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Objectives and competences

The objective of this course is to give students knowledge of the principal decision making models and systems and to qualify them for objective, responsible, and rational decision making.

Content (Syllabus outline)

• Introduction: definition of decision making, decision making process, individual-based decision making, group-based decision making, measuring benefits, measurement scales. • Impact of IT on decision making process: decision making methods and procedures, parameters binding and non-binding decision making methods, decision trees, interest reconciliation methods. • Multi-parameter decision making and decision support information systems: selecting criteria sets, goodness function definition, multi-parameter goodness function, partial goodness function combination method, direct goodness function definition method, risk-based decision making. • Group-based decision making: advanced methods of group-based decision making, interest reconciliation. • Sociological and psychological aspects of decision making. • Information for business decision making: sources of information, information management, determining information need of an organisation, unstructured data in decision making. • Information retrieval methods for decision making: decision making data identification, data collection, data processing, data and information retrieval techniques • Intelligent data analysis: knowledge discovery in data, data mining, basic machine learning methods. • Business simulation and optimization methods.

Learning and teaching methods

lectures, case studies, lab work, individual work.

Intended learning outcomes - knowledge and understanding

On completion of this course the student will be able to demonstrate knowledge and understanding of decision making methods and models in real world cases, analyse, design and perform information retrieval process for the needs of decision making, relate decision making processes in organisations with their organisational processes and management, objectively evaluate the benefits of decisions and their impact on the further decision making process.

Intended learning outcomes - transferable/key skills and other attributes

Use of information technology: use of software tools for information retrieval and management and decision support systems. Organisation skills: organisation of decision making process in relation to organisational and management processes in an organisation. Problem solving: systematic approach to collecting appropriate information and decision making for an arbitrary decision task. Working in a group: group-based decision making.

Readings

• M. Bohanec: Odločanje in modeli, DMFA-založništvo, 2007. • G. A. Klein, J. Orasanu, R. Calderwood: Decision Making in Action: Models and Methods, Ablex Publishing, 1993. • M. Wisniewski: Quantitative Methods for Decision Makers, 4th edition, Prentice Hall, London, 2006. • P. F. Drucker, J. Hammond, R. Keeney, H. Raiffa, A.M. Hayashi: Harvard Business Review on Decision Making, Harvard Business School Press, Boston, MA, 2001.

Prerequisits

Basic knowledge of information systems and electronic communication, knowledge of information systems design and databases is recommended.

  • red. prof. dr. VILI PODGORELEC, univ. dipl. inž. rač. in inf.

  • 1st midterm examination: 25
  • 2nd midterm examination: 25
  • work in computational laboratory: 20
  • Project work: 20
  • quizzes: 10

  • : 45
  • : 30
  • : 105

  • Slovenian
  • Slovenian

  • INFORMATICS AND DATA TECHNOLOGIES (INFORMATION SYSTEMS) - 3rd