (2), 3 of the examination regulation. The course is considered successfully taken, if at least 50 out of 100 points are acquired in the written exam. In this case, all additional points (up to 10) from excersise work will be added. Grade: Minimum points
The grade consists of approximately 91% of exam points and 9% of exercise points. |
Business Administration in Information Engineering and Management
type: | Vorlesung (V) | links: | weitere Informationen |
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semester: | SS 2018 | ||
time: | 2018-04-20 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-04-27 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-05-04 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-05-11 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-05-18 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-05-25 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-06-01 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-06-08 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-06-15 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-06-22 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-06-29 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-07-06 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-07-13 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude 2018-07-20 09:45 - 11:15 wöchentlich 10.91 Redtenbacher-Hörsaal 10.91 Maschinenbau, Altes Maschinenbaugebäude |
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lecturer: | Prof. Dr. Andreas Geyer-Schulz | ||
sws: | 2 | ||
lv-no.: | <a target="lvn" href="https://campus.studium.kit.edu/events/ymWMUAf-Q_apo1FKiV6O_g">2540500</a> | ||