Quantitative Methods for Decision-Making (21848)
Degree/study: degree in Business Sciences
Year: 2nd
Term: 2nd and 3rd
Number of ECTS credits: 10 credits
Hours of studi dedication: 250 hours
Teaching language or languages: Spanish
Teaching Staff: Helena Ramalhinho, Joan B. Pallarés, Danilo Guaitoli, Agustí Garrido, Giampaolo Viglia
PART 1
1. Presentation of the subject
The area of Quantitative Methods for Decision-Making is based on the scientific method for investigating and helping to take decisions about complex problems in modern organisations. Public and private organisations today face complex management problems in which their managers have to take a decision. Decision-making is the process by means of which the choice is made between the alternatives or ways to resolve various situations or problems. These decisions have a very significant effect on organisations' competitiveness and survival. The increasing availability of communication and information systems also provide enable decision-makers with access to a great deal of data and computer systems that can help them to take decisions. Quantitative Methods for Decision-Making, also known as Operations Research, is a science that provides decision-makers, managers and directors in an organisation with the methodologies and techniques that enable them to assess several alternatives and choose the best one for their organisation. This science is based on the scientific method and has countless successful applications. The methodology uses mathematical models, databases and computer programmes to help in decision-making. On this course, we will be focusing on the application of Quantitative Methods to decision-making in problems in the field of Business Management and Administration that involve quantitative factors.
The objective of this course is to provide the essential concepts, quantitative models, solutions and latest techniques in solving management and administration problems in complex systems, with special emphasis on decision-making. In the classes, the essential topics will be discussed, as well as case studies of these models and methodologies in various areas of business administration. The application of models will be emphasised, as well as an explanation of how they can help in decision-making for the problems that appear in any organisation.
2. Competences to be attained
The objective of this course is to provide the essential concepts, quantitative models, solutions and latest techniques in solving management and administration problems in complex systems, with special emphasis on decision-making.
|
General skills |
Specific skills |
|
Instrumental • Organisation and planning capability. • Knowledge of computer programmes. • Problem-solving. • Search for the appropriate information from various sources.
Interpersonal • Oral communication in public. • Teamwork. • Written communication.
Systematics • Critical reasoning in reading and in written work and in oral communication. • Analysis and synthesis of qualitative and quantitative information. • Adaptation to new situations. |
Academic and professional • Appreciate the importance and power of Quantitative Methods in decision-making in organisations of the present and future. • Be able to recognise when this methodology and these techniques can be applied, and when they cannot. • Learn how to apply the main techniques of the Quantitative Methods to analysis and solving of managerial problems. • Be able to use analytical tools and methodologies based on mathematical models to help in decision-making in business environments. • Be able to use information systems and computer programs to help in decision-making in business environments. • Develop an understanding of the interpretation of the results of a study based on the methodology of Quantitative Methods. |
