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DRPS : Course Catalogue : Business School : Business Studies

Undergraduate Course: Management Science and Information Systems (BUST08007)

Course Outline
SchoolBusiness School CollegeCollege of Humanities and Social Science
Credit level (Normal year taken)SCQF Level 8 (Year 2 Undergraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis 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.
Course description 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.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Business Studies 1 (BUST08001) OR Economics 1A (ECNM08005) OR Economic Principles and Applications (ECNM08002) OR ( Industrial Management 1 (BUST08002) AND Techniques of Management (MAEE08002))
Prohibited Combinations Other requirements None
Information for Visiting Students
Pre-requisitesVisiting 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.
Course Delivery Information
Academic year 2014/15, Available to all students (SV1) Quota:  None
Course Start Semester 2
Timetable Timetable
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 )
Additional Information (Learning and Teaching) Coursework: 30% individual lab assessments; 30% group essay (1500 words; 25% essay 5% peer WebPA)
Assessment (Further Info) Written Exam 40 %, Coursework 30 %, Practical Exam 30 %
Additional Information (Assessment) 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).
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)2:00
Resit Exam Diet (August)2:00
Learning Outcomes
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.

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
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
Additional Information
Graduate Attributes and Skills Transferable skills
1. demonstrate report writing skills
2. demonstrate problem analysis and problem solving skills
Additional 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.
Keywordsinformation systems, data management, linear programming, decision analysis
Course organiserDr Roberto Rossi
Tel: (0131 6)51 5239
Course secretaryMs Patricia Ward-Scaltsas
Tel: (0131 6)50 3823
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