Course : Decision Mathematics for Marketing
Course Code : BMKT 21233
Credit Value : 3
Status : Compulsory
Level : Level 2
Semester : Semester I
Overall Learning Outcomes : At the end of the session students should be able to;
 evaluate marketing related problems based on the techniques available under discrete mathematics
 recommend the best possible solution for a given scenario by interpreting the outcome of the problem analyzed using decision mathematical techniques
 convince how far the decisional mathematical techniques could be applied in marketing related decision making
 integrate the classroom learning to solve a real world business scenario given as a case study
 construct the best possible solution with the given information related to a real world business scenario accurately
 practice the techniques learned under the subject into decision making related to the project carried out as a group work
 practice the techniques under discrete mathematics in order to make best possible solution for business based problems
Course Content :
Topic No 
Topic 
Learning Outcomes 
Teaching and Learning Method 
Method of Assessment 
1 
Introduction to decision making using discrete mathematics 
At the end of the session students should be able to;

Lectures Class room discussions 
End Semester Examination 
2 
Linear Programming in marketing decisions 
At the end of the session students should be able to;

Lectures Problem based learning Tutorials 
End Semester Examination Answers for the questions given at tutorial sessions 
3 
Decision making for transportation and assignment problems 
At the end of the session students should be able to;

Lectures Practical sessions using MS excel Buzz groups 
End Semester Examination 
4 
Project Management for marketing 
At the end of the session students should be able to;

Lectures Problem based learning Implementation of a project as a group work 
End Semester Examination Written report based on group work Presentations based on group work 
5 
Decision theory 
At the end of the session students should be able to;

Lectures Problem based learning Tutorials 
End Semester Examination 
6 
Waiting line models for service systems 
At the end of the session students should be able to;

Lectures Problem based learning Case study 
End Semester Examination Written report based on case study analysis 
7 
Game theory and marketing in action 
At the end of the session students should be able to;

Lectures Problem based learning

End Semester Examination 
Recommended Reading :
 Anderson, D.R. and Sweeney, D.J. (2011), “An Introduction to Management Science: Quantitative Approaches to Decision Making”, 13th edition, Cengage Learning.
 Hillier, F.S., Lieberman, G.J., Nag, B. and Basu, P. (2010), “Introduction to Operations Research”, McGrawHill Higher Education.
 Pai, P. P. (2012), “Operations Research”,1st edition, Oxford University Press India.
 Pomerai, S. D. and Berry, J. (2001) , “Decision Mathematics :Discovering Advanced Mathematics”, 1st edition , Heinemann.
 Roueche, N. R., Michae, V. G. and Tuttle, I. D. (2005), "Business Mathematics: A Collegiate Approach", 9th edition, Prentice Hall.
 Stevenson, W.J. and Ozgur, C. (2012) , “Introduction to Management Science with Spreadsheets” , 9th edition, Tata McGraw – hill.