3. Contents
1. Introduction to quantitative methods for decision-making
1.1. The scientific method applied to decision-making
1.2. Operations Research and decision-making
1.3. Examples of application of quantitative methods to decision-making
2. Linear Programming
2.1. Linear Programming: Basic concepts
2.2. Linear Programming Models
2.3. Using Excel to solve Linear Programming problems
3. Applications of Linear Programming
3.1. The Transport Problem
3.2. Assignment Problems
3.3. Examples of application Linear Programming to problems in Operations, Marketing, Finances etc.
4. Integral Linear Programming
4.1. Integral Linear Programming: Basic concepts
4.2. Integral Linear Programming Models
4.3. Location Models
4.4. Using Excel to solve Integral Linear Programming problems
5. Multiobjective Models & Goal Optimisation
5.1. Multiobjective Models & Goal Optimisation: Basic concepts
5.2. Examples of Multiobjective Models & Goal Optimisation
6. Network Models
6.1. Network Models: Basic concepts
6.2. Shortest Route problems
6.3. Flow problems
7. Project Management
7.1. Project Planning and Management with PERT/CPM
7.2. Examples of application
8. Resolution Techniques: Heuristics
8.1. Advanced resolution techniques
8.2. Heuristics and Metaheuristics
8.3. Application to Integral Linear Programming and Network models
9. Queue Management
9.1. Queue Models
9.2. Examples of application
10. Simulation
10.1. Example of application of the simulation to decision-making
4. Assessment
Assessment of the subject will take place in one of the two options chosen by the student:
1. Continuing Assessment Option (June examination or September examination):
• Seven activities for assessment and participation in seminars (3.5 points out of 10 in the final mark);
• A final examination consisting of a multiple-choice section + exercises (65%) and obtaining a minimum garde of 4 out of 10 in this examination.
The activities will be assessed according to the following criteria (each seminar counts for 0.5 points out of 10 in the final mark):
A. Attendance at the seminar; active participation in the seminar; submission of an original report or the exercises set and the grades achieved for them.
B. Marks in the exercises to be solved in class.
The remaining 0.5 will be marks for the exercises to be solved by students on the blackboard (at least once in the series of six seminars).
2. Classic Assessment Option (September examination only):
• A final examination consisting of a multiple-choice section + exercises + cases (100%).
Comments:
• The subject of Quantitative Methods for Decision-Making consists of two parts: 1st part in the second term, and the 2nd part in the third term. The final mark for the subject will be the average of the two parts.
• The mark for the first part of the subject of Quantitative Methods for Decision-Making accounts for 50% of the final mark in the subject, but only if the student has obtained at least 4 out of 10 in the final mark. Failing this, the subject is automatically failed.
• Reports wholly or partially copied from Internet without appropriate citation or reference to the original work will receive a mark of 0 (zero) and depending on the degree of seriousness, may lead to the subject being failed.
• Students must bring the prepared activities for each seminar. In the case studies, students must bring a case prepared for discussion and the written report with the appropriate presentation. In the exercise seminars, they must bring the solved exercises, and doubts regarding these exercises will be clarified in the first part of the class.
• The exercises for assessment will be indicated by the lecturer in the appropriate seminar and solved by the student at the end of the class.
• If the student fails to attend the seminar aims in the exercises, he/she will receive a maximum of half the mark for that seminar.
• Reports or any other item for assessment cannot be handed in by e-mail. No enquiries by e-mail will be answered.
N.B.: UPF students on ERASMUS schemes outside Catalonia
Assessment will be identical for all students, including ERASMUS students. No exceptions will be made. Erasmus students who are not in Catalonia must contact the lecturer to decide how to hand in the activities if they choose the continuing assessment option.
5. Bibliography and teaching resources
5.1. Basic bibliography
• Render, B. , Stair, R. & Hanna, M.E. (2006). Métodos cuantitativos para los negocios. Pearson Prentice Hall.
5.2. Complementary bibliography
• Hillier F., Hillier M. and Lieberman, G.(2008). Métodos cuantitativos para administración, McGraw Hill.
• Powell, S.G. & Baker, K.R. (2010). The Art of Modelling with Spreadsheets: Management Science and Modelling Craft, 3rd edition, Wiley
• Serra D. (2003). Métodos Cuantitativos para la Toma de Decisiones. Gestión 2000.
• Winston, W. (2004). Excel Data Analysis and Business Modeling, Microsoft Press
5.3. Teaching resources
Software
• Excel Solver
• GLP (Windows graphic visualization program for 2-dimensional linear programming models).
• GIDEN - a graphical environment for network optimization (http://users.iems.northwestern.edu/~giden/)
• LINDO & LINGO - http://www.lindo.com/
The support material for the subject is available in the Aual Global - Moodle and consists of:
- Transparencies for each subject for the theoretical classrooms in PDF format.
- A detailed bibliography for each subject.
- Exercises and Case Studies for seminars.
