Master
2023/2024
Decision Analysis
Type:
Compulsory course (Business Analytics and Big Data Systems)
Area of studies:
Business Informatics
Delivered by:
Department of Mathematics
Where:
Graduate School of Business
When:
1 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Master’s programme:
Business Analytics and Big Data Systems
Language:
English
ECTS credits:
6
Contact hours:
48
Course Syllabus
Abstract
The course contains the main topics of decision analysis in the deterministic framework widely used in management. Topics include uni- and multicriterial choice models, models of personnel management, models of fair division, network analysis, and firm performance analysis. It also includes data analysis models used in making business and political decisions. All models are widely illustrated with real-life examples.
Learning Objectives
- Study of the theoretical foundations of modern models of individual, multi-criteria and collective decision-making in economics and business
- Study of the principles of construction, analysis and evaluation of formalized mathematical models describing real situations
- Mastering the basic models of multi-criteria, individual and collective decision-making, building compliance, assessing influence in groups and evaluating the effectiveness of companies
Expected Learning Outcomes
- Apply different methods for solving multicriteria problems
- Evaluate the efficiency of companies taking into account many factors
- Apply the Gale-Shapley algorithm to find a stable matching
- Identify the criterion type (quantitative or qualitative)
- Evaluate the impact of group members with assistance of influence indices (Banzaf, Johnston, Shapley-Shubik, Digen-Pakel, alpha-indices)
Course Contents
- Uni- and multicriterial choice models
- Matchings
- Fair division
- Network analysis
- Data analysis in business
- Efficiency of firms
- Political decisions
- Power in groups
Bibliography
Recommended Core Bibliography
- Aizerman, M. A. (1985). New Problems in the General Choice Theory. Working Papers.
- Aleskerov, F., Meshcheryakova, N., & Shvydun, S. (2016). Centrality measures in networks based on nodes attributes, long-range interactions and group influence.
- Aleskerov, F., Meshcheryakova, N., Rezyapova, A., & Shvydun, S. (2018). Network analysis of international migration.
- Y. Ilker Topcu, Özay Özaydın, Özgür Kabak, & Şule Önsel Ekici. (2021). Multiple Criteria Decision Making : Beyond the Information Age (Vol. 1st ed. 2021). Springer.
Recommended Additional Bibliography
- Gregory S. Parnell, Terry Bresnick, M., Steven N. Tani, P., & Eric R. Johnson, P. (2012). Handbook of Decision Analysis. Wiley.
- Kenneth D. Lawrence, & Gary Kleinman. (2010). Applications in Multi-criteria Decision Making, Data Envelopment Analysis, and Finance: Vol. 1st ed. Emerald Group Publishing Limited.
- Sherman, E. H. (2015). A Manager’s Guide to Financial Analysis : Powerful Tools for Analyzing the Numbers and Making the Best Decisions for Your Business: Vol. Sixth edition. AMA Self-Study.
- Ward Edwards, Ralph F. Miles Jr, & Detlof von Winterfeldt. (2007). Advances in Decision Analysis : From Foundations to Applications. Cambridge University Press.
- Zopounidis, C., & Doumpos, M. (2017). Multiple Criteria Decision Making : Applications in Management and Engineering. Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1231843