Market Analysis

Code:

2GEC01

Acronym:

AM

Keywords
Classification	Keyword
OFICIAL	Management Studies

Instance: 2024/2025 - 1S

Active?	Yes
Responsible unit:	Management
Course/CS Responsible:	Master in Sales Management

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
GCOM	32	Official Bologna Syllabus	1	-	7,5	56	202,5

Teaching language

Suitable for English-speaking students

Objectives

Master the main methods and techniques useful in market research and in economic and business time-series analysis.

Understand the relevance of information in business studies : models' design, information planning and surveys, data treatment, analysis of results and presentation of reports.

Buiding quantitative models and data analysis using specialized software (SPSS and EVIEWS).

Read and produce scientific reports in the Business and Management domains.

Learning outcomes and competences

Design, plan, build and analyse relevant information for companies and studies on management and commercial subjects.

Know the scientific methodology to perform market studies and professional and academic reports.

To know surveys' procedures, scales building and proposition of questionnaires.

To know methods and techniques on data analysis.

Use specialized software regarding data analysis.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Knowledge on Statistics and Multiple Linear Regression (at FEP's Economics or Management Bachelor level)

Program

 

• 1- Introduction: Market research and studies on Commercial Management 

 

(Session 1)

• 2- Sales forecasting and quantitative studies on commercial series. Applied study using real data

 (Sessions 2, 3, 4 e 5)

 

• 3- Market studies and research questionnaire. Applied case study

(Sessions 5 e 6)

 

• 4- Surveys and sampling 

(Sessions 7 e 8)

 

• 5- Data analysis : factorial and cluster methods. Applied case study

(Sessions 10 e 11)

• 6- Complementary explicative models. Multiple regression, ANOVA and Conjoint analysis. Applied case study

 (Sessions 13 and 14)

  

• 7- Scientific articles (3) study and discussion

(Sessions 9 and 12)

 

 

Mandatory literature

Malhotra; Marketing Research, Mc-Graw Hill, 2007

Complementary Bibliography

Hair, Black, Babin, Anderson and Tatham; Multivariate data analysis, 7th ed.,, 2010, Prentice-Hall, 2010
Hanke, Wichern, Reitsch; Business Forecasting, Prentice Hall, 2001
Levy and Lemeshow; Sampling of populations - methods and applications, Wiley, 1991

Teaching methods and learning activities

- Classes with mandatory attendance;
- case studies with real data and specialised software;
- participation of students - reports and presentations.

Software

EVIEWS
SPSS

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	80,00
Trabalho escrito	20,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Apresentação/discussão de um trabalho científico	9,00
Estudo autónomo	42,00
Frequência das aulas	42,00
Trabalho escrito	15,00
Total:	108,00

Eligibility for exams

Attending and participation on classes

Calculation formula of final grade

There are two opportunities to pass the discipline.

1- Normal/regular examination – by “Distributed evaluation with final exam” .

This evaluation procedure includes a written global exam about the program of the course (“final exam”) with a weight of 80 % and an assignment/report weighting 20%.

Formula : Written final exam (80%) +Assignment/ report and class attendance (20%)

NOTE : The written final exam includes questions (with a weight of 40%) on three articles which are to be presented by the students and discussed during classes.

2- Appeal/ reset exam

The evaluation is done by a written final exam weighting 100%.

Examinations or Special Assignments

Students must :

- work on a report (by example: modelling / forecasting  a commercial series, an applied case study with real data);

- study 3 proposed articles which are presented by students and discussed during class;

- participate in models design and data analysis of specific subjects.

Internship work/project

Not apply

Special assessment (TE, DA, ...)

Not apply

Classification improvement

Students may improve rating doing the appeal/reset exam and in this case the written final exam weights 100%.

Observations

Nothing to add.