Postgraduate Course: Innovation Systems Theory and Practice (PGSP11426)
|School||School of Social and Political Science
||College||College of Humanities and Social Science
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Available to all students
|Summary||This course provides an introduction to the theory of innovation systems (national, sectoral and technological etc) using a range of case examples in national and international contexts, covering both high and low resource settings. The course also provides students with the necessary knowledge, skills and understanding to critique and apply methods of foresight and scenario analysis. The course requires no prior knowledge of the area, and will provide students with a foundational understanding of the theories and practices underpinning technological change and innovation from a systems perspective. The focus will be on the relationship among a variety of possible configurations for innovation in different industrial sectors, the processes of structural change, and evaluation of innovative performance.
Is technological innovation contributing to the removal of geographical boundaries? The web, the globalisation of financial markets, the increasing delocalisation of manufacturing towards low-wage countries, the standardisation of intellectual property rights, all are seen as generating a global economy in which nation states and local constituencies have become less relevant. Local economies, however, are characterised by different infrastructures for research, innovation and production and continue to display different rates of technological change and economic growth.
Having emerged in parallel with efforts in economics to include technological change and knowledge dynamics into endogenous growth models, the development of systemic approaches to innovation can be seen as an attempt to provide an answer to this apparent paradox. From an interdisciplinary and historical perspective, this course provides an introduction to the theory of innovation systems (national, sectoral and technological etc.) using a range of case examples in national and international contexts, covering both high and low resource settings. The course provides students with the necessary knowledge, skills and understanding to critique and apply methods of foresight and scenario analysis. The course requires no prior knowledge of the area, and provides students with a foundational understanding of the theories and practices underpinning technological change and innovation from a systems perspective. The focus will be on the relationship among a variety of possible configurations for innovation in different industrial sectors, the processes of structural change, and evaluation of innovative performance.
i. Innovation Systems Theory Overview
In this session you will be introduced to innovation and how it provides a better explanation for why some firms, sectors, regions and nations did better than others. Given that innovation in firms does not occur in isolation, you will be introduced to the systemic nature of innovation through the concepts of national, regional and sectoral systems of innovation. You will be introduced to relationships and linkages between and amongst firms, industrial clusters, sectors, regions and nations in different innovation ecosystems. The focus will be on systems of innovation because of their holistic and interdisciplinary approach to innovation and learning, which is not necessarily constrained by geographic boundaries.
ii. Innovation Systems for energy and environment
In this session you will cover the challenges of conceptualising and analysing the complexity surrounding innovations systems, with particular reference to energy and the environment. You will be introduced to the tensions surrounding environmental sustainability, energy production and innovation. This will be done by looking at technology development cycles, innovation processes and how actors, institutions and networks link up in the system. The focus on renewable energy provides a dual analysis of innovation systems in energy and the environment. You will be introduced to the tensions arising from aligning innovation incentives with energy and environmental policies, within the context of sometimes divergent economic policies/agendas.
iii. Innovation Systems in Low Resource Settings
In this session you will be introduced to the tensions and dynamics of introducing the National Systems of Innovation framework developed in resource-rich settings to resource-limited settings with different development thrusts. The focus will be on institutional, infrastructural, technological and skills challenges in application of the NIS concept. You will be introduced to lessons surrounding the heated debates on choice of developmental trajectories and whether frameworks developed under different economic and political environments should be adopted without major reengineering. This is in light of the global push by international development bodies and funders to adopt national systems of innovation approaches to policy making. You will develop an understanding of the spaces and roles that policy makers, industrialists (and their associations) and academia can play in designing context specific systemic approaches to innovation.
iv. Introduction to Foresight and Scenario Analysis Methods (Prof. Joyce Tait)
Impacts and future trajectories of innovation in life sciences are often uncertain, complex and dynamic. There is no simple way to predict what technologies will become world-leading, which business models and regulatory systems will enable successful transition to market, and how value will be created at different stages of product development. This makes it difficult for companies, and public sector organisations, to know where to target investments and policies. No crude rule of the market, and no single government initiative, can reliably predict innovation futures. Furthermore, factors outside science and technology innovation systems (regulatory, policy, markets, sources of finance, stakeholders etc) will affect how the bioeconomy as a whole performs and whether individual products succeed.
