Schedule: 14.01.2019 - 18.02.2019
Teacher in charge (valid 01.08.2018-31.07.2020):
Contact information for the course (applies in this implementation):
Liesiö, email@example.com, G4.13, Chydenia, Runeberginkatu 22-24, Office
hours: After lectures or by appointment
Teaching Period (valid 01.08.2018-31.07.2020):
Period III (2018-2019) Otaniemi campus
Period III (2019-2020) Otaniemi campus
Learning Outcomes (valid 01.08.2018-31.07.2020):
Management Science deals with use of analytical models to help make better business decisions. This course focuses on models for supporting decision making under uncertainty, risk and multiple objectives. After the course the student can (i) recognize the types of real-life business problems where use of the models brings added value, (ii) interpret results of these models to derive defensible decision recommendations, and (iii) build and solve these models using a computer to support business decision making.
Content (valid 01.08.2018-31.07.2020):
Monte Carlo simulation, decision trees, value of information, expected utility theory, risk attitudes, stochastic dominance, risk measures, multi-attribute utility/value theory, modelling uncertainties and multiple objectives in optimization problems.
Details on the course content (applies in this implementation):
This course focuses on MS methods that support
decision making under uncertainty and/or multiple objectives (see schedule for
detailed list of topics). Some required background concepts from applied
probability are also covered.
Assessment Methods and Criteria (valid 01.08.2018-31.07.2020):
Assignments 50%, exam 50%.
Elaboration of the evaluation criteria and methods, and acquainting students with the evaluation (applies in this implementation):
Final points, which consist of exam point (50%) and assignment points (50%), determine the final grade: >50p ->1; >60p -> 2; >70p -> 3; >80p -> 4; >90p -> 5. These bounds maybe relaxed during final grading. Moreover, at least half of the exam points are required to pass.
There are three assignments with deadlines during the
course. Each assignment consists of 4-12 problems or cases, which usually
require the use of spreadsheets or other mathematical software to solve.
Assignments are individual work. You may discuss the
problems with your colleagues, but you must
return individual answers. Returning
a copied answer or solution is strictly forbidden. Remember that in the exam
you will need to individually solve equivalent problems.
Workload (valid 01.08.2018-31.07.2020):
Contact teaching 36h, individual work 121h, exam 3h. Total 160h (6 ECTS).
Details on calculating the workload (applies in this implementation):
Contact teaching includes lectures, assignment demonstrations and assignment feedback.
Individual work includes class preparation (12h), work on the assignments (101h) and preparing for the exam (8h).
Study Material (valid 01.08.2018-31.07.2020):
Lecture slides, articles, assignments, computer implementations of mathematical models, and the textbook (An Introduction to Management Science by Anderson et al., 2014, ISBN Code: 978-1-111-82361-0).
Details on the course materials (applies in this implementation):
Course materials excluding the text book are distributed
in MyCourses. These include lecture slides, additional readings, example spreadsheet implementations of mathematical models and assigments.
Course Homepage (valid 01.08.2018-31.07.2020):
Prerequisites (valid 01.08.2018-31.07.2020):
The course ”30A02000 Tilastotieteen perusteet" (Introduction to Statistics) and at least one of the courses ”30A03000 Talousmatematiikan perusteet" (Introduction to Business Mathematics) and ”30C00600 Tilastotieteen jatkokurssi" (Continuation course in statistics). The course “27C01000 Business Decisions 1” is highly recommended. Equivalent studies in mathematics/statistics from another school/university are also acceptable.
Grading Scale (valid 01.08.2018-31.07.2020):
Registration for Courses (valid 01.08.2018-31.07.2020):
Further Information (valid 01.08.2018-31.07.2020):
A maximum of 80 students will be admitted to the course. Priority will be given to Aalto ISM MSc students and students with strong analytical skills (see prerequisites).
Additional information for the course (applies in this implementation):
Register to course in MyCourses.
Details on the schedule (applies in this implementation):
There are two sessions per week both lasting 3-4
hours. From each session about 1 hour is dedicated for working on the
assignments with the teacher present to offer guidance.
Week 2: Introduction, Review of probability, Monte Carlo simulation
Week 3: Decision making under uncertainty: Decision trees, Value-of-information, assessment of subjective probabilities, biases in probability estimation
Week 4: Modelling risk preferences: Expected Utility Theory (EUT), Stochastic Dominance, Risk measures
Week 5: Multi-objective decision making: Multi-attribute utility theory (MAUT), and the Analytic Hierarchy Process (AHP).
Week 6: Supporting decision making with optimization: Multi-objective and stochastic models