Managerial Model Building BA 669

Spring 2007

MBA Program

College of Business Administration

California State University San Marcos

Contents:

 

Course Information:

Textbook:

 

Required Text books:

References:

Course description and objectives:

 

Course Description: Today's business problems tend to be very complex, and approaches such as business experience, intuition, and thoughtful guesswork can no longer be applied to resolve managerial situations. But common sense and intuition go only so far in the solution of the complex problems business now face. This is where decision models are so useful. When the methods discussed in this course are implemented in user-friendly computer software packages and are then applied to complex problems, the results can be amazing.

The power of the methods in this course is that they are applicable to so many problems and environments. The following is a short list of success stories where management science has been applied: (1) United Airlines installed one of DFI's systems, which cost between $10 million and $20 million. United expects the system to add $50 million to $100 million annually to its revenue. (2) The Gap clothing chain uses management science to determine exactly how many employees should staff each store during the Christmas rush. (3) Management Science has helped medical researchers test potentially dangerous drugs on fewer people with better results. (4) Hotels, airlines, and television broadcasters all use management science to implement a new method called "yield management". In this method different prices are charged to different customers depending on their willingness to pay. The effect is that more customers are attract and revenues increases.

 

The purpose of this course is to expose you to variety of problems that have been solved successfully with management science methods and to give you experience in modeling these problems in the Excel Spreadsheet package. Our intent in this course is to emphasize the applied aspects of management science.

 

Learning Outcomes:

 

Following this course the students should be able to

 

Evaluation:

 

Your course grade will be based on

 

Case write-ups:

Each case study will require a written case report and the use of computer software. It should be appropriate as a consulting report. Students are encouraged to work in a team for case reports. The size of teams is determined based on the enrolment. The general plan of a case report should be as follows:

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Homework assignments:

Homework assignments are designed to help you learn the mechanics of the methods discussed in class and to give you an opportunity to apply these concepts in a straightforward manner. In addition to their value as learning exercises, doing a careful and thorough job on the homework assignments is the best preparation for the midterm and final exams. Homework assignments should be done individually.
 

Team project:

The objective of this is to permit students to tailor the course to their own interests, whether they are in Finance, Marketing, Accounting, Manufacturing, Systems, .... The project is designed to acquaint students with one specific area of modeling and optimization. Each team is required to present their findings and hand in a report.

The team project involves using optimization and or simulation in solving a real-world problem, ideally one involving your workplace. Each team must submit a one-page proposal on or before March 31.

The team project involves using optimization and or simulation in solving a real-world problem, ideally one involving your workplace.

Grading policy:

94-100

90 < 94

85 < 90

80 < 85

75 < 80

70 < 75

65 < 70

60 < 65

0 < 60

A

A-

B+

B

B-

C+

C

D

F


 

Tentative Course Schedule:

 

Date

Topics

Notes

Jan 20

Linear Programming models: Introduction

 

Jan 27

Linear Programming models: Graphical and Computer Solutions

 Assignment 1 due

Feb 3

Linear Programming models: Modeling Applications

 Assignment 2 due

Feb 10

Linear Programming models: Modeling Applications

 Case 1 due

Feb 17

Transportation and Network models

Assignment 3 due

Feb 24

Problem solving session

Assignment 4 due

Sample Exam

Mar 3

Exam 1

  

Mar 10

Group meeting – No lecture

 

Mar 17

Integer Programming

Case 2 due

Mar 24

Integer Programming

Assignment 5 due

March 31

 Spring break  

Apr 7

Decision Theory

Case 3 due

Project proposal due

Apr 14

Simulation

Assignment 6 due

Apr 21

Simulation

Case 4 due

Apr 28

Exam 2

 

May 5

Group presentation

 

 

Academic Honesty Statement: Students will be expected to adhere to standards of academic honesty and integrity, as outlined in the Student Academic Honesty Policy. All written work and oral presentation assignments must be original work. All ideas/material that are borrowed from other sources must have appropriate references to the original sources. Any quoted material should give credit to the source and be punctuated with quotation marks.

 

ADA statement: Students with disabilities who require reasonable accommodations must be approved for services by providing appropriate and recent documentations to the Office of Disabled Student Services (DSS). This office is located in Craven Hall 5205, and can be contacted by phone at (760) 750-4905, or TTY (760) 750-4909. Students authorized by DSS to receive reasonable accommodations should meet with me during my office hours in order to ensure confidentiality.

NOTE: It is the student’s responsibility to understand and follow the University Policies as stated in the catalog.