6. Methodology
The teaching/learning activities will be as follows:
• Face-to-face in the classroom with the complete group (85-100 students). One topic will be discussed each week (see section 4: Contents). There will be twenty 90-minute classes using the lecture methodology.
• Face-to-face in the classroom with subgroups - Seminars (3 subgroups per group). One or more activities will take place in each class, ranging from discussion of a case study or carrying out quantitative exercises. There will be twenty 90-minute classes practical classes with activities using a highly interactive and participatory methodology. These activities require preparation before and after the seminar (see the subject dossier).
• Supervised individually outside the classroom. For each topic, students must do the reading shown in the subject dossier, and preparation for the individual activities.
• Supervised in groups (3 to 5 students) outside the classroom. Case studies for discussion in class must be prepared by groups of 3 to 5 students. The discussion and the report to be presented at the seminar must also prepared in groups.
• Autonomy outside the classroom, both individually and in a team. Students can also learn autonomously by consulting other sources, such as the additional bibliography.
The following tables show the learning activities, resources and workload in the theory sessions and seminars.
7. Planning of activities (part 1 of QMDM only)
|
Group |
Term |
Language |
Timetable |
Seminar Groups |
||||||
|
1 |
2 |
Spanish |
from 10.01.2011 to 18.03.2011 |
|
||||||
|
2 |
2 |
Spanish |
from 10.01.2011 to 18.03.2011 |
|
Date |
Subject |
Seminars |
Case - Exercises |
Comments |
|
|
Week 1 |
1. Introduction to quantitative methods for decision-making |
|
|
|
|
|
Group 1 |
Group 2 |
||||
|
13.01.2011 14.01.2011 |
12.01.2011 14.01.2011 |
||||
|
Week 2 |
2. Linear Programming |
|
|
|
|
|
Group 1 |
Group 2 |
||||
|
20.01.2011 21.01.2011 |
19.01.2011 21.01.2011 |
||||
|
Week 3 |
|
3. Applications of Linear Programming |
|
|
|
|
Group 1 |
Group 2 |
||||
|
27.01.2011 28.01.2011 |
26.01.2011 28.01.2011 |
||||
|
Week 4 |
|
4. Integral Linear Programming |
Subgroups 101, 102, 201, 202: 31.01.2011 |
Seminar 1 Exercises and cases of Linear Programming |
|
|
Group 1 |
Group 2 |
||||
|
03.02.2011 04.02.2011 |
02.02.2011 04.02.2011 |
Subgroups 103, 203: 01.02.2011 |
|||
|
Date |
Subject |
Seminars |
Case - Exercises |
Comments |
|
|
Week 5 |
|
1. Multiobjective Models & Goal Optimisation
|
Subgroups 101, 102, 201, 202: 07.02.2011 |
Seminar 2 Exercises and cases of Linear Programming |
|
|
Group 1 |
Group 2 |
||||
|
10.02.2011 11.02.2011 |
09.02.2011 11.02.2011 |
Subgroups 103, 203: 08.02.2011 |
|||
|
Week 6 |
|
2. Network Models
|
Subgroups 101, 102, 201, 202: 14.02.2011 |
Seminar 3 Exercises and cases of Linear Programming |
|
|
Group 1 |
Group 2 |
||||
|
17.02.2011 18.02.2011 |
16.02.2011 18.02.2011 |
Subgroups 103, 203: 15.02.2011 |
|||
|
Week 7 |
|
3. Project Management
|
Subgroups 101, 102, 201, 202: 21.02.2011 |
Seminar 4 Exercises and cases of Multiobjective Models and Goal Optimisation |
|
|
Group 1 |
Group 2 |
||||
|
24.02.2011 25.02.2011 |
23.02.2011 25.02.2011 |
Subgroups 103, 203: 22.02.2011 |
|||
|
Week 8 |
|
4. Resolution Techniques: Heuristics |
Subgroups 101, 102, 201, 202: 28.02.2011 |
Seminar 5 Exercises and cases of Network Models
|
|
|
Group 1 |
Group 2 |
||||
|
3.03.2011 4.03.2011 |
2.03.2011 4.03.2011 |
Subgroups 103, 203: 01.03.2011 |
|
Date |
Subject |
Seminars |
Case - Exercises |
Comments |
|
|
Week 9 |
|
1. Queue Management
|
Subgroups 101, 102, 201, 202: 07.03.2011 |
Seminar 6 Exercises and Project Management cases |
|
|
Group 1 |
Group 2 |
||||
|
10.03.2011 11.03.2011 |
09.03.2011 11.03.2011 |
Subgroups 103, 203: 08.03.2011 |
|||
|
Week 10 |
|
2. Simulation
|
|
|
|
|
Group 1 |
Group 2 |
||||
|
17.03.2011 18.03.2011 |
16.03.2011 18.03.2011 |
PART 2
1. Presentation of the subject
