Work Plan (Dissertation / Work Project /Internship)

Code:

2GE10

Acronym:

WP

Keywords
Classification	Keyword
OFICIAL	Management Studies

Instance: 2018/2019 - 1S

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

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIM	46	Bologna Official Syllabus	2	-	7,5	56	202,5

Teaching language

English

Objectives

To allow students to apply the knowledge acquired in the first year of the Master in Management programme, in preparing their dissertation plan.

 

 

Learning outcomes and competences

At the final essay, the student is expected to:

- clearly identify the research question(s) and discuss the gap(s) he/she wants to address in the master dissertation;

- fully perform a literature review and systematize the relevant literature on the chosen topic;

- identify the most suitable methodology to address the research problem and questions.

Working method

Presencial

Program

Part I. RESEARCH PROCESS

1 – Stages of the research process (1/2 class)

1. Research question;
2. Exploratory readings;
3. Theoretical framework: theories and concepts;
4. Model analysis and research hypotheses construction;
5. Methodology;
6. Collecting and treating the data;
7. Conclusions.

Bibliography:

- Hart, C. (2008), Doing your Masters Dissertation: Realizing your Potential as a Social Scientist, London: SAGE.

2 – Scientific writing (1/2 class)

1. Rules for presentation of dissertations and reports;
2. How to structure a scientific work;
3. Academic integrity.

Bibliography:

- Hart, C. (2008), Doing your Masters Dissertation: Realizing your Potential as a Social Scientist, London: SAGE.

- Saunders, M., P. Lewis and A. Thornhill (2002), Research Methods for Business Students, 3^rd ed., Edinburgh: Prentice-Hall.

3 – Bibliometrics (1 class) Note: Students are advised to bring their Laptops to class.

1. Key concepts (bibliometrics, scienciometrics, meta-analysis);
2. Bibliometrics as a tool for literature review;
3. Data, sources, variables & methods;
4. Practical application of bibliometrics using Scopus Sci Verse and Web of Science bibliographic databases.

Bibliography:

- Castro e Silva, M. and A. A. C. Teixeira (2012), "Methods of assessing the evolution of science: a review ", European Journal of Scientific Research, Vol. 68(4): 616-635.

- Cronin, B. and C. R. Sugimoto (eds.) (2014), Beyond Bibliometrics: Harnessing Multidimensional Indicators of Scholarly Impact, London: MIT Press.

- Gingras, Y. (2016), Bibliometrics and Research Evaluation: Uses and Abuses, Cambridge: MIT Press.

- Osareh, F. (1996), Bibliometrics, Citation Analysis and Co-Citation Analysis: a review of analysis, in Libri., vol.46: 149-158.

Part II. RESEARCH METHODS

4 – Sampling and surveys (1 class)

1. Data collection: Introduction;
2. Steps of research process;
3. Data collection;
4. Sampling (first concepts)
5. Sample survey/questionnaires
6. General overview of some Statistical Databases available in FEP.

Bibliography:

- Cohen L., L. Manion and K. Morrison (2005), Research Methods in Education, 5^th ed., Taylor & Francis.

- Norland-Tilburg, E. V. (1990), “Controlling error in evaluation instruments”, Journal of Extension, 28(2) (http://www.joe.org/joe/1990summer/tt2.html).

-Trochim, W. M. K. (2006), The Research Methods Knowledge Base, 2^nd (http://www.socialresearchmethods.net/kb/).

5A – Qualitative Methods (3 classes)

1. Qualitative research;
2. Theoretical Frameworks: narrative inquiry, phenomenology, ethnography, generic qualitative inquiry, action-research;
3. Qualitative designs;
4. Data collection: observation, interview, focus-group;
5. Data analysis: Content analysis (using or not NVivo11);
6. Advantages & disadvantages of qualitative research;
7. Ethical considerations.

Bibliography:

- Patton, M. (2014), Qualitative Research and Evaluation Methods, 4^th ed., London: Sage Publications.

5B – Quantitative Methods (2 classes)

1. Parametric and non parametrical statistical tests:
1. Introduction;
2. Types of data;
3. Descriptive statistics;
4. Distributions, inference and hypothesis testing (assumptions and applications);
5. Parametrical tests: T-Student test for 1 population; T-Student test for 2 independent populations; T-Student test for 2 paired samples; ANOVA.
6. Non parametrical tests: Normality tests; Wilcoxon test for 1 population; Mann-Whitney test for 2 independent populations; Wilcoxon test for 2 paired populations; Kruskall-Wallis test for k independent populations.
7. Correlations;
8. Chi-Square independence test.
2. Multivariate data analysis:
1. Data matrix and variables;
2. Types of methods;
3. Multiple Regression;
4. MANOVA;
5. Discriminant analysis;
6. Factorial analysis;
7. Principal component analysis;
8. Cluster analysis: Hierarchical method; K-means.

