Bachelor
2024/2025![Learning Objectives](/f/src/global/i/edu/objectives.svg)
![Expected Learning Outcomes](/f/src/global/i/edu/results.svg)
![Course Contents](/f/src/global/i/edu/sections.svg)
![Interim Assessment](/f/src/global/i/edu/intermediate_certification.svg)
![Bibliography](/f/src/global/i/edu/library.svg)
Quantitative Decision Making in a Big Data Society
Type:
Compulsory course (Digital Product Management)
Area of studies:
Business Informatics
Delivered by:
Department of Business Informatics
Where:
Graduate School of Business
When:
3 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Margarita Gladkova
Language:
English
ECTS credits:
5
Contact hours:
50
Course Syllabus
Abstract
Management science can be defined as the application of scientific and systematic procedures, techniques and tools to operational, strategic and policy problems in order to help develop and evaluate solutions to problems encountered within management. Management science includes all rational approaches to management decision-making that are based on an application of scientific and systematic methodologies. Both management science as a discipline, and management scientists as individuals with specialised training, aid management by providing a structure to decision-making situations whose complexity, and/or level of uncertainty, makes intuition an unsafe guide. The distinctive feature of the management science approach is the construction of an explicit, simplified model of relevant aspects of the situation under study. Such models are often based on mathematical or statistical formulations, but may at other times have a more qualitative character.
Learning Objectives
- enable you to see that many managerial decision-making situations can be addressed using standard techniques and problem structuring methods
- provide a comprehensive and concise introduction to the key techniques and problem structuring methods used within management science that are directly relevant to the managerial context
- enable you to see both the benefits, and limitations, of the techniques and problem structuring methods presented.
Expected Learning Outcomes
- be able to discuss the main techniques and problem structuring methods used within management science
- to be able to carry out simple exercises using such techniques and problem structuring methods themselves (or explain how they should be done)
- to be able to critically appraise the strengths and limitations of these techniques and problem structuring methods
Course Contents
- Problem structuring and problem structuring methods
- Mathematical programming formulation
- Linear programming solutions
- Network analysis
- Decision making under uncertainty
- Inventory control
- Queueing theory and simulation
- Markov processes
Interim Assessment
- 2024/2025 2nd module0.4 * Exam + 0.15 * Group hometasks + 0.15 * Group hometasks + 0.1 * In-class tests + 0.1 * In-class tests + 0.05 * Quizzes + 0.05 * Quizzes
Bibliography
Recommended Core Bibliography
- An introduction to management science : quantitative approaches to decision making, , 2017
- Rational analysis for a problematic world revisited : problem structuring methods for complexity, uncertainty and conflict, Rosenhead, J., 2009
Recommended Additional Bibliography
- Operations research : applications and algorithms, Winston, W. L., 2004