In this session, you will be provided with a general introduction to a range of foresight and scenario methods, how and why they were developed, and the key benefits and limitations. We will explore how foresight and scenario analysis has been applied in a variety of different ways, with different starting points and outcomes, in both policy and industry contexts. The importance of identifying the most relevant drivers for foresight, and using the most appropriate scenarios, will become clear in this session and provide a foundation for conducting your own foresight analysis for the assignment for this course.
v. Making Foresight Methods Work- Student led presentations
This session is preparation for the assignment for this course. Students will be expected to provide a short presentation on their chosen Foresight and/or Scenario planning case study and get feedback from fellow students and the course organisers.
The course, which has no prerequisites, is delivered through a 5-week lecture and seminar discussion format. The two-hour sessions will typically consist of a short lecture (introducing the key themes of the week's topic and the core readings provided), followed by an hour and a quarter of classroom discussion and/or student-led presentations. Each week's class will typically cover conceptual, theoretical and empirical material related to the topic. Discussion with staff and with others on the course is a key element in learning. The course is cross-discipline and open to students with backgrounds in social sciences, natural sciences and the humanities.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| None
Information for Visiting Students
|High Demand Course?
Course Delivery Information
|Academic year 2018/19, Available to all students (SV1)
||Block 2 (Sem 1)
|Learning and Teaching activities (Further Info)
Seminar/Tutorial Hours 30,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||3000 word Essay (100%)
||Assessment will be based on a Foresight/Scenario case of the student's choice or an essay. The topic could be chosen from one of cases included in the Additional Readings for Lecture 9, or students may choose their own essay topic with approval from the course organiser. If students wish to collaborate on the development of a single case study, they can each develop an essay covering one aspect of the case in contribution to a joint conclusion (essays to be marked on an individual basis). The essay will be of no more than 3000 words.
|No Exam Information
On completion of this course, the student will be able to:
- Critical understanding of the innovation system, in the context of competing theoretical approaches, including the recent focus on innovation ecosystems, and in-depth knowledge and understanding of the key factors determining system behaviour.
- Knowledge and understanding of the key components of an innovation system ¿ its enablers and constraints - and how the overall system functions in different technology and industry sectors
- Ability to critically analyse, and use, foresight as a method to construct and plan for particular technology futures.
- Critical awareness of the challenges in planning and coordinating an innovation policy strategy for economic development.
|Breschi S and Lissoni F (2001) Knowledge Spillovers and Local Innovation Systems: A Critical Survey, ICC, 10 (4), 975-1005.|
Cooke P (2001), Regional Innovation Systems, Clusters, and the Knowledge Economy, ICC, 10 (4): 945-974.
Foresight (2011) The Future of Food and Farming: challenges and choices for global sustainability. London: Government office for Science. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/288329/11-546-future-of-food-and-farming-report.pdf
Jefferson R. 2012. Shell scenarios: What really happened in the 1970s and what may be learned for current world prospects. Technological Forecasting and Social Change 79(1): 186-97.
Malerba F (2002), Sectoral systems of innovation and production, Research Policy 31(2), 247-264.
Maskell P. (2001), Towards a Knowledge-based Theory of the Geographical Cluster, ICC, vol. 10 (4), 921- 943.
Metcalfe S, and Ramlogan R, 2005 Innovation Systems and the Competitive Process in Developing Countries, The Quarterly Review of Economics and Finance, 48, 433-446.
Nelson RR, Nelson K (2002), Technology, institutions, and innovation systems Research Policy, 31(2), 265-272.
UK Synthetic Biology Roadmap Coordination Group (2012) A Synthetic Biology Roadmap for the UK. http://www.rcuk.ac.uk/RCUK-prod/assets/documents/publications/SyntheticBiologyRoadmap.pdf
Weber E, Eriksson A and K Matthias. 2008. Adaptive Foresight: Navigating the complex landscape of policy strategies. Technological Forecasting and Social Change. 75:462-482.
Wilkinson A. 2009. Scenarios Practices: In Search of Theory. Journal of Futures Studies 13:107-114.
|Graduate Attributes and Skills
|Course organiser||Dr Geoffrey Banda
Tel: (0131 6)50 6391
|Course secretary||Miss Kate Ferguson
Tel: (0131 6)51 5122