B5587 - Geography of Innovation

Learning outcomes

Upon completion of the course, students will be able to: 1. apply key innovation concepts in geographical analyses with an economic background; 2. understand the link between innovation outcomes and regional preconditions, structures, and actors; 3. discuss the main theoretical approaches in geography of innovation studies and their implications for different types of regional innovation systems; 4 examine multiscalar knowledge flows and how they can generate innovation outcomes in regions characterized by different geographical location and levels of socioeconomic development; 5. discern innovation policies and reflect on their applicability in various geographical contexts.

Course contents

In particular, the course will focus on the concept of innovation, its evolution over time and the main dynamics that determine its degree and main effects at the territorial level.

At the end of the course, students will have learned the main notions on the subject and will be able to use different methodological approaches in the field of the geography of innovation.

The course aims to provide a broad overview of the main themes that have emerged in the geography literature, including:

- the definition of innovation and its spatial diffusion;

- the impact of different innovation models at the spatial level;

- the role of innovation policy as a possible tool to reduce spatial disparities;

- innovation networks and different innovation systems at various geographical scales;

- knowledge bases and their contribution to the spatial and relational innovation dynamics;

- the role of universities in innovation processes and competitiveness at territorial level.

Readings/Bibliography

Texts to study for attending students:

Course book:

Fagerberg, J. (ed.), Mowery, D.C. (ed.) (2009), The Oxford Handbook of Innovation. Oxford Academic. DOI: https://doi.org/10.1093/oxfordhb/9780199286805.001.0001. Only chapters 1, 3, 6, 7, 8, 11, 12, 14 and 18.

Coe, N. M., Advanced Introduction to Global Production Networks. Edward Elgar

Academic articles and book chapters:

Several readings (academic articles and book chapters) on specific topics will be offered during the course, enabling students to prepare for the presentation to be given in class and the written test (in this regard, see the section “Assessment Methods”).

 

Non-attending students must study all the texts listed above. In addition, non-attending students must study all the texts listed below: 

Calignano, G., & Quarta, C. A. (2014). University of Salento’s transactional relations: assessing the knowledge transfer of a public university in Italy. ERDKUNDE, 68(2), 109–123. https://doi.org/10.3112/erdkunde.2014.02.03 

Castellacci, F., & Archibugi, D. The technology clubs: The distribution of knowledge across nations, Research Policy, Volume 37(10): 1659-1673, ISSN 0048-7333, https://doi.org/10.1016/j.respol.2008.08.006

Chesbrough, H.W. (2003), The Era of Open Innovation, MIT Sloan Management, Review VOL.44 NO.3: 35-41.

Feldman, M.P., Kogler, D.F. Chapter 8 - Stylized Facts in the Geography of Innovation, Editor(s): Bronwyn H. Hall, Nathan Rosenberg, Handbook of the Economics of Innovation, North-Holland, Volume 1, 2010, Pages 381-410, ISSN 2210-8807, ISBN 9780444519955, https://doi.org/10.1016/S0169-7218(10)01008-7

Foray, D., & Lissoni, F., Chapter 6 - University Research and Public–Private Interaction, Editor(s): Bronwyn H. Hall, Nathan Rosenberg, Handbook of the Economics of Innovation, North-Holland, Volume 1, 2010, Pages 275-314, ISSN 2210-8807, ISBN 9780444519955, https://doi.org/10.1016/S0169-7218(10)01006-3 .

Giuliani, E. (2007), The selective nature of knowledge networks in clusters: evidence from the wine industry, Journal of Economic Geography, 7(2): 139–168, https://doi.org/10.1093/jeg/lbl014

Feldman, M.P., Kogler, D.F. Chapter 8 - Stylized Facts in the Geography of Innovation, Editor(s): Bronwyn H. Hall, Nathan Rosenberg, Handbook of the Economics of Innovation, North-Holland, Volume 1, 2010, Pages 381-410, ISSN 2210-8807, ISBN 9780444519955, https://doi.org/10.1016/S0169-7218(10)01008-7

Lundvall, B. (2007). National Innovation Systems—Analytical Concept and Development Tool. Industry and Innovation, 14(1), 95–119. https://doi.org/10.1080/13662710601130863

Mathieu, A. (2011). "University-Industry interactions and knowledge transfer mechanisms: a critical survey," Working Papers CEB 11-015, ULB -- Université Libre de Bruxelles.

Trippl, M., Sinozic, T., & Lawton Smith, H. (2015). The Role of Universities in Regional Development: Conceptual Models and Policy Institutions in the UK, Sweden and Austria. European Planning Studies, 23(9), 1722–1740. https://doi.org/10.1080/09654313.2015.1052782

Tödtling, F., Isaksen, A., Trippl, M. (2018). Innovation policies for regional structural change: Combining actor-based and system-based strategies. In A. Isaksen, R. Martin, & M. Trippl (Eds.), New avenues for regional innovation systems – Theoretical advances, empirical cases and policy lessons (pp. 221–238). Springer.

Teaching methods

Lectures; in-class presentations followed by discussion; writing a paper in academic style..

Assessment methods

Attending students (in-class presentation and discussion; written test):

Attending students must prepare a presentation to be given in class that includes a critical discussion of one of the topics covered in the course or an illustration of a case study. In either case, the topic will be agreed with the lecturer. At the same time, attending students will be expected to discuss another student's presentation. The manner of presentation and discussion will be explained in detail during the first class.

The written examination will consist of a paper. The topic of the paper will be the same as the in-class presentation and will therefore consist of a critical discussion of one of the topics covered in the course or an illustration of a case study. The length of the paper will be approximately 4,000 words and must be written in academic style. If the number of attending students permits, in-class laboratory activities will be planned with the aim of deepening the subject and monitoring the progress of each student in preparation for the submission of the final paper, which will be assessed.

For students who have attended at least 80% of the scheduled classes, the final grade will be based on the following parameters

• 30% determined by the quality of the presentation, critical analysis of the chosen topic or case study treated, as well as the quality of the discussion of the paper presented by another student;
• 70% determined by the quality of the written paper in academic style.

 

Non-attending students (oral examination):

Oral examination through which overall preparation on the topics covered in the course will be assessed. The texts to be studied are indicated in the “Readings/Bibliography” section.

 

REFUSAL OF THE GRADE: The student who passes the exam can refuse the grade only once. This principle is in accordance with the provisions of the University Teaching Regulations, art. 16, co. 5, modified by the resolution of the Academic Senate approved by the Board of Directors in February 2018: "in the event of a positive outcome, the student can ask to refuse the grade. The refusal must be granted by the professor at least once for each individual course". After a refusal, any positive outcome will be recorded.

Candidates can only use the grade obtained in the last attempt to pass the exam.

Furthermore, with regard to the evaluation method:

- Attending students who refuse the grade will submit a new paper that must deal with a completely different topic from the one presented in class and originally agreed with the teacher for the drafting of the first paper. Furthermore, in the event of a new attempt, attending students will have to work independently, but will be able to avail themselves of the support of the teacher in defining the research question and in the development of the paper. The new paper will contribute 70% of the final grade, while the presentation given in class will continue to contribute the remaining 30%.

- Non-attending students who refuse the grade will take a new oral exam.

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Final grade:

• Minimum analytical skills → 18-19;
• Good analytical skills → 20-24;
• Very good analytical skills → 25-29;
• Excellent analytical skills → 30-30L

Teaching tools

Computer and projector.

Office hours

See the website of Giuseppe Calignano