Instructor: Dr. Yu-Mong Hsiao

Office:     230 Lundy-Fetterman School of Business Bldg. 

Phone:     910-893-1397                    Fax: 910-893-1392

E-Mail Address: hsiao@campbell.edu

Office Hours:      10 am - 10:50am MWF; 2:00 pm-2:50 pm  Tuesday, or by appointment.

Blackboard course web site: http://www.blackboard.campbell.edu  (BADM-760-B1-08-RLB1)

STATEMENT OF PURPOSE:

As an integral part of University purpose, this course is designed to equip students with superior vocational skills, productive insights, and professional integrity, and to transfer from one generation to the next the vast body of knowledge and values accumulated over the ages.

Text:

Bernard W. Taylor III, Introduction to Management Science, Ninth Edition, Pearson/Prentice Hall, 2007

Software & Web Resource:  

1. Excel QM, Crystal Ball,  TreePlan, The Management Scientist, V.6 (packed with UG textbook)
2. Textbook Web Page: www.prenhall.com/taylor

SUPPLEMENTARY READINGS AND REFERENCES:

1. William J. Stevenson & Ceyhun Ozgur,  Introduction to Management Science with Spreadsheets,  McGraw-Hill/Irwin, 2007
2. Winston Albright, Practical Management Science, 3e, Thomson/South-Western, 2007.
3. Anderson, Sweeney & Williams, Quantitative Methods for Business, 10th Edition, South-Western/Thomson Learning, 2006

SUPPORT SERVICES:

Students with documented disabilities who desire modifications or accommodations should contact the office of Student Support Services located in the University's Hight House.

1. For disability and tutoring services, contact:  Miss Laura Rich - Director of Student Support Services,  Hight House 104, 910-814-4364

2. For personality and career interest testing, and job placement services, contact:  Mr. John Creech - Assistant Dean of Student Services, Hight House 103,  910-893-1901 or creech@campbell.edu

Course Description:

This course intends to acquaint students with contemporary basic management science methodology.  It emphasizes the use of computers and computer assisted solution methods, and the application of a wide variety of quantitative techniques to the solution of business and economic problems. Business ethics related to decision-makings will be addressed.  In-class work (quizzes and discussions), homework and case studies will supplement class lectures. 

Course Learning Objectives:

The student will learn the most commonly-used quantitative techniques in business and its relevant applications in the real world management problems.  A variety of management science techniques will be covered, including the following four major groups of models:

1. Linear programming (LP): computer solution and sensitivity analysis; duality; LP formulation applied to transportation/transshipment/assignment problems and other business decision-making problems.
2. Network techniques: network flow models; project/scheduling management
3. Probabilistic techniques- Queuing theory, Markov processes, probabilistic decision theory, and decision tree analysis
4. Other decision techniques: Break-even analysis, Forecasting, Inventory models, non-probabilistic decision criteria, and Game theory.

Course Learning Outcomes: Students will be able:

1. To understand the quantitative techniques covered in this course
2. To analyze and apply the appropriate quantitative methods to business decision-making situations
3. To interpret their results.

ATTENDANCE REQUIREMENT:

1. Students are expected to be punctual and to comply with the University’s class attendance policy described on page 21 of Campbell University Bulletin; 2007-2009.   
2. The Campbell University absence policy requires that a student must be present for at least 85% of the class meetings in order to receive a grade. There are 32 contact hours in fall I term, which consists of 8 four-hour classes.  Each class meeting (Thursday) is considered 4 one-hour-class held.  If absences (legitimate or otherwise) exceed five contact hours, an F will be assigned.  Each student should keep a record of his/her absences to avoid over-cutting.
3. If a student arrives after the roll has been called the student will be counted absent unless he/she informs the instructor of his/her arrival immediately after class.  Three tardiness will count as one absence.  Early departure without permission or tardy for more than15 minutes will count as an absence.

IN-CLASS USE OF LAPTOPS AND SIMILAR ELECTRONIC DEVICES

In-class use of laptops, PDAs, and other similar electronic devices is prohibited unless it is pre-approved or asked specifically by the instructor.

GRADING SYSTEM*:

  *Notes:

1. Tentative Test Dates:

   	Midterm test: September 11, 6:00pm -8:00pm
   	Final Exam:   October 9, 8:00pm -10:00pm

2. All tests are mandatory.  If you know in advance that you will not be able to take the midterm test on the scheduled date, the test should be taken as soon as possible before the next class met subject to the instructor's approval. If a student fails to take the test within the allowable time, the student will receive a zero grade for that test.  The final exam is scheduled on  October 9, the last day of class.  No ramification will be allowed unless it is due to inclement weather or other extenuation situations.
3. The test may include open book/notes and close book/notes parts. Test format may consist of multiple-choice and problem solving.  A 3" by 5" index card with any information you care to write on it will be allowed in the close book/notes component.
4. Format, delivery methods and due dates for all assignments will be posted on the Bb course web site. Please check your Campbell email and Bb course web site for detailed announcements.  Assignments include homework,  postings of applications on Discussion Board, and case studies.  No late assignments will be accepted for any reasons.
5. Quizzes: Most quizzes are in-class open book/notes exercises on specific topics covered in class. It is intended to engage students and, at the same time,  to get feedback from students as a formative assessment.  No make-up quiz will be given for any reason. I will drop one of your lowest quiz grade. If you miss a class, you can take it as your drop.
6. Homework: The best way to learn the material is by doing problems.  There will be a set of problems to do on every topic.  You may discuss the problems with other students, but the work you hand in must be your own. Simply copying someone's work is considered cheating and will result in a zero grade. You may drop one of your lowest homework grade.
7. Discussion Board on Bb web site:

   Application Forum: (10% course grade) This forum is to provide students an environment to make connections from materials learned in this course to the real world. Each student is required to post at least three distinctive real world applications using different quantitative methods covered in this course. First hand, job-related application is most appropriate.  If you can not think of any job-related application, you may cite and summarize any application from articles found in Wall Street Journals or other business professional journals.  Interfaces,  the most prestigious professional journal in Operations Research, is the best source for management science applications. In your posting, you should describe briefly the nature of business situation, the quantitative model used and the results of the application. As long as your post is relevant, clear, and timely, you will earn full credit.  The due date and detailed requirements will be posted on the Bb course web site.  No late post will be accepted. Students who do not post will receive zero grade.

