Undergraduate Course: Management Science and Information Systems (BUST08007)
Course Outline
| School | Business School |
College | College of Humanities and Social Science |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Credits | 20 |
| Home subject area | Business Studies |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | This course demonstrates how information systems and decision support models can be effectively integrated to analyse and solve business problems. The course is taught by means of lectures, computer labs, tutorials, and group activities. Lectures cover topics in information systems and data management, such as database design and SQL; as well as a number of management science techniques, such as linear programming and decision analysis. Computer labs let students acquire the skills that are necessary to apply these techniques in practice by using state of the art software packages. Tutorials provide an understanding of the theory underpinning the aforementioned techniques. Group activities are designed to let student experience challenges and opportunities that stem from the integration of decision support models and information systems.
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Information for Visiting Students
| Pre-requisites | Visiting students should usually have at least 1 introductory level Business Studies course at grade B or above (or be predicted to obtain this) for entry to this course. We will only consider University/College level courses. |
| Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
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| Delivery period: 2014/15 Semester 2, Available to all students (SV1)
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Learn enabled: Yes |
Quota: None |
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Web Timetable |
Web Timetable |
| Class Delivery Information |
Plus tutorials for 8 weeks; five tutorials are 1 hour classes and 3 are two-hour computer lab assessed exercises. Please sign up for tutorial groups on the course website on Learn. |
| Course Start Date |
12/01/2015 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 5,
Summative Assessment Hours 8,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
163 )
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| Additional Notes |
Coursework: 30% individual lab assessments; 30% group essay (1500 words; 25% essay 5% peer WebPA)
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| Breakdown of Assessment Methods (Further Info) |
Written Exam
40 %,
Coursework
30 %,
Practical Exam
30 %
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| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S2 (April/May) | | 2:00 | | | Resit Exam Diet (August) | | 2:00 | |
Summary of Intended Learning Outcomes
COURSE OBJECTIVES
The goal of this course is to demonstrate how information systems and decision support models can be used in synergy to address business problems.
More specifically, our aim is to:
1. illustrate how data can be modelled, stored and retrieved in order to effectively support decision making;
2. introduce a range of quantitative approach to decision making
3. demonstrate how information systems and decision support systems can be integrated to ensure effective decision support.
LEARNING OUTCOMES
On completion of this course students should be able to
Academic Knowledge
1. discuss state of the art techniques for data modelling, storage and retrieval in database management systems
2. discuss the key elements of a linear programming model and its underling assumptions; illustrate possible solution methods for solving linear programs
3. discuss selected approaches to decision making under uncertainty and illustrate possible solution methods
4. discuss selected techniques in project management
5. discuss the key steps that should be executed to takle a management decision problem
Intellectual Skills
1. design a database suitable for a given dataset
2. build a decision support model for a given management decision problem
3. integrate a database and a decision support model to derive management recommendations for a given management decision problem
4. identify what combination techniques covered is most suitable to address a management decision problem
Professional Skills/Subject Specific/Practical Skills
1. model a given set of data using the relational modelling paradigm
2. store and retrieve data from a database management system
3. build, solve and analyse linear programming or decision analysis models in Excel
4. use Gant Project to schedule project activities
Transferable skills
1. demonstrate report writing skills
2. demonstrate problem analysis and problem solving skills
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Assessment Information
Your work will be assessed in three ways:
1. direct assessment of the work you complete within computer sessions (30% of the Final Mark; each computer lab contributing to 10% of the Final Mark);
2. essay of 1500 words in which each group of 4 or 5 students report their findings stemming from the analysis of a management decision problem (25% of the Final Mark); peer assessment from other group members carried out via WebPA (5% of the Final Mark);
3. a degree examination (40% of the Final Mark).
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Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
1. Data Management - database design, Structured Query Language (SQL);
2. Linear Programming - graphical solution, simplex method, sensitivity analysis, applications of linear programming;
3. Project Management - critical path analysis, monitoring progress, cost-time trade-offs;
4. Decision Analysis - decision criteria, use of information.
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| Transferable skills |
Transferable skills
1. demonstrate report writing skills
2. demonstrate problem analysis and problem solving skills
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| Reading list |
There is no set textbook, but the following books will prove useful:
1. David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, R. Kipp Martin, (2008) An Introduction to Management Science: Quantitative Approaches to Decision Making (12th ed.), West Publishing, ISBN 0324399804. (Note that other editions of this text have similar content.)
2. Bernard W. Taylor, (2009) Introduction to Management Science (10th ed.), Pearson Education, ISBN 0132371197.
3. Frederick S. Hillier and Gerald J. Lieberman, Introduction to Operations Research (6th ed.), McGraw-Hill, ISBN 0071139893.
4. Jeffrey H. Moore and Larry R. Weatherford, (2001) Decision Modeling with Microsoft Excel (6th ed.), Prentice Hall, ISBN 013017789x.
5. Wayne L. Winston, (1997) Operations Research Applications and Algorithms (3rd ed.), Brooks/Cole Publishing, ISBN 0534520200.
6. Hillier & Lieberman, (2001) Introduction to Operations Research (7th ed.), McGraw-Hill.
7. Diebold F. X. (2007), Elements of Forecasting (4th ed.), South-Western
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| Study Abroad |
Not entered |
| Study Pattern |
The lecture programme provides an introduction to data management and to a number of quantitative techniques commonly used to help define or solve management decision problems. Topics are introduced during lectures, which are supported via learning material made available on Learn. Students then have the opportunity to apply the technique illustrated during the lectures in dedicated tutorials and computer sessions, all of which may be supported by further resources available from Learn. Students finally have the opportunity to apply selected techniques among those introduced in the context of a group project.
Attendance at example class tutorials and computer sessions is mandatory (the Business School will enforce a sliding scale of penalties for non-attendance, see Learn). Although this does place a requirement on the student to maintain progress with the course schedule, exercise classes lag behind lectures to help self-paced review of the materials. This allows a structured learning environment. Students who are unable to attend all the computer sessions or would like to repeat them may approach the Laboratory Computing Officer to access course's computer exercises during 'open access' laboratory times.
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| Keywords | information systems, data management, linear programming, decision analysis |
Contacts
| Course organiser | Dr Roberto Rossi
Tel: (0131 6)51 5239
Email: Roberto.Rossi@ed.ac.uk |
Course secretary | Ms Patricia Ward-Scaltsas
Tel: (0131 6)50 3823
Email: Patricia.Ward-Scaltsas@ed.ac.uk |
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