Bibliography:

- Conover, W. J. (1999), Practical Nonparametric Statistics, 3^rd ed., New York: John Wiley & Sons.

- Everitt, B. S. & G. Dunn (2013), Applied Multivariate Data Analysis, 2nd ed., Wiley.

- Hair Jr., J. F., W. C. Black, B. J. Babin & R. E. Anderson (2010), Multivariate Data Analysis – A Global
Perspective, 7th ed., Pearson Prentice Hall.

- Keller, G. (2008), Statistics for Management and Economics, Thomson.

- Sharma, S. (1996), Applied Multivariate Techniques, Wiley.
5Bi.

5Bi. - Quantitative methods: Social network analysis, opinion mining, sentiment analysis (1 class)

1. Social network analysis. Social networks: interactions between actors. Professional social networks, e.g. LinkedIn. Social network analysis:
2. The role of actors in the network: centralities and influence;
3. Communities and interactions;
4. Information diffusion in social networks.
5. Sentiment analysis:
6. Opinions in the digital age: social media, blogs, tweets, etc.;
7. Text mining: identifying entities, and polarity.

Bibliography:

- Liu, B. (2012), Sentiment Analysis and Opinion Mining, Human Language Technologies.

- Zafarani, R., M. Ali Abbasi and H. Liu (2014), Social Media Mining, Cambridge University Press.

5Bii. - Econometric Methods (1 class)

1. Object and method of Econometrics;
2. Brief revision of the linear regression model;
3. Binary choice models (logit/probit);
4. Time series models;
5. Panel data models.

Bibliography:

- Asteriou, D. & S. G. Hall (2015), Applied Econometrics, 3rd ed., Palgrave.

- Griffiths, W. E., R. C. Hill & G. C. Lim (2012), Using EViews for Principles of Econometrics, 4th ed., John
Wiley & Sons.

- Gujarati, D. (2014), Econometrics by Example, 2nd ed., Palgrave.

- Gujarati, D. N. & D. C. Porter (2009), Basic Econometrics, 5th ed., McGraw-Hill.

- Heij, C., P. De Boer, P. H. Franses, T. Kloek & H. K. Van Dijk (2004), Econometric Methods with
Applications in Business and Economics, Oxford University Press.

- Hill, R.C., W. E. Griffiths & G. C. Lim (2012), Principles of Econometrics, 4th ed., John Wiley & Sons.
 

Part III. TUTORIALS and PRESENTATIONS

Mandatory literature

Saunders, Mark; Lewis, Philip and Thornhill, Adrian; Research Methods for Business Students, Prentice-Hall, Edinburgh, 2002
Bryman, Alan; Bell, Emma; Business Research Methods, Financial Times / Prentice Hall, London, 2006
To be Defined by the Lecturers of the Thematic subjects; Quantitative and Qualitative research methods

Teaching methods and learning activities

- Teaching sessions.

- Tutorial sessions for reflection, discussion and motivation for future work of dissertation project.

- Presentation and discussion of dissertation themes, intermediate dissertation project draft and final project.

 

Evaluation Type

Distributed evaluation without final exam

Assessment Components

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

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de projeto	60,00
Estudo autónomo	20,00
Frequência das aulas	33,00
Trabalho de investigação	89,50
Total:	202,50

Eligibility for exams

All students can attend the exam.

Calculation formula of final grade

Assessment Type and Calculation of final grade

• 100% of the final grade: Final essay delivery (Dissertation proposal) – Report.

Penalties

• 1 page summary containing the research topic. If the student does not send an adequate summary until the date defined in the schedule, 1 point (out of 20) will be deducted from the final grade.
• Research Topic/Idea presentation. If the student does not make this presentation according to the recommended guidelines, 1 point (out of 20) will be deducted from the final grade.
• 1st essay: Report containing information about the research topic (reformulated, if needed). If the student does not send this 1st Essay according to the recommended guidelines until the date defined in the schedule, 2 points (out of 20) will be subtracted from the final grade.
• Students’ oral presentation of the dissertation project. If the student does not make this presentation according to the recommended guidelines, 2 points (out of 20) will be deducted from the final grade.

Classification improvement

Not available