DE LA SALLE UNIVERSITYCOURSE SYLLABUS

COLLEGE : COLLEGE OF BUSINESS DEPARTMENT: DSICOURSE CODE : MANASCICLASS DAYS AND CLASS TIME: TH, 1800-1930/1940-2110 ROOM: L330

INSTRUCTOR: MR. ENRICO L. CORDOBA (lance_emeric@yahoo.com)

COURSE DESCRIPTION:MANASCI (MANAGEMENT SCIENCE) is a 14-week course on the study of quantitative techniques in business decision-making. The course covers linear programming models and its special algorithms; network (PERT/CPM) models; decision-making theories and processes; and decision tree construction and analysis.

LEARNING OUTCOMES (LO):On completion of the course, the student is expected to be able to do the following:

ELGA LEARNING OUTCOMEEffective communicators To present in class the application of quantitative

techniques to management decision models through case analysis

Critical and creative thinkers To develop analytical thinking and proper reasoning in the application of quantitative techniques to management decision models

  To acquire the essential skills for the proper use of quantitative techniques in business decision-making

Technically proficient and competent professionals and leaders

To identify the various mathematical tools used in business decision-making

To apply the theories of quantitative analysis in solving business problems

  To be proficient in building quantitative models in business decision-making

  To establish the habits of neatness and orderliness in presenting written solutions to problems

Service-driven, ethical, and socially responsible citizens

Challenge the Lasallian learners to realize their full potential in applying quantitative techniques through creativity, innovativeness, honesty, and perseverance.

  Ensure that the learners translate knowledge, innovation, and creativity into something useful in actual practice for the betterment of society and the Church.

  Prepare the learners to participate responsibly in the world of work, family, community, nation, and Church by developing values of honesty, patience, and perseverance in the process of finding solutions to problems; and

  Bring a Christian perspective to bear on human understanding, skills and values of the learners through the realization of the role of quantitative techniques in decision-making in enabling businessmen to be more socially responsible.

COURSE OUTPUT:As evidence of attaining the above learning outcomes, the student is required to do the following during the indicated dates of the term.

LEARNING OUTCOME REQUIRED OUTPUT DUE DATELO 1: present in class the application of quantitative techniques to management decision models

Case Analysis At the end of each major quantitative model group (see Learning Plan)

LO 2: apply the theories of quantitative analysis in solving business problems and to be proficient in building quantitative models in business decision-making

Case Analysis At the end of each major quantitative model group (see Learning Plan)

LO 3: apply the theories of quantitative analysis in solving business problems; establish the habits of neatness and orderliness in presenting written solutions to problems

Quizzes and Final Exam At the end of each major quantitative model group (see Learning Plan)

LO 4: realize of the role of quantitative techniques in decision-making in enabling businessmen to be more socially responsible.

Case Analysis and Quizzes  At the end of each major quantitative model group (see Learning Plan)

RUBRIC FOR ASSESSMENT OF CASE ANALYSIS:CRITERIA STRONG ACCEPTABL

EUNACCEPTABLE WEAK RATIN

G  4 3 2 1  

Define the problem

Accurately interprets evidence, statements, graphics, questions, etc.

Accurately interprets evidence, statements, graphics, questions, etc.

Misinterprets evidence, statements, graphics, questions, etc.

Offers biased interpretation of evidence, statements, graphics, questions, information, or the points of view of others.

 

Develop a model

Identifies the most important arguments for choice of model

Identifies relevant arguments (for choice of model)

Fails to identify strong, relevant arguments for choice of model

Fails to identify or hastily chooses model

 

Acquire input data

Identifies and gathers the most important data suitable for chosen model

Identifies and gathers relevant data suitable for chosen model

Fails to identify and gather relevant data suitable for chosen model

Fails to identity or hastily gathers relevant data suitable for chosen model

 

Develop and test the solution

Draws warranted and sensible conclusions based on solution

Draws warranted conclusions based on solution

Draws unwarranted of fallacious conclusions

Does not justify results or procedures, nor explain conclusions

 

Analyze the results

Thoughtfully analyzes and evaluates major alternative points of view

Offers analyses and evaluations of obvious alternative points of view

Ignores or superficially evaluates obvious alternative points of view

Ignores or superficially evaluates obvious alternative points of view.

