GUIDELINES FOR FULL COURSE OUTLINES

2020/21

 

THE UNIVERSITY OF MANCHESTER

ALLIANCE MANCHESTER BUSINESS SCHOOL

Academic Year          2020/21

Semester                    Semester 2

Course Unit Code       BMAN60092

Course Unit Title        Risk, Performance and Decision Analysis

Credit Rating               15

Year                                 PGT course unit

 

Course Coordinator and contact details

Prof Jian-Bo Yang (JBY)

Office Room: 3.056 in AMBS Building

Tel: 0161 306 3427

Email: [email protected]

Office Hours: Monday 9:00am - 11:00am 

 

Other Staff Involved and contact details

Prof. Dong-Ling Xu (DLX)

Office Room: AMBS 3.070 in AMBS Building

Tel: 0161 275 0941

Email: [email protected]   

Dr Ting Wu (TW)

Email: [email protected] 

 

Programme Restrictions

MSc Business Analytics: Operational Research and Risk Analysis,

MSc Computer Science and IT Management

 

Pre-requisites

BMAN60101 Mathematical Programming and Optimisation

Co-requisites

N/A

 

Dependent course units

N/A

 

Aims

This course unit covers risk, performance and decision modelling and analysis, including risk modelling and assessment, both single and multiple criteria decision modelling and analysis, data envelopment analysis and multiple objective optimization for performance improvement. Emphasis will be placed on the integrated applications of these methods and tools to performance and efficiency analysis and planning. The aim is to familiarise students with the applications of decision modelling and performance analysis methodologies.

 

Learning Outcomes

At the end of the course unit students should be familiar with concepts, methods and tools for decision tree analysis, multiple criteria decision analysis, data envelopment analysis and multiple objective optimisation, which they can apply to support decision making and deal with performance assessment and efficiency analysis problems. They should also be able to use appropriate software tools such as Excel and IDS Multicriteria Assessor.

 

Employability

The course equips students with skills of using data and analytical models to analyse risk, performance and business decision at the levels of product, process, organisation or system in general. Students will also be taught how to use software to conduct different kinds of analysis. These skills can help students to be employable in a wide range of sectors wherever data and decision analyses are needed.

 

Social Responsibility

Students will be taught how multiple criteria, such as economy, environment, culture, benefit, cost, quality, sustainability, human wellbeing, etc., should be balanced and how multiple stakeholders’ preferences and interests should be taken account in analytical modelling and decision making. They will also be taught how to make the best use of resources in most cost effective way by optimizing quality, sustainability, human wellbeing, etc. at minimum cost and minimum consumption of resources.

Methods of Delivery

Lectures/Workshops

5 x 4 hour online lectures and group presentations

5 x 2 hour tutorials

 

Private Study

120

 

Total Study Hours

150

 

Timetable

Semester 2 teaching period and revision/reading/examinations:			Semester 2 starts 8 Feb. 2021 Easter break starts 26 March 2021 Easter break ends 12 April 2021 Semester 2 exams 17 May – 11 June 2020 Semester 2 ends 11 June 2020
Lectures:	Mon. Fri.	9-11am 10am-12pm	Online. Video clips available from blackboard Online. Video clips available from blackboard
Seminars:			Please see the weekly schedule and your timetable. You should be allocated to one of the following time slots. Please keep to your slot as much as possible. All seminars will be available through Zoom online at the scheduled time. We believe that it is more effective to attend your seminar online than to attend it in classroom, as you can see more clearly through the Share Screen function of Zoom, and you can compile your questions before the seminar and post them through the Chat function.

 

Course Code	Course Unit Name	Zoom Link	Day	Time		Room	Group	AMBS Weeks
BMAN60092	Risk, Performance and Decision Analysis	TW & JBY	Mon	3pm	5pm	3.014/A/B	A	weeks 2 - 6
BMAN60092	Risk, Performance and Decision Analysis	TW & JBY	Tue	1pm	3pm	3.014/A/B	B	weeks 2 - 6
BMAN60092	Risk, Performance and Decision Analysis	TW & JBY	Tue	3:30 pm	5:30 pm	3.014/A/B	C	weeks 2 - 6
BMAN60092	Risk, Performance and Decision Analysis	TW & JBY	Wed	10 am	12 pm	Online	D	weeks 2 - 6

Attendance of Lectures and Seminars

Lecture (through downloading) and seminar attendance will be monitored and poor attendance will be dealt with based on the AMBS policies.

 

Syllabus and Teaching Schedule

Week	Date	Lecturer	Topics	Readings
1	08/02/21	JBY	Decision Tree Analysis and Utility – Models, Methods and Concepts	Hillier & Lieberman
1	12/02/21	JBY	Utility Theory and Bayesian Decision Theory – Concepts and methods	Hillier & Lieberman
2	15/02/21	JBY	Performance Assessment and Multiple Criteria Decision Analysis (MCDA)	Keeney & Raiffa  IDS, Excel, etc.
2	19/02/21	JBY	MCDA – Models and Preference Modelling	Keeney & Raiffa
3	22/02/21	JBY	MCDA – Process and Aggregation Methods	Belton and Stewart
3	26/02/21	JBY	MCDA – Aggregation Methods, Tools and Applications	Sen & Yang
4	01/03/21	JBY	Data Envelopment Analysis – Concepts and Basic Models	Cooper, Seiford and Tone
4	05/03/21	JBY	Data Envelopment Analysis – Models, Methods, Tools and Applications	Cooper, Seiford and Tone
5	08/03/21	JBY	Multiple Objective Linear Programming – Concepts and Models	Liu, Yang and Whidborne
5	12/03/21	JBY	Multiple Objective Linear Programming–Methods & Applications	Liu, Yang and Whidborne

 

Reading List

· 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.

