ManSci syllabus

DE LA SALLE UNIVERSITYCOURSE SYLLABUS

COLLEGE: RAMON DEL ROSARIO COLLEGE OF BUSINESS DEPARTMENT: DECISION SCIENCES AND INNOVATIONCOURSE CODE/SECTION: MSC515M GMD SY 2013-2014 3rd Term COURSE TITLE: MANAGEMENT SCIENCECLASS DAYS AND CLASS TIME: Thurs, 6-915pm ROOM: MEC 510INSTRUCTOR: DR. DENNIS BERINO ([email protected]) CONSULTATION HOURS:

COURSE DESCRIPTION:

MSC515M - Management Science is a course on the use of management science/operations research techniques in solving management decision problems and is meant to assist students in acquiring a special competence in the scientific management approach to problem solving.

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

ELGA LEARNING OUTCOMEEffective communicators Acquires facility for management science

jargon and is able to explain quantitative process and results in simple terms, both verbally and in writing.

Critical and creative thinkers Knowledgeable with standard tools in management science as well as relevant techniques in systems model building.Proficient in model formulation and interpretation of results.

Technically proficient and competent professionals and leaders

Adept in use of quantitative methods for objective decision making.

Service-driven, ethical, and socially responsible citizens

Incorporates ethical issues that need to be considered in quantitative decision making.

Note: Each ELGA does not have to have its own LO.

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

LEARNING OUTCOME REQUIRED OUTPUT DUE DATELO 1: Acquires facility for management science jargon

Class participationCase discussions

During lecture discussions for class

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mailto:[email protected]

and is able to explain quantitative process and results in simple terms, both verbally and in writing.

Project presentationsQuestionnaires

participationDuring designated dates for cases/projects & questionnaires.

LO 2: Knowledgeable with standard tools in management science as well as relevant techniques in systems model building.Proficient in model formulation and interpretation of results.

Use of QM for Windows

Volunteer exercises/ gamesCase discussionsProject presentations

During lecture discussions, vol ex, games, cases/projectsDuring designated dates for vol ex, games, cases/projects

LO 3: Adept in use of quantitative methods for objective decision making.

MS/OR in action, Web research

During designated dates for MS/OR in action, web research

Note: Each LO need not have its own output or work. Outputs may be in the form of a product to be submitted or a performance to be done (e.g., demonstration).

RUBRIC FOR ASSESSMENT:CRITERIA EXEMPLARY

4SATISFACTORY

3DEVELOPING

2BEGINNING

1RATING

Category 1 The submitted work manifests qualities which go beyond the requirements.

The submitted work manifests the required qualities.

The submitted work partially manifests the required qualities. Certain aspects are either incomplete or incorrect.

The submitted work does not manifest any of the requirements.









TOTAL:

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OTHER REQUIREMENTS AND ASSESSMENTS:

1. Examinations - Games (40%)

Games will test the comprehension of the student of the concepts and techniques discussed in class. It will have two parts:

( i) Individual Effort – closed notes questions on MS/OR concepts;

(ii) Group Effort – open notes, open books, open computer group computations of problems employing MS/OR techniques studied in class. Since we usually work in groups in the work place, there will be two (2) games wherein the students will work on assigned problems as a team. This will test their collective knowledge as well as ability to work as a team.

2. Computer Applications/Online SessionsMost model formulations for problems and cases taken up in class can be performed using a computer. We will require the use of available computer software packages to for computational facility during lectures, exercises, cases and projects.

The online sessions are meant to supplement classroom sessions to expose students to learning using online facilities/technology.

3. MS/OR in Action (5%) Students will be required to share MS/OR applications in their respective companies and how these applications facilitated decision making management. If no concrete experience from their companies can be shared, research/readings on other companies can be used as substitute. MS/OR in Action guidelines will be uploaded in Moodle.

4. Case Analysis (25%)Analysis of cases would expose the students to actual business problems confronting managers in some of their activities. The cases may involve either open- or close-ended situations that would call for the use of descriptive or prescriptive model formulations and their corresponding solutions. Also included in the case analysis are online business research assignments. All case analysis will be thru online discussions.

The cases require group analysis. This would allow the group members to interact intelligently among themselves to come up with a thorough analysis of the case. The corresponding groups assigned to the cases are required to submit a written analysis of the case. They will conduct an online discussion forum and come up with points of agreements and resolutions in the way they evaluated assigned case. Case Analysis guidelines will be uploaded in Moodle.

