- UCAS course code
- N201
- UCAS institution code
- M20
Course unit details:
Business Decision Analytics
Unit code | BMAN31152 |
---|---|
Credit rating | 20 |
Unit level | Level 3 |
Teaching period(s) | Semester 2 |
Available as a free choice unit? | No |
Overview
The course covers a variety of decision analysis / analytics techniques and processes widely used in business and management to enhance productivity and performance, including
- Linear Programming: formulation & graphical solution, simplex and dual-simplex methods & Excel Solvers, sensitivity analysis, applications
- Transportation algorithms and software (TORA software)
- Integer programming and software (Excel Solvers and TORA software)
- Decision analysis under uncertainty and risk, Bayesian or multiple stage decision making model and method
- Modelling and analysis of decision maker's attitudes towards risk, preferences and values
- Multiple criteria decision models, methods, processes, tools and decision support systems
- Introduction to game theory for decision making under competition, Markov chain process and time-dependent decision making under risk
Pre/co-requisites
Unit title | Unit code | Requirement type | Description |
---|---|---|---|
Quantitative Methods for Accounting and Finance | BMAN10750 | Pre-Requisite | Compulsory |
Quantitative Methods for Business and Management | BMAN10960 | Pre-Requisite | Compulsory |
Pre-requisite course units have to be passed by 40% or above at the first attempt unless a higher percentage is indicated within this course outline.
Pre-requisites: BMAN10960 Quantitative Methods for Business & Management or BMAN10750 Quantitative Methods for A+F. For BSc Mathematics with Business and Management, BSc Mathematics with Finance, BSc Mathematics and Statistics no pre- requisites are required.
International exchange students may be permitted to take this course unit provided that the equivalent pre- requisite courses have been taken and checked by the course co-ordinator.
Aims
To introduce modelling and optimisation methods to address decision problems in resource management. To introduce the concepts, processes, models, methods and software tools of decision analysis with real-world application examples for supporting better operational, tactical and strategic decision making in business and management.
Learning outcomes
At the end of the course students should be able to:
- recognise a variety of management decision problems addressed by different linear modelling techniques in operational research
- apply a range of specific and generic linear optimisation methods and tools for solving the problems to achieve the effective and efficient use of resources
- conduct sensitivity analysis to support managerial decision making
- describe and apply the decision analysis models and methods covered
- consider different approaches to particular decision problems and identify the assumptions, advantages and disadvantages of each approach
- discuss how computer software tools are used to implement the models and methods, and how they are used in real-world decision problems in business and management
Teaching and learning methods
Four-hour lecture per week (see detailed schedule below) for 10 weeks, directed reading and computer based support
Lecture hours: 40
Private study: 160
Total study hours: 200
Total study hours: 200 hours split between lectures, self-study and preparation for classes, and examinations.
Informal Contact Methods
1. Office Hours: 4:00pm-6:00pm Monday
2. Online Learning Activities (blogs, papers, discussions, self-assessment questions and answers)
3. Drop in Surgeries (extra help sessions for students on material they may be struggling with)
Assessment methods
Examination (100%)
Feedback methods
• Informal advice and discussion during lectures and office hours.
• Written and/or verbal comments on assessed or non-assessed coursework.
• Solution files to some exercises are published on Blackboard.
• Responses to student questions via Blackboard or emails.
• Generic feedback posted on Blackboard regarding overall examination performance.
In addition to the central unit evaluation questionnaire, student are encouraged to give feedback through emails and conversations at anytime, and questionnaire near the end of the semester
Recommended reading
Taha, H. A. (2017), Operations Research, An Introduction, Prentice-Hall Inc. 10th Edition, Precinct. Earlier or later editions are fine. Search topics in Index of the book to find the right pages to read about the relevant topics.
Hillier, F.S. & Lieberman, G.J. (2015) Introduction to Operations Research 10th Edition, McGraw-Hill, Precinct. Earlier or later editions are fine. Search topics in Index of the book to find the right pages to read about the relevant topics.
Belton, V., Stewart, T. J. (2002), Multiple Criteria Decision Analysis -An Integrated Approach. Kluwer Academic Publishers: Dordrecht, ISBN 0-7923-7505-X.
Keeney, R.L. and Raiffa, H. (1993), Decision with Multiple Objectives: Preference and Value Tradeoffs. Cambridge University Press.
Sen, P. and Yang, J. B. (1998), Multiple Criteria Decision Support in Engineering Design, Springer. All libraries
Study hours
Scheduled activity hours | |
---|---|
Assessment written exam | 3 |
Lectures | 40 |
Independent study hours | |
---|---|
Independent study | 160 |
Teaching staff
Staff member | Role |
---|---|
Dong Xu | Unit coordinator |
Additional notes
Other staff involved:
Pre-requisite course units have to be passed by 40% or above at the first attempt unless a higher percentage is indicated within this course outline.
Pre-requisites: BMAN10960 Quantitative Methods for Business & Management or BMAN10750 Quantitative Methods for A+F. For BSc Mathematics with Business and Management, BSc Mathematics with Finance, BSc Mathematics and Statistics no pre- requisites are required.
Co-requisites: None
Dependent courses: N/A
International exchange students may be permitted to take this course unit provided that the equivalent pre- requisite courses have been taken and checked by the course co-ordinator.
Programme Restrictions: This course is available to all students registered under the BSc programmes at MBS, provided that they meet the requirements set out in the course pre-requisites. Students for the following programmes can take this course: BSc Mathematics with Business and Management, BSc Mathematics with Finance, BSc Mathematics and Statistics; students from other university programmes may be allowed to take this course by discussion with the course coordinator.
For Academic Year 2023/24
Updated: May 2023
Approved by: March UG Committee