 

GRADING SYSTEM:Final Grade GRADE POINT

Quizzes - 40% EQUIVALENTClass Participation - 10% 97-100 4.0Case Analysis - 20% 93-96 3.5Final Dept. Exam - 30% 89-92 3.0

100% 85-88 2.5

80-84 2.075-79 1.5

Passing grade is 70%

LEARNING PLAN:LEARNING OUTCOME

TOPIC WEEK NO. LEARNIG ACTIVITIES

  Orientation 1 Discuss course syllabus and class policies

Ensure that the learners translate knowledge, innovation, and creativity into something useful in actual practice for the betterment of society and the Church.

Introduction to Management Science

2 Lecture and discussion on: Origins of Management

Science/ Operations Research Significant contributions of

scientists to Operations Research

To apply the theories of quantitative analysis in solving business problems;

To be proficient in building quantitative models in business decision-making;

To develop analytical thinking and proper reasoning in the application of quantitative models to management decision models.

Linear Programming

Lecture and discussion on: Linear Programming and

Formulation Graphical Method to Solving

Linear Programming Problems

3 Lecture and discussion on: Simplex Methods to Solving

Linear Programming Problems Sensitivity Analysis/Post-

Optimality Analysis Dual Program/Shadow Pricing

4 Lecture and discussion on: Spreadsheet Modeling Use of Available Software in

Management Science 5 Quiz # 1

Presentation and discussion of Case # 1

To apply the theories of quantitative analysis in solving business problems;

To be proficient in building quantitative models in business decision-making;

To develop analytical thinking and proper reasoning in the application of quantitative models to management decision models.

Project Management

6 Lecture and discussion on: Networks The Shortest-Route problem The Minimum Spanning Tree

problem The Maximal Flow problem Program Evaluation and

Review Technique (PERT)

7 Lecture and discussion on: Stochastic PERT Critical Path Method (CPM) Optimum Completion Time,

Slack Time Cost PERT/Cost Crashing a project’s

completion time

8 Presentation and discussion of Case # 2

To apply the theories of quantitative analysis in solving business problems;

To be proficient in building quantitative models in business decision-making;

Transportation Model

Lecture and discussion on: General Transportation Model Solving Transportation

Problems Heuristically Northwest Corner Rule Greedy Method Row-Minimum Method Vogel’s Approximation

Method

To develop analytical thinking and proper reasoning in the application of quantitative models to management decision models.

9 Lecture and discussion on: The Stepping-Stone Method The Modified Distribution

(MODI) Method Occurrence of Degeneracy Transshipment Model Assignment Model

10 Quiz # 2 Presentation and discussion

of Case # 3

LEARNING OUTCOME

TOPIC WEEK NO. LEARNIG ACTIVITIES

To apply the theories of quantitative analysis in solving business problems;

To develop analytical thinking and proper reasoning in the application of quantitative models to management decision models.

Integer Programming

Multiple Criteria Decision Making

11 Lecture and discussion on: Integer Programmingo Branch-and-Bound Method

Multiple Criteria Decision Makingo Goal Programmingo Multiple-Objective Linear

Programming (MOLP)

Queuing Lecture and discussion on: Parts of any Queuing System Steps in Queuing Analysis Basic Single Server Model Multi-Server Model Single Server Model with

Arbitrary Service Times Single Server Model with

Arbitrary Service Times and a Priority Queue Discipline

To apply the theories of quantitative analysis in solving business problems;

To develop analytical thinking and proper reasoning in the application of quantitative models to management decision models.

Decision Theory

12 Lecture and discussion on: Steps in Decision Theory

Approach The Criteria for Decision-

making under Uncertainty Decision-making under the

condition of Risk Expected Monetary Value Constructing a Decision Tree

Game Theory

Analytic Hierarchy Program

Lecture and discussion on: Application of Game Theory in

Business Decision-Making Steps in using the Analytic

Hierarchy Program in Business Decision-Making

13 Quiz # 3 Presentation and discussion

of Case # 414 Final Examinations

TEXT/ MATERIALS:Render, B., Stair, R., & Hanna, M. (2009). Quantitative Analysis for Management (10th ed.)Upper Saddle River, NJ: Pearson Education, Inc.

REFERENCES

Anderson, D., Sweeney, D., & Williams, T. (2001). Quantitative Methods for Business (8th ed.). Cincinnati, OH: South Western College Pub.

Levin, R., Rubin D., Stinson, J., & Gardner, E. (1992). Quantitative Approaches in Management (8th ed.). New York: McGraw Hill.

Taylor, B. (2007). Introduction to Management Science (9th ed.). Upper Saddle River, NJ: Pearson Education, Inc.

CLASS POLICIES:

Please refer to the student handbook.