LEARNING OUTCOMES
Management Science uses analytical models to help make better business decisions. This course focuses on models for supporting decision making under uncertainty, risk and multiple objectives. After taking the course the student can (i) recognize the types of real-life business problems where the use of models adds value, (ii) interpret results of these models to derive defensible decision recommendations, and (iii) build and solve these models computationally to support business decision making.
Credits: 6
Schedule: 08.01.2024 - 19.02.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Ilkka Leppänen
Contact information for the course (applies in this implementation):
Email: ilkka.j.leppanen@aalto.fi
I am available for consultation meetings outside of lecture hours, room T201 / Teams.
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Simulation, decision trees, value of information, expected utility theory, risk attitudes, stochastic dominance, risk measures, multi-attribute utility/value theory, modelling uncertainty and multiple objectives in optimization problems.
Assessment Methods and Criteria
valid for whole curriculum period:
Coursework and exam
applies in this implementation
There are three individual assignments that together form 50% of the course grade. The exam is 50% of the grade.
Workload
valid for whole curriculum period:
Contact teaching, individual work, exam.
DETAILS
Study Material
applies in this implementation
Course material is delivered via MyCourses and consists mostly of lecture slides.
The following textbook is recommended as additional reading: Anderson, David R. (David Ray) et al. An Introduction to Management Science ; Quantitative Approaches to Decision Making. 14th ed. Boston, MA, 2016. (Other editions from the same author(s) are also applicable).
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
8 Decent Work and Economic Growth
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 Spring III
2023-2024 Spring IIIapplies in this implementation
We will use a mix of computational techniques, including spreadsheet modelling and Python/R scripts. Please expect that the assignments require a moderate level of coding to produce programming scripts. The focus is not on programming itself, rather on formulating models for problem solving using modern computational techniques. The teaching sessions will have dedicated time to support students in using these tools.