5. Project Assignment (15%) Students will be assigned to undertake projects the aim of which is to provide experience in the practical application of the materials discussed in the course. The projects will be

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done on a group work basis. Projects will be assigned for discussion and submission during the mid-point and final schedule of the school. Project Assignment guidelines will be uploaded in Moodle.

6. Class Participation (10%) We encourage the students to actively participate in class discussions as this will maximize their learning as well as create a livelier class atmosphere thru the interactions. The lectures will be mixed with volunteer hands-on computational exercises and take home assignments to improve understanding and retention of subjects being studied.

7. Volunteer ExercisesThese are take-home computational problems to be worked on and submitted in pairs (or by twos). This is meant to test the comprehension of the student of concepts discussed in class. Though not directly part of basis for evaluation, submitted exercises will be given point credits for certain activities in class as well as provide the student better facility for computations.

NOTE ON GROUP ACTIVITIES. Students will be grouped for the group activities. They will elect a group leader among themselves. The number and size of the groups will depend on class size. There will be a peer evaluation once, during the final period, to surface individual efforts of group members in assigned activities. This will be inputted in the grade of each group member for the specified group activities. For this course, the requirements with group effort are: games; case studies; and project assignments.

MIXED-MODE ONLINE LEARNING. The class will be under a mixed-mode online learning environment using Moodle as the learning management platform. Certain sessions will be conducted fully online.

PAPERLESS CLASS ENVIRONMENT. As a small contribution to preserving the environment, all class submissions will be done online. No paper submissions will be required of all requirements.

GRADING SYSTEM:MS/OR in Action

Case Analysis Project Assignment

Games Class Participation

AttendanceTOTAL

5% Grade pt. Equivalent Description25% 4.0 97-100 Excellent15% 3.5 93 - 96 Superior40% 3.0 89 - 92 Very good 10% 2.5 85 - 88 Good 5% 2.0 80 - 84 Satisfactory100% 1.5 75 - 79 Fair 1.0 70 - 74 Passed 0.0 Below 70 Failed W Withdrawal (authorized) 9.9 Incomplete

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LEARNING PLAN:LEARNINGOUTCOME

TOPIC WEEK NO.

LEARNINGACTIVITIES

1,2

1, 2, 3

1, 2, 3

1, 2, 3

SESSION 1A. Preliminaries – Syllabus Discussion, Housekeeping Rules, Student Information Sheet, Class Introduction, Grouping

B. Introduction to Management Science/Operations Research (MS/OR) 1. Introduction (1: 1-2) 2. Approach/Model Development (1: 3-4) 3. MS/OR and the Computer (1: 5)4. Problems/Implementation (1: 6-7)

SESSION 2Decision Theory Models1. Introduction (3: 1-3)2. Decision Making Under Uncertainty (3: 4)3. Decision Making Under Risk (3: 5)

SESSION 3Decision Theory Extensions1. Marginal Analysis *2. Decision Trees (3: 6)3. Utility Theory (3: 8)4. Game Theory *

Case 1 – Starting Right Corp., 130-131

SESSION 4Forecasting 1. Introduction to Forecasting (5: 1-4)2. Time Series Forecasting Models (5: 5-6)3. Causal Forecasting Methods (4: 1-8)

SESSION 5 - OnlineWeb research/online discussion forum on applications of1. Decision making under – Risk (1), Uncertainty (6)2. Decision trees (2), Utility theory (5)3. Game theory (3), Regression (4)

1,1/09

2,1/16

3,1/23

4,1/30

5,2/06

Lecture DiscussionGroup Dynamics

Lecture DiscussionSubmissions –1. Student Information Sheet2. Distance Learning Self-Assessment

Lecture DiscussionCase 1 Online Discussion (1,2)

Lecture DiscussionGame Theory Application; Game 1 credits – 20%

Web ResearchOnline Discussion Forum (1, 6), (2, 5), (3, 4)

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LEARNINGOUTCOME

1, 2, 3

2, 3

1, 2, 3

1, 2

1, 2, 3

1, 2, 3

TOPIC

SESSION 6Linear Programming1. Graphical/Computer Methods (7: 1-4) a. Special Cases (7: 7) b. Applications (8)2. Simplex method *3. LP Extensions a. Integer Programming (10: 1-2) b. Goal Programming (10: 4)

