Postgraduate Course: Industrial Analytics (CMSE11352)
Course Outline
| School | Business School |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 15 |
ECTS Credits | 7.5 |
| Summary | This is an option course for the MSc in Business Analytics programme. The course will provide students with the foundations of industrial analytics. In the era of big data, the importance of industrial analysis skills for graduates in business can hardly be overstated. |
| Course description |
Industry analysis has a long history which can be traced back from Michael Porter's five-force analysis. Nowadays, this practice is widely adopted in a lot of business activities including business consultancy, strategic analysis, etc. This course aims at training students in the field of industrial analytics using a variety of methodologies. To be more specific, this course covers the typical theories of industrial organisation along with a range of techniques to analyse an industry, assess business models, identify competition patterns, and propose appropriate strategies for high-level managers.
The objective of this course is to enhance students¿ understanding of the importance of adopting a series of sound methodological steps in industrial analytics and to provide them with a variety of modelling and analysis techniques along with hands-on experience in using them. The course provides opportunities for students to learn from each other, from practitioners in the field, and from the latest theoretical and applied research in the field. The course will require students to work in groups on realistic projects in different business settings involving industry analysis and profiling, business models assessment, identification of competition patterns, and design of appropriate strategies for high-level managers, and to present their work to the rest of the class and to an external panel when the projects are supplied by industry.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2017/18, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
150
(
Lecture Hours 20,
Seminar/Tutorial Hours 10,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
117 )
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| Assessment (Further Info) |
Written Exam
30 %,
Coursework
70 %,
Practical Exam
0 %
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| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Discuss the concept and methods of industrial analytics using the proper terminology
- Identify and properly state research problems related to industrial analytics in different business settings
- Identify and properly state research problems related to industrial analytics in different business settings
- Formulate managerial guidelines and make recommendations
- Communicate solutions and strategies effectively and efficiently to a critical audience
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Reading List
SUGGESTION:
Lynne Pepall, Dan Richards and George Norman, Industrial Organisation: Contemporary Theory and Empirical Applications. 5th Edition, 2013, ISBN-13: 978-1-118-25030-3
Recommended Reading
SUGGESTION:
Jean Tirole, The Theory of Industrial Organization, 1988, ISBN-13: 978-0262200714
Don E.Waldman, Elizabeth J. Jensen, "Industrial Organization: Theory and Practice", 2013, ISBN-13: 978-1292039985
Oz Shy, "Industrial Organization: Theory and Application", 1996, ISBN-13: 978-0262691796
Geoff Harcourt, Clive W. J. Granger, "Empirical Modeling in Economics: Specification and Evaluation", 1999, ISBN-13: 978-0521778251
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | BA-IA |
Contacts
| Course organiser | Dr Tong Wang
Tel: (0131 6)51 5551
Email: |
Course secretary | Mr Peter Newcombe
Tel: (0131 6)51 3013
Email: |
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