· Keeney, R.L. and Raiffa, H. (1993), Decision with Multiple Objectives: Preference and Value Tradeoffs. Cambridge University Press.

· Saaty, T. L. (1988), The Analytic Hierarchy Process. University of Pittsburgh, 1988.

· Cooper, W. W, Seiford, L. M. and Tone, K. (2007), Data Envelopment analysis: a comprehensive text with models, applications, references and DEA Solver software. 2nd edition, Springer.

· Liu G. P., Yang J. B. and Whidborne, J. F. (2002), Multiobjective Optimisation and Control. Engineering Systems Modelling and Control Series, Research Studies Press Limited, Baldock, Hertfordshire, England.

· Sen, P. and Yang, J. B. (1998), Multiple Criteria Decision Support in Engineering Design. Springer. London, ISBN 3540199322.

· Yang, J. B. (1999), Gradient projection and local region search for multiobjective optimisation, European Journal of Operational Research, Vol.112, No.2, pp.432-459.

· Yang, J. B. (2000), Minimax reference point approach and its application for multiobjective optimisation, European Journal of Operational Research, Vol.126, No.3, pp.90-105.

· Yang, J. B. (2001), Rule and utility based evidential reasoning approach for multiple attribute decision analysis under uncertainty, European Journal of Operational Research, Vol. 131, No.1, pp.31-61.

· Yang, J. B. and Xu, D. L. (2002), On the evidential reasoning algorithm for multi-attribute decision analysis under uncertainty, IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans, Vol.32, No.3, pp.289-304.

· Yang, J. B. and Li, D. (2002), Normal vector identification and interactive tradeoff analysis using minimax formulation in multiobjective optimisation, IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans, Vol.32, No.3, pp.305-319.

· Xu, D. L. and Yang, J. B. (2003), Intelligent decision system for self-assessment, Journal of Multiple Criteria Decision Analysis, Vol.12, 43-60.

· Xu, D. L., McCarthy, G. and Yang, J. B. (2006), Intelligent decision system and its application in business innovative capability assessment, Decision Support Systems, Vol.42, pp.664-673.

· Yang, J. B., Wang, Y. M., Xu, D. L. and Chin, K. S. (2006), The evidential reasoning approach for MCDA under both probabilistic and fuzzy uncertainties, European Journal of Operational Research, Vol. 171, No.1, pp.309-343.

· Yang, J. B., Wong, Y. H., Xu, D. L. and Stewart, T. J. (2009), Integrating DEA-oriented performance assessment and target setting using interactive MCDA methods, European Journal of Operational Research, Vol.195, pp.205–222.

· Yang, J. B., Wong, Y. H., Xu, D. L., Liu, X. B. and Steuer, R. E. (2010), Integrated bank performance assessment and management planning using hybrid minimax reference point – DEA approach, European Journal of Operational Research, Vol.207, pp.1506–1518.

· Yang, J. B., Xu, D. L., Xie, X. L. and Maddulapalli, A.K. (2011), Multicriteria evidential reasoning decision modelling and analysis – prioritising voices of customer, Journal of the Operational Research Society, Vol.62, pp.1638–1654.

· Yang, J. B., Xu, D. L. and Yang, S. L. (2012), Integrated efficiency and trade-off analyses using a DEA-oriented interactive minimax reference point approach, Computers & Operations Research, Vol.39, pp. 1062-1073.

· Yang, J. B. and Xu, D. L. (2013), Evidential reasoning rule for evidence combination, Artificial Intelligence, Vol.205, pp.1-29, 2013.

· Yang, J. B. and Xu, D. L. (2014), Interactive minimax optimisation for integrated performance analysis and resource planning, Computers & Operations Research, Vol.46, pp.78–90.

Assessment

70% examination 2 hour closed book, in the semester 2 examination period.

 

30% Group Project Report and Presentation. Group presentations will be on Friday 19^th March 2021. Deadline for submitting both group PPT files and group reports to Blackboard/Turnitin will be before 3pm on Friday 19^th March 2021. 

Plagiarism

Please refer to the “Penalty and Plagiarism.docx” document on Blackboard.

Resits

Resit will be assessed by a closed book exam only.

Marking Process

The School follows a fair, rigorous and transparent marking process for all summative work and makes available the adapted grade descriptors for your course unit assessment.

Feedback  

Informal advice and discussion will be given during a lecture and workshop. Written or verbal comments will be provided after students have given a group presentation. Generic feedback will be posted on Blackboard regarding overall examination performance.

 

Timescales for delivery of feedback to students :

 

Feedback on Coursework

Feedback for all assessed coursework will be available from 21^st May 2021.

 

Feedback on Exams

Students should not expect to find detailed written comments on an exam script. Any comments on the exam script are predominantly part of the marking process. Commentary on exam performance is in the generic feedback published to students on the course via Blackboard. The generic feedback will normally be posted within 20 working days after the exam.

 

Methods of Feedback from Students/Course Unit Survey

The course will be evaluated by means of an online feedback questionnaire completed by students on completion of the course.