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Unit information: Management Science in 2020/21

Unit name Management Science
Unit code EFIM20005
Credit points 20
Level of study I/5
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Holland
Open unit status Not open
Pre-requisites

Mathematical and Statistical Methods 1 (EFIM10008) or Quantitative Analysis in Management (EFIM10014)

Co-requisites

None

School/department School of Management
Faculty Faculty of Social Sciences and Law

Description

Management Science is concerned with the application of quantitative techniques and the modelling of operational and strategic problems to aid management decision-making and planning both in the private and public sectors. Management scientists need to have a good awareness of the ways in which organisations operate, whether for-profit or in the public sector, and to understand the formulation and application of tools which aid managers in developing a more efficient and successful operation.

The term Management Science is often used synonymously with Operational Research, hence the acronym MS/OR. Applications of models typically relate to three functional areas of management: Operations Management, Project Management and, in recent decades, Strategic Management. Techniques which will be introduced include linear programming, project network analysis, decision trees and simulation. All concepts and techniques are illustrated using examples often derived from case studies. Appropriate software will be introduced for simulation. The practice of this methodology has been revolutionised by advances in computer technology and its application offers one of the most exciting developments for dealing with management problems, particularly those surrounding queueing and congestion issues.

Intended learning outcomes

On successful completion of this unit, students will be able to:

  1. Understand and apply the basic concepts, techniques and theories of management science.
  2. Understand applications in operations management, project management and strategic management and apply them to the management aspects of these functional areas.
  3. Demonstrate understanding of commonly-applied management science techniques, including: linear programming, simulation, project network analysis and decision trees.
  4. Understand the circumstances in which each technique might be applied and, further, the occasions when a particular approach might not be the appropriate one.

Teaching details

Teaching will be delivered through a combination of synchronous and asynchronous sessions including lectures, tutorials, drop-in sessions, discussion boards and other online learning opportunities.

Assessment Details

MCQ: 20% , Test 20% and course work report 60% (approx 1500 words)

Reading and References

  • Anderson, D.R., Sweeney D.J., Williams, T.A., Wisniewski M. and Pierron X., 3rd Ed, (2017). An Introduction to Management Science: Quantitative Approaches to Decision-Making. Cengage Learning, Andover.
  • Taylor, B. (2013). Introduction to Management Science. 11th Ed, Pearson.
  • Daellenbach, H.G. and McNickle, D.C. (2005) Management Science: Decision Making through Systems Thinking. Palgrave.
  • Kallrath, J and Wilson, JM (1997) Business Optimisation Using Mathematical Programming. Macmillan.
  • Brailsford S, Churilov L and Dangerfield B (Eds ) (2014) Discrete Event Simulation and System Dynamics for Management Decision Making, Wiley.
  • Pidd, M. (2012). Tools for Thinking: Modelling in Management Science. 3rd Ed., Wiley.

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