The area of Quantitative Methods for Decision-Making is based on the scientific method for investigating and helping to take decisions on complex problems in modern organisations. Public and private organisations today face complex management problems which their managers have to solve by taking a decision. Decision-making is the process by means of which a choice is made between alternatives or ways of resolving various situations or problems. These decisions have a very significant effect on organisations' competitiveness and survival.
This second part of the subject (third term) presents an analytical approach to decision theory in two basic contexts: decisions under conditions of risk or uncertainty, and decisions in strategic interaction situations.
The first type of problems is situations where a random external factor affects the result of an agent's decisions: they consider how to represent the agent's uncertainty, attitude towards risk, and preferences. The concepts of lotteries, expected usefulness and aversion to risk will be introduced, and applications such as insurance contracts and financial assets portfolios will be studied. We will analyse the value of information and how sequential decisions are represented.
The second type of problems is situations where the consequences of our decisions depend on the decisions of other agents. These are strategic interaction situations, because each agent's decisions do not only depend on the actions of others, but also affect these other people's decisions. That is the objective of studying game theory. We will learn how to define the elements in a game, the strategies, the logic behind the behaviour of the agents, and the results we can expect from a given type of game (the concepts of solution or equilibrium in games). We will look at examples of economic applications such as decisions in companies in an oligopoly situation, decisions when entering a market, and the contribution to the production of public goods.
2. Competences to be attained
The objective of this course is to provide the essential concepts, tools for analysis, quantitative models, solutions and techniques for solving decision-making problems in various situations.
|
General skills |
Specific skills |
|
Instrumental • Organisation and planning capability. • Knowledge of computer programmes. • Problem-solving. • Search for the appropriate information from various sources. Interpersonal • Oral communication in public. • Teamwork. • Written communication. Systematics • Critical reasoning in reading and in written work and in oral communication. • Analysis and synthesis of qualitative and quantitative information. • Adaptation to new situations. |
Academic and professional • Appreciate the importance and power of Quantitative Methods in decision-making in organisations of the present and future. • Be able to recognise when these methodologies and techniques can be applied, and when they cannot. • Learn how to apply the main techniques and methods to analysis and problem-solving. • Be able to use analytical tools and methodologies based on mathematical models to help in decision-making in business environments. • Be able to use information systems and computer programs to help in decision-making in business environments. • Develop an understanding of the interpretation of the results of a study based on quantitative methods. |
3. Contents
1. Decisions under risk conditions
Alternatives, consequences, objectives, choice.
Uncertainty and risk: the concept of the lottery and probabilities.
Decisions under certainty conditions: preferences, usefulness function, maximisation.
Decisions under risk conditions.
The expected value.
The theory of expected usefulness.
2. Risk aversion
Risk aversion.
Risk premium.
Risk aversion measures.
Assurance: insurance contracts and market
Diversification of assets portfolio.
3. Sequential decisions and information
Sequential decisions.
Decision trees.