   Students Free Forum: (not graded)  This forum is open for students to post any questions, comments, or discussions about BADM 760 class.  For example, if you do not understand a subject discussed in class, you may post your questions and your fellow students who understand it may respond to it.  Students can help each other to learn the materials.  So you do not struggle alone. You do not need to wait until the next class for clarification from me.

8. Case Studies: Cooperative learning pedagogy will be used in the case study. Each case study will be done and graded individually. Then a group of two or three students will be assigned to work together to improve and fine-tuning their report.  Your case study grade will be the average of your individual  and group report grades. Details will be discussed in class.
9. Honor Code: Cheating of any kind including plagiarism will not be tolerated.  The Honor Code applies to the major tests, pop quizzes, homework, case studies and all course assignments.  Any cheating will result in an FX as  the course grade and other possible sanctions.
10. Grading Scale:  A = 90 and above;  B = 80s; C = 70s and F = below 70.  Students earn their grade according to the grading system stated in this syllabus.  To be consistent and fair to every student, I do not permit any individual to do extra projects or other work to improve one's grade.  If a student's overall course grade is less than half-point away from the next better grade, I will make the favorable adjustment. 
11. No grade will be distributed over the phone or by email.

COURSE OUTLINE:

Part 1.  Introduction and Math Review (Ch. 1)

1. Introduction (Ch. 1)
   1. Model Building - Break Even Analysis
   2. Quantitative Methods in Practice
   3. Business Ethics in Decision-Making Process

Part 2.  Linear Programming (Ch. 2, 3, 4)

1. LP Formulation and Graphical Solution* (Ch.2)
2. Computer Solution and Sensitivity Analysis (Ch.3)
3. Duality  (handouts)
4. LP Modeling Examples (Ch.4)
5. Integer Programming*  - Computer Solution (Ch.5)

Part 3.  Transportation, Transshipment, and Assignment Problems (Ch. 6)

1. LP formulation & Computer Solution

Part 4.   Network Flow Models (Ch. 7)

Part 5.  Project Management (Ch. 8)

1. PERT network
2. The Critical Path
3. PERT under Uncertainty
4. The LP Formulation for Project Crashing Decision

Part 6.  Decision Theory (Ch. 12)

1. Decision making under uncertainty

1. Deterministic Decision Criteria
   1. Optimistic approach (maximax, Minimin)
   2. Conservative approach (Maximin, minimax regret)
2. Probabilistic Decision Criteria
   1. Expected Value criterion
   2. Maximum Likelihood Principles
   3. EVPI
3. Decision Tree Analysis

2. Game Theory (CD-ROM Module E)

Part 7.  Forecasting & Regression Analysis (Ch. 15)

1. Forecasting Methods
   1. Time Series Methods
      1. Moving Average
      2. Weighted Moving Average
      3. Exponential Smoothing
   2. Linear Trend Projection
   3. Seasonal Adjustments (handout)
   4. Forecasting Accuracy Criteria: MAD; MSE
2. Regression Analysis
   1. Simple linear regression
   2. Multiple linear regression
   3. Nonlinear regression
   4. Goodness of fit (R² and F test)

Part 8. Inventory Management* (Ch. 16)

1. The simple EOQ model
2. The EOQ model with noninstantaneous receipt
3. The EOQ model with shortages
4. The EOQ model with quantity discounts
5. The Reorder Point and Safety Stocks

Part 9.  Probabilistic Techniques

1. Queuing Analysis (Ch. 13)
2. Markov Process Models (CD-ROM Module F)

Note: Chapters with * sign may not be fully covered in class.

Tentative Schedule (The sequence of chapters covered in class and materials covered in the midterm test and final exam are subject to change)

August	21	Syllabus, Introduction
		Model Building: Break-even Analysis (Ch. 1); LP modeling* (Ch. 2)
		LP- computer solution, sensitivity analysis, and duality (Ch. 3)
	28	LP modeling - product mix, investment, marketing problems (Ch 4)
		LP modeling- Integer programming*(Ch. 5)
		LP modeling-Transportation/Transshipment/Assignment problems (Ch. 6)
September	4	Network Flow Models (Ch. 7)
		PERT/CPM (Ch. 8)
	11	6:00 pm - 8:00 pm Midterm test (Ch. 1, 2*, 3, 4, 6, 7, 8)
		8:20 pm - 10:00pm Decision Theory (Ch. 12)
	18	Decision Theory (Ch. 12)
		Game Theory (Module E)
	25	Forecasting & Regression Analysis (Ch. 15)
October	2	Queuing Analysis (Ch. 13)
		Markov Process Models (Module F)
	9	Markov Process Models (Module F)
		Final Exam: Ch. 12, 15, 13, module E and F
		8:00 pm - 10:00 pm: Final Exam: Part I: open book/notes; Part II: close book/notes