This unit introduces students to quantitative modelling for business-oriented decisions.

Assessment amended to better align the weighting of the coursework component with the amount of coursework actually done by students. Change to be implemented in Semester 1 2012.

22/1/2014 - Change to contact hours made to align with Handbook entry (bulk upload from CUPID extract). Approved by ADE.

22 May 2014- Updated objectives to learning outcomes for AQF compliance.

22 May 2014 - Added Prescribed reading. Deleted Clayton from location of offering since unit has never been offered at Clayton and will not be offered at Clayton in the future. Changes effective Semester 2,2014.

20/9/2019: Admin - updating exam duration to include additional 10 minutes as per University requirement.

09/10/2020 Admin: Update to include new assessment and teaching approach fields as per Handbook requirements.

15/07/2021 Matt: Reinstating the unit learning outcomes to what they were last offering on behalf of the CE

The unit is core within the Business Intelligence track of the Master of Business Information Systems (MBIS), and an elective within the Master of Business Systems (MBS), Master of Information Management Systems (MIMS), Master of Information Systems (MIS), Master of Applied Information Technology (MAIT) and the Master of Information Technology (MIT). It re-develops the content of BUS5570 Computer Models for Business Decisions to broaden and update the contents in order to better reflect current themes and approaches to business decision modelling.

On completion of this unit students should be able to:

• explain a variety of techniques for modelling business decision problems;
• choose the appropriate decision model for a particular problem;
• set up simple models and solve with hand calculations;
• set up mathematical models for solution in a spreadsheet or other application software;
• validate models and conduct a sensitivity analysis;
• analyse a real problem and report the results;
• explain the difficulty of applying models to real situations - which often requires that approximations, simplifications and generalisations be made;
• explain the approximate nature of some types of business modelling and why this usually means that a sensitivity analysis needs to be conducted.

020399

This unit introduces students to the principles, techniques and applications of computer-based decision support models for business and industry. Topics include: decision trees; linear programming and optimisation; other mathematical programming methods; waiting lines and queues; time series analysis and forecasting; inventory modelling and discrete-event simulation. Models will be built and solved using spreadsheets or other computer applications as appropriate.

MicroSoft Excel Solver is available for use in all University labs.

Prescribed text

Ragsdale C.T. (2018). Spreadsheet Modeling & Decision Analysis . (8th Edition) Thomson

Recommended resources

• Lapin, L. and Whisler , W., Quantitative Decision Making with Spreadsheet Applications 7th Ed., Wadsworth (Thomson Learning) Belmont, 2002 (7 th edition, 2002) or later. (supplementary, main text for inventory models)
• Anderson D., Sweeney D. and Williams T., Quantitative Methods for Business 11th Ed, South-Western College Publishing (Thomson Learning), 2008 or later.
• Winston, W. L. Operations Research: Applications and Algorithms, Duxbury Press, Belmont, 2004 or later.
• Willis, R. J., Business Modelling, Eruditions Publishing, 2000.

On-campus

• Active learning
• Case-based teaching
• Enquiry-based learning
• Laboratory-based classes
• Lecture and/or tutorials or problem classes
• Online learning
• Peer-assisted learning (there will be some problems to discuss)
• Problem-based learning
• Studio teaching

Examination (2 hours and 10 minutes): 60%; In-semester assessment: 40%

1. Tutorial Participation: 6% - ULO 1,2,3,4,5,6,7,8
2. Quiz 1: 2% - ULO 1,2,3,4,5,7,8
3. Spreadsheet Modelling Assignment: 30% - ULO 1,2,3,4,5,6,7,8
4. Quiz 2: 2% - ULO 1,2,3,4,5,7,8
5. Examination: 60% - ULO 1,2,3,7,8

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

(b.) Additional requirements (all students):

FIT