Decision support systems in administration2018

2031 Decision support systems in administration

  • Study programme and level: Master’s Degree Programme Administration- Public sector governance 2nd Cycle
  • 2nd year
  • 6 ECTS
  • Course type: Elective
  • Lectures: 21
  • Seminar: 11
  • Other forms of study: 88
  • Individual work: 60
  • Lecturer: Ljupčo Todorovski, PhD

1. Prerequisits

No prerequisits.

2. Content (Syllabus outline) 

  • Introduction: decision theory, decision making and decision making process
  • Decision support
  • Decision models
  • Modeling methods and techniques with focus on multi-attribute decision models
  • Software for building decision models and decision support
  • Examples of decision support models and their practical use

3. Readings

  • Clemen, RT and Reilly, T (2014) Making Hard Decisions: An Introduction to Decision Analysis. Third Edition. Duxbury, USA: South-Western Cengage Learning.
  • French, S. (1988) Decision Theory: An Introduction to the Mathematics of Rationality. London, UK: Ellis Horwood.
  • Turban, E, Sharda, R, Delen, D (2011) Decision Support and Business Intelligence. US, Boston: Pearson.

4. Objectives and competences

Objectives – student knows how to:

  • analyze decisions processes in public administration and discover their specific properties
  • use methods, techniques and systems for support of complex decision processes and building decision models
  • estimate, check, evaluate and compare the utility and suitability of methods, techniques and systems for decision support in public administration
  • analyze and compare the results of using decision models in a given/specific public administration context

Competences:

  • the ability to identify opportunities for using decision theory and decision support in the public administration domain
  • the ability to analyze real-word decision problems in public administration and design of the appropriate decision models
  • the ability to use decision models for making and analysis of decisions as well as analysis of different scenarios

5. Intended learning outcomes

Student:

  • knows, understands and is able to use methods for analysis of decision problems and processes in public administration
  • knows, understands and is able to use appropriate methods and techniques for building multi-criteria decision models
  • knows and is able to use software for formalization and use of decision models
  • knows, understands and is able to use what-if analysis, sensitivity analysis and option evaluation for analysis of decisions obtained with a decision model

6. Learning and teaching methods

  • preparations for lectures
  • lecture
  • preparations for seminars
  • seminars
  • study consultation
  • seminar paper

7. Assessment

  • Seminar work and presentation 70 %
  • Written and/or Oral exam 30 %

8. Lecturer's references

  • Erman, N., Todorovski, L. (2015) The effects of measurement error in case of scientific network analysis. Scientometrics, let. 104, št. 2, str. 453-473.
  • Simidjievski, N., Todorovski, L., Džeroski, S. (2015) Predicting long-term population dynamics with bagging and boosting of process-based models. Expert systems with applications, let. 42, št. 22, str. 8484-8496.
  • Erman, N., Todorovski, L. (2011) Collaborative network analysis of two egovernment conferences : are we building a community? Electronic journal of e-government, let. 9, št. 2, str. 141-151.
  • Colombo, C., Kunstelj, M., Molinari, F., Todorovski, L. (2011). Participatory policy process design: lessons learned from three European regions. Journal of Balkan & Near Eastern studies, let. 13, št. 1, str. 117-139.