Perfect information.
Strategies and backward induction.
Value of information.
Conditional probabilities and updating information.
4. Strategic interaction: decisions and games
Strategic interaction.
Players, rules, results, payments.
Extensive-form games.
Strategies and backward induction.
Normal-form games.
Conflicts, cooperation, efficiency.
5. Games solution and equilibrium
Imperfect information.
Equilibrium in dominant strategies.
Iterated elimination of dominated strategies.
Rationalisable strategies.
Nash equilibrium.
6. Infinite and sequential games and mixed strategies
Infinite series of strategies and reaction functions.
Applications: oligopoly and public goods.
Mixed strategies.
Sequential games.
4. Assessment
The entire subject (two terms):
• The subject Quantitative Methods for Decision-Making consists of two parts: the 1st part in the second term and the 2nd part in the third term. There will be a single overall mark for the subject which will be the average of the two parts, but only if the student has obtained at least 4 out of 10 in each term; the subject is otherwise automatically failed.
• If the subject is not passed in June, if the mark obtained in one of the two terms is 5 or higher, the student may only sit the resit examination in September for the term failed. No mark will be carried forward after September.
Assessment of third term (2nd part of the subject):
1. Continuing Assessment (April - June):
• Exercises and seminars: 20%. Assessment in this section includes: the lists of solved exercises handed in on the stipulated dates; attendance and active participation at the seminars (the lecturer will ask questions and invite students to the blackboard to discuss the solutions to the exercises handed in). Each student must attend the seminars in the subgroup to which they are assigned.
• Partial examination: 10%. The partial examination will take place on Friday 27 May in class time on the topics covered between the beginning of the course and the week before the examination.
• Final examination: 70%. The final examination will be on the entire syllabus. A mark of at least 4 out of 10 must be obtained in this examination (otherwise the entire subject will be failed).
• Attendance at theory classes is not compulsory, and does not provide any points, but points may be deducted from the mark obtained for assessed activities: any behaviour that in the lecturer's opinion interferes with the class will be penalised.
2. September resit:
• Final examination: 80%. The final examination will be on the entire syllabus. A mark of at least 4 out of 10 must be obtained in this examination (otherwise the entire subject will be failed).
• Exercises and seminars: 20%.
Comments:
• Hand-in of a weekly list of exercises solved (starting in the 4th week): no later than 5pm on Friday, in the box located on the door of the seminar group lecturer's office (Sem. 102: 20,163; Sem. 101, 103, 202: 20,165; Sem. 201, 203: 20.1E50 or in the theory class). State your name and seminar group. No e-mail submissions will be accepted.
5. Bibliography and teaching resources
Subjects 1, 2 and 3:
• Transparencias de las clases de teoría (Aula global).
• X. Calsamiglia, Apunts de teoria de les decisions (Aula global).
• H. Varian, Microeconomía intermedia, A. Bosch 2006 (7ª ed.): cap. 12 (La incertidumbre).
Subjects 4, 5 and 6:
• Transparencias de las clases de teoría (Aula global)
• R. Gibbons, Un primer curso de teoría de juegos, A. Bosch 1993: cap. 1 y 2.
• H. Varian, Microeconomía intermedia, A. Bosch 2006 (7ª ed.): cap. 28 (La teoría de los juegos) y 29 (Aplicaciones de la teoría de los juegos).
6. Methodology
The teaching/learning activities will be as follows:
• Face-to-face in the classroom with the complete group. One topic in the syllabus will be discussed each week (see Contents). There will be 20 90-minute classes using the lecture methodology.
• Face-to-face in the classroom with subgroups - Seminars (3 subgroups per group). The exercises on the list handed in the week before will be discussed in each class. There will be 6 90-minute practical classes based on an interactive and participatory methodology: students will be individually invited to discuss the problems and suggest solutions. These activities require preparation before the seminar (exercise lists).
