2025
Partnerships and Cooperation Networks
Name: Partnerships and Cooperation Networks
Code: ECN13499M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Economy
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Regime de Frequência: Presencial
Sustainable Development Goals
Learning Goals
Companies and organizations recognize the importance of cooperation in creating value and competitiveness. Partnerships and networks are motivated by economic, technological, and strategic factors and promote the production and dissemination of scientific and technological knowledge and innovation, factors of high strategic and competitive importance. This course aims to analyze partnerships and cooperation networks between private and/or public companies and organizations, motivated by the economic and strategic value they enhance in terms of competitiveness, growth, or development. By the end of the course, students should be able to:
- Understand the diversity of forms of cooperation between private and/or public agents;
- Identify the advantages of partnerships in project implementation;
- Justify the motivation and relevance of public policies supporting cooperation in the areas of science, technology, and innovation;
- Identify the risks and demands of partnership projects.
- Understand the diversity of forms of cooperation between private and/or public agents;
- Identify the advantages of partnerships in project implementation;
- Justify the motivation and relevance of public policies supporting cooperation in the areas of science, technology, and innovation;
- Identify the risks and demands of partnership projects.
Contents
1. Introduction
2. Economics, markets and cooperation
3. Public policy and cooperation
4. Interfirm cooperation
5. University-industry cooperation and research partnerships
6. Public-private partnerships
2. Economics, markets and cooperation
3. Public policy and cooperation
4. Interfirm cooperation
5. University-industry cooperation and research partnerships
6. Public-private partnerships
Teaching Methods
The in-person sessions are theoretical and practical and combine a blended teaching methodology. The sessions include, on the one hand, a more teaching-focused component through theoretical presentation of the program's topics, accompanied by a strong empirical dimension with examples and application to concrete cases. On the other hand, they include a more learning-focused component through the discussion of texts, statistics, and empirical data, individual responses to practical questions, and the preparation and presentation of an essay on a partnership or network. Students are encouraged to contact external entities to collect empirical data on their work. The teaching method, therefore, seeks a balanced framework between theoretical presentation by the professor and the active involvement of the student in the search and consolidation of information and knowledge. The teaching method also seeks to combine various learning sources, such as the professor's theoretical presentation of subjects, information search and individual assignments, group work in the preparation and presentation of the scientific paper, and the interaction with entities outside the University.
The teaching and learning method includes:
- theoretical presentation in the classroom with PowerPoint slides;
- use of the internet and e-learning tools;
- analysis and discussion of empirical cases based on news, articles and reports;
- completion, presentation, and discussion of group work by students;
- individual practical assignments throughout the semester;
- availability of all individual and group work on the Moodle platform, with the teacher?s notes and suggestions;
Policy on the Use of Artificial Intelligence (AI)
In this course, the use of AI tools is permitted to support learning, literature review, and the creation of educational materials, provided that the student critically validates all information and maintains human control over the content produced. However, there are unacceptable uses of AI because they constitute an ethical and academic violation that will be sanctioned.
Acceptable uses:
- Support for technical writing and review of reports.
- Support for data analysis or hypothesis formulation, with manual verification.
- Support in structuring scientific texts and educational materials.
- Synthesis and organization of scientific evidence, with source confirmation.
- Linguistic or formatting support.
Unacceptable uses:
- Fabrication of references or citations without verification.
- Submitting reports, code, or results produced entirely by AI.
- Displaying data, equations, or references generated without verification.
- Using AI in assessments or exams without faculty authorization.
Misuse will be classified as academic fraud under Article 119 of the Academic Regulations (Code of Conduct, Fraud and Plagiarism).
The teaching and learning method includes:
- theoretical presentation in the classroom with PowerPoint slides;
- use of the internet and e-learning tools;
- analysis and discussion of empirical cases based on news, articles and reports;
- completion, presentation, and discussion of group work by students;
- individual practical assignments throughout the semester;
- availability of all individual and group work on the Moodle platform, with the teacher?s notes and suggestions;
Policy on the Use of Artificial Intelligence (AI)
In this course, the use of AI tools is permitted to support learning, literature review, and the creation of educational materials, provided that the student critically validates all information and maintains human control over the content produced. However, there are unacceptable uses of AI because they constitute an ethical and academic violation that will be sanctioned.
Acceptable uses:
- Support for technical writing and review of reports.
- Support for data analysis or hypothesis formulation, with manual verification.
- Support in structuring scientific texts and educational materials.
- Synthesis and organization of scientific evidence, with source confirmation.
- Linguistic or formatting support.
Unacceptable uses:
- Fabrication of references or citations without verification.
- Submitting reports, code, or results produced entirely by AI.
- Displaying data, equations, or references generated without verification.
- Using AI in assessments or exams without faculty authorization.
Misuse will be classified as academic fraud under Article 119 of the Academic Regulations (Code of Conduct, Fraud and Plagiarism).
Assessment
The assessment structure encompasses both formative and quantitative dimensions. Formative assessment is present in the teacher's comments and suggestions for improvement on all individual and group assignments, in the classroom discussion of specific issues related to group assignments, and in the availability of all assignments on the Moodle platform, which allows students to access other students' work and the teacher's comments and suggestions. Regarding group assignments (scientific articles), assignments submitted to the teacher at the end of the semester and used as the basis for their in-class presentation receive the teacher's comments and suggestions without quantitative grading. Students can submit an improved final version up to 2 to 3 weeks later. This final version will be graded quantitatively.
Continuous assessment regime. In this regime, the quantitative assessment consists of two assessment items, with the group assignment (scientific article) accounting for 60% of the final grade and the written exam accounting for 40%. This seeks to emphasize the student-centered dimension of learning.
Continuous assessment has the following components:
- Group work (60%);
- Written exam (40%);
Final assessment regime. In this assessment regime, there is only one written exam to be taken at the end of the semester:
- Final exam (100%);
In the resit exam, the student can choose to take a written exam (100% weighting) or a written exam (40% weighting) plus an assignment, which can be new or the same one they developed throughout the semester (60% weighting).
If deemed necessary to verify the extent to which the student has developed the knowledge and skills expected for the course unit, the teaching staff may call the student for an oral examination, in accordance with paragraph 13 of article 110 of the Academic Regulations of the University of Évora, ensuring the conditions set out in paragraph 4 of article 116 and paragraph 1 of article 118 of the same Regulations. The oral examination will account for 50% of the final grade for the course.
Continuous assessment regime. In this regime, the quantitative assessment consists of two assessment items, with the group assignment (scientific article) accounting for 60% of the final grade and the written exam accounting for 40%. This seeks to emphasize the student-centered dimension of learning.
Continuous assessment has the following components:
- Group work (60%);
- Written exam (40%);
Final assessment regime. In this assessment regime, there is only one written exam to be taken at the end of the semester:
- Final exam (100%);
In the resit exam, the student can choose to take a written exam (100% weighting) or a written exam (40% weighting) plus an assignment, which can be new or the same one they developed throughout the semester (60% weighting).
If deemed necessary to verify the extent to which the student has developed the knowledge and skills expected for the course unit, the teaching staff may call the student for an oral examination, in accordance with paragraph 13 of article 110 of the Academic Regulations of the University of Évora, ensuring the conditions set out in paragraph 4 of article 116 and paragraph 1 of article 118 of the same Regulations. The oral examination will account for 50% of the final grade for the course.
Teaching Staff
- Adão António Nunes de Carvalho [responsible]
Accreditations and Certifications