Case 2 – North-South Airlines, 165-166

SESSION 7 Game 1

SESSION 8 Project Presentations

Case 3 – Mexicana Wire Works, 320-321

SESSION 9

Specially structured LP1. Transportation Problem (10: 1-10)2. Assignment Problem (10: 13-15)Network Models1. Minimal Spanning Tree technique (11:2)2. Maximal-Flow Technique (11: 3)3. Shortest-Route technique (11: 4)4. PERT/CPM (12: 2-4)

SESSION 101. Waiting Lines and Queuing Theory (13: 1-5)2. Simulation (14: 2-3, 6)3. Markov Analysis (15: 2-6)

Case 4 – Old Oregon Woodstore, 412-413

SESSION 11 - OnlineWeb research/online discussion forum on applications of -1. Minimal spanning tree (1), maximal flow (4)

TOPIC

WEEK NO.

6, 2/13

7,2/20

8,2/27

9,3/06

10,3/13

11,3/20

LEARNINGACTIVITIES

Lecture DiscussionSubmit One Page Project 1 Proposal (1,2,3)Case 2 Online Discussion (3,4)

Game 1 (Chapters 1,3-5, 7,10) Project Presentations (1,2,3) - OnlineMS/OR in ActionCase 3 Online Discussion (5,6)

Lecture DiscussionMS/OR in ActionMid-Term Class Standing Update

Lecture DiscussionMS/OR in ActionCase 4 Online Discussion (3,4)

Web ResearchOnline Discussion Forum (1,4) (2,6) (3,5)MS/OR in Action

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LEARNINGOUTCOME

2, 3

1, 2, 3

1, 2, 3

2. PERT/CPM (2), Queuing (6)3. Simulation (3), Markov analysis (5)

SESSION 12 Game 2

SESSION 13 Project Presentations

Case 5 – Southwestern University Traffic Problems, p.476

SESSION 14 – Online Web research/online discussion forum on applications of1. Analytic Hierarchy Process* (1,2,3) 2. Decision Support Systems* (4,5,6)

*Pairings: (1,5), (2,4), (3,6)

Case 6 – Statewide Dev.Corp., 591-592

WEEK NO.

12,3/27

13,4/03

14,4/10

LEARNINGACTIVITIES

Submit One Page Project 2 Proposal (4,5,6)

Game 2 ( Chapters 11-16)Simcity submission (by pair); Game 2 credits – 20%

Project Presentations (4,5,6)Case 5 Online Discussion (1,2)MS/OR in Action

Web ResearchOnline Discussion ForumCase 6 Online Discussion (5,6)

TEXTBOOK:Quantitative Analysis for Management (11th edition, 2012)By: Render, Stair and Hanna

SUPPLEMENTARY READINGS: Online sources/applications on management science

ACADEMIC INTEGRITY POLICY

It is the mission of COB to train its students in the highest levels of professionalism and integrity. In support of this goal, academic integrity is highly valued at COB and violations are considered serious offenses.

Examples of violations of academic integrity include, but are not limited to, the following: Plagiarism - using ideas, data or language of another without specific or proper

acknowledgement. Example: Copying text from a web site without quoting or

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properly citing the page URL, paraphrasing a source’s spoken or written words without attribution, etc. For a clear description of what constitutes plagiarism as well as strategies for avoiding it, students may refer to the Writing Tutorial Services web site at Indiana University using the following link: http://www.indiana.edu/~wts/pamphlets/plagiarism.pdf. For citation styles, students may refer to http://www.indiana.edu/~wts/pamphlets/apa_style.pdf .

Cheating - using or attempting to use unauthorized assistance, materials, or study aids during examination or other academic work. Examples: using a cheat sheet in a quiz or exam, altering a grade exam and resubmitting it for a better grade, etc.

Fabrication - submitting contrived or improperly altered information in any academic requirement. Examples: Making up data for a research project, changing data to bias its interpretation, citing nonexistent articles, contriving sources, etc.

Reference: Code of Academic Integrity and Charter of the Student Disciplinary System of the University of Pennsylvania at: http//:www.upenn.edu/almanac/v43/n03/codechar.html.

Contacts: Dr. Dennis L. Berino

Associate Professorial Lecturer Advisor Development HeadDSI Dept, RVR-College of Business Agencies DivisionDe La Salle University AXA PhilippinesMakati Extension Campus 35th Floor, GT Tower5th Floor, Tower 2, RCBC Plaza Ayala Ave. cor. Dela Costa St., Makati CityAyala cor. Buendia Ave., Makati City [email protected]@dlsu.edu.ph 8850101 loc. 14207534611

[email protected], [email protected]+6329193266204

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