• Individual supervision outside the classroom. For each topic, students must do the appropriate reading and the preparation in the list of exercises.
• Autonomously outside the classroom, both individually and in a team. Students can also learn autonomously by consulting other sources, such as the additional bibliography.
Subject material and information
The support material for the subject and other important information is available in the Aula Global - Moodle as necessary:
- Transparency of each subject for the theory classrooms.
- Bibliography.
- Lists of exercises to be handed in preparation for the seminars.
-
etc.
7. Planning of activities
Date |
Subject |
Seminars |
Exercises |
|
|
Week 1 |
Introduction 1. Decisions under risk conditions |
|
|
|
|
Group 1 |
Group 2 |
|||
|
07.04.2011 08.04.2011 |
06.04.2011 08.04.2011 |
|||
|
Week 2 |
1. Decisions under risk conditions 2. Risk aversion |
|
|
|
|
Group 1 |
Group 2 |
|||
|
14.04.2011 15.04.2011 |
13.04.2011 15.04.2011 |
|||
|
Week 3 |
|
2. Risk aversion |
|
|
|
Group 1 |
Group 2 |
|||
|
28.04.2011 29.04.2011 |
27.04.2011 29.04.2011 |
|||
|
Week 4 |
|
3. Sequential decisions and information
|
|
List 1 hand-in 06.05.11 |
|
Group 1 |
Group 2 |
|||
|
05.05.2011 06.05.2011 |
04.05.2011 06.05.2011 |
|
||
|
Date |
|
Subject |
Seminars |
Exercises |
|
Week 5 |
|
3. Sequential decisions and information 4. Strategic interaction: decisions and games |
101, 102, 201, 202: 09.05.2011 Seminar 1 |
List 2 hand-in 13.05.11 |
|
Group 1 |
Group 2 |
|||
|
12.05.2011 13.05.2011 |
11.05.2011 13.05.2011 |
103, 203: 10.05.2011 Seminar 1 |
||
|
Week 6 |
|
4. Strategic interaction: decisions and games
|
101, 102, 201, 202: 16.05.2011 Seminar 2 |
List 3 hand-in 20.05.11 |
|
Group 1 |
Group 2 |
|||
|
19.05.2011 20.05.2011 |
18.05.2011 20.05.2011 |
103, 203: 17.05.2011 Seminar 2 |
||
|
Week 7 |
|
5. Games solution and equilibrium PARTIAL EXAMINATION 27.05.11 |
101, 102, 201, 202: 23.05.2011 Seminar 3 |
List 4 hand-in 27.05.11 |
|
Group 1 |
Group 2 |
|||
|
26.05.2011 27.05.2011 |
25.05.2011 27.05.2011 |
103, 203: 24.05.2011 Seminar 3 |
||
|
Week 8 |
|
5. Games solution and equilibrium
|
101, 102, 201, 202: 30.05.2011 Seminar 4 |
List 5 hand-in 03.06.11 |
|
Group 1 |
Group 2 |
|||
|
02.06.2011 03.06.2011 |
01.06.2011 03.06.2011 |
103, 203: 31.06.2011 Seminar 4 |
|
Date |
|
Subject |
Seminars |
Exercises |
|
Week 9 |
|
5. Games solution and equilibrium 6. Infinite and sequential games and mixed strategies |
101, 102, 201, 202: 06.06.2011 Seminar 5 |
List 6 hand-in 10.05.11 |
|
Group 1 |
Group 2 |
|||
|
09.06.2011 10.06.2011 |
08.06.2011 10.06.2011 |
103, 203: 07.06.2011 Seminar 5 |
||
|
Week 10 |
|
6. Infinite and sequential games and mixed strategies |
101, 102, 201, 202: 14.06.2011 Seminar 6 103, 203: 14.06.2011 Seminar 6 |
|
|
Group 1 |
Group 2 |
|||
|
16.06.2011 17.06.2011 |
15.06.2011 17.06.2011 |