MEng Computer Science with Industrial Experience / Course details
Year of entry: 2021
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Course unit details:
Decision Behaviour, Analysis and Support
|Unit level||FHEQ level 7 – master's degree or fourth year of an integrated master's degree|
|Teaching period(s)||Semester 1|
|Offered by||Alliance Manchester Business School|
|Available as a free choice unit?||No|
Taking decisions and enhancing decision making ability are important skills to have. Operational, tactical and strategic decisions however, are often complex in organisational and policy making contexts. This course provides a better understanding of soundly-based approaches for structuring and analysing decisions in the face of uncertainty and conflicting objectives (Decision Analysis). It explains how decisions are taken (Decision Behaviour) and how we can improve decision making capabilities at individual, group, organisational and societal levels (Decision Support).
The aim of this module is to provide a state-of-the-art overview on decision making in a variety of organisational settings (e.g. private, public and not-for-profit sectors). It explores how decision analysis and decision aiding technologies can help individuals, groups and organisations make better decisions. Drawing from decision theory, behavioural and psychological studies, information systems, artificial intelligence, operational research and organisational studies, the course highlights the multi-faceted challenges of decision making. The main emphasis is on prescriptive theories of decision making.
In summary, you will gain an understanding of the capabilities and types of decision frameworks and decision aiding technologies used in businesses and their impact on business performance and competiveness. You will develop analytical skills for structuring decisions and developing decision models by incorporating data from multiple sources and judgments from experts and stakeholders. You will use decision analytics tools to support your decision analysis and communicate the results.
By the end of the course you will:
- Become aware of behavioural, normative and prescriptive models of decision making
- Develop content and process skills for modelling and analysing critical decisions in prescriptive decision support
- Understand a range of modelling frameworks, methods and tools for designing prescriptive decision processes and facilitating business decisions
- Become aware of emerging trends in decision support technology
Teaching and learning methods
Formal Contact Methods
Minimum Contact hours: 20
Delivery format: Lecture and Workshops
Project project presentations: 30%
Examination: 70% (2 hours)
Informal advice and discussion during a lecture, seminar, workshop or lab.
Specific course related feedback sessions.
Written and/or verbal comments on assessed or non-assessed coursework.
Written and/or verbal comments after students have given a group or individual presentation.
Generic feedback posted on Blackboard regarding overall examination performance.
The main course text is:
Simon French, Nadia Papamichail, John Maule. ‘Decision Making: Behaviour, Analysis and Support’ Cambridge: Cambridge University Press, 2009
Another suitable text is:
R. Sharda, D. Delen. and E. Turban. ‘Business Intelligence, Analytics and Data Science- A Managerial Perspective’ Upper Saddle River, New Jersey: Prentice Hall, 2017.
|Scheduled activity hours|
|Assessment written exam||2|
|Independent study hours|
|Konstantinia Papamichail||Unit coordinator|
Informal Contact Method
Drop in Surgeries (extra help sessions for students on material they may be struggling with)