Tuesday, September 26, 2006

Plenary session

• Indicator development required for science, technology and innovation policies in an era of democratizing innovation
• Developments in EU statistics on science, technology and innovation: Taking stock and moving forward towards evidence based policy analysis
• Towards understanding the impacts of science, technology and innovation activities

Indicator development required for science, technology and innovation policies in an era of democratizing innovation

Biographical Note

Eric von Hippel manages the Innovation and Entrepreneurship Group at MIT. von Hippel is known for his research into the sources of innovation, finding that product development is rapidly shifting away from product manufacturers to product "lead users" in the Internet Age. This shift suggests major changes to innovation indicators would be of value.

Abstract

Innovation is rapidly becoming democratized. Users, aided by improvements in computer and communications technology, increasingly can develop their own new products and services. User innovation, the data show, is strongly concentrated among "lead users". These lead users —both individuals and firm–soften freely share their innovations with others, creating user–innovation communities and a rich intellectual commons. The trend toward democratized innovation is visible both in information products like software and also in physical products. Lead–user innovation provides a valuable feedstock for manufacturer innovation, and produces an increase in social welfare relative to a manufactureronly–innovation system.

Freely–revealed innovations by users forms the basis for a user–centric innovation system that is so robust that it is actually driving manufacturers out of product design in some fields. At the same time, much of this user–centered innovation activity involves "learning by doing" by users rather than R&D. As a result, this important type of activity – which may prove to account for most of the innovation–related expenditures by private individuals and firms – is not easily captured by current indicators. I explain what is known about the phenomenon of democratized, user–centered innovation including open–source in this paper in order to provide a context for those wishing to develop appropriate novel indicators for science, technology and innovation policies.

Developments in EU statistics on science, technology and innovation: Taking stock and moving forward towards evidence based policy analysis

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Biographical Note

Reinhilde Veugelers is professor of Managerial Economics, Strategy and Innovation at the Katholieke Universiteit Leuven. She was a visiting scholar at Northwestern University's Kellogg Graduate School of Management, at Sloan School of Management (MIT), Stern Business School (NYU), ECARES/Université Libre de Bruxelles, Université de Paris I (Panthéon–Sorbonne), Universitat Pompeu Fabra & Universitat Autonoma de Barcelona, Universiteit Maastricht.

With her research concentrated in the fields of industrial organisation, international economics and strategy and innovation, she has authored numerous publications on multinationals, R&D cooperation and alliances, industry–science links and market integration in leading international journals. She obtained research grants from the Belgian Science Policy Office, the European Commission (DG Research and DG ECFIN) and the Flemish Government (VRWB–IWT).

She is co–promotor for the Flemish Government "Steunpunt" on R&D Statistics, a CEPR Research Fellow (London) and currently an Economic Advisor at the Bureau of European Policy analysis (BEPA) of the European Commission, on leave from the KU Leuven (2004–2008).

Abstract

Over the past ten years, the official statistics on Science, Technology and Innovation in the EU have progressed, but still lack basic features of a systemic framework for measuring the knowledge economy and feeding into evidence based policy analysis. Some experiments with 'process indicators' (describing 'knowledge flows' or 'research networks') and 'micro–level indicators' (monitoring the behaviour and performance of key actors such as firms, universities), have tried to remediate to this problem. These pilots, however, did not yet result in internationally comparable data and methodologies.

The aim of this discussion is to indicate where the main gaps are in the current Statistics on Science, Technology and Innovation, and to propose ways of improving the current situation. Starting from a broad perspective on assessing beyond R&D inputs the innovative capacity of nations, it evaluates the stock of indicators currently used in the EU policy process. Although the set of indicators clearly look like being inspired by the specific weaknesses of the EU innovative capacity and the 'systems' approach towards improving this capacity, we are still far away for a smooth process of evidence based policy analysis. Work to be done in future includes (i) improving the basic indicators for innovation input and output; (ii) develop new indicators, most notably in the area of industry–science links and the international creation and diffusion of know–how; (iii) disaggregate the data reporting at sectoral/technology; geography and institutional level.

But beyond the "creation" of better statistics, it is important to also improve on the "diffusion" and exploitation of S&T statistics. The process of creation, diffusion and exploitation of S&T statistics should be less linear, involving more interactions between policy analysts, researchers and statisticians;

Towards understanding the impacts of science, technology and innovation activities

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Biographical Note

Heidi Ertl is the head of Statistics Canada's Information Society Research and Analysis unit, which develops socio–economic indicators of connectedness and conducts research and analytical work in the areas of information and communications technology and the Digital Divide. Ms. Ertl is also responsible for the measurement and analysis of Canada 's Information and Communications Technology (ICT) sector. She has both authored and edited several studies on the Information Society, and is involved in a number of related international development and capacity–building activities. Ms. Ertl joined Statistics Canada eight years ago after completing a Master's degree in Economics at McMaster University, Hamilton, Canada.

Anik Lacroix is Chief of the Information Society Section at Statistics Canada, the section responsible for the collection, integration and analysis of information regarding the supply and demand of Information and Communication Technologies and the impacts of those technologies on economy and society. Ms Lacroix has been at Statistics Canada for the last 15 years. She has acquired a strong expertise in a variety of areas such as health, environment and the information society. She has a Master's degree in economics from Université de Montréal, Montréal, Canada.

Abstract

Much has been accomplished with respect to basic measures of science, technology and innovation (STI) in Canada; however the focus is now shifting to more sophisticated measures of the potential value added and costs of such activities. This paper will present Canadian initiatives towards better understanding the social and economic outcomes, linkages and longer term impacts associated with STI activities. In particular, it will discuss approaches and measures currently used by Statistics Canada and others,map potential paths for the future, and highlight the importance of this work for policy makers and for the application of international standards. 

Two key questions will be addressed with a view towards understanding the impacts of various STI activities:

1. How can existing approaches or measures be used to understand impacts?

A number of initiatives are currently underway which use existing measures of readiness and intensity to shed light on impacts. For example, linkages have been made between ICT use and a number of social and economic outcomes, including income, literacy and obesity. The impact of ICT on communication and spending patterns, as well as on people's work and leisure time, are also topics that are being explored, while measures of the 'digital divide' are used to gain insight into the uneven use (and users) of technology. Measures of value added, R&D, and innovation by the ICT sector can also be used to examine impacts on the Canadian economy.

The impacts of advanced technology are being explored by linking surveys of advanced technology use to production surveys. These data linkages have demonstrated that manufacturing establishments using advanced technologies outperform those that do not. Moreover, advanced technology adoption in the manufacturing sector has been shown to lead to better jobs and higher salaries/wages than non–adoption. Other impacts include gains in market share at the expense of non–adopters and growth in labour productivity. A section of the paper will also be devoted to measures of biotechnology activities that begin to address social benefits and detriments.

2. What new approaches or measures are needed to gain a better understanding of impacts?

Although the work on understanding impacts has been advancing, it remains in the very early stages. Many of the social and economic impacts of STI activities are still evolving and the longer term implications have not yet been fully absorbed. This makes the assessment of STI activities and their broader impacts on the economy and society an even greater challenge.

Policy makers are asking for measures of the return on science and technology investment, for example, but it is not yet clear what those measures should be. The paper will explore approaches and measures needed to address the results and outcomes of these investments. Work on intellectual property management in the public sector and results from a new survey on business incubators will also give rise to alternative approaches and measures of impacts.

Other issues include the characteristics of R&D performers versus non–performers, whether technology adopters are more innovative than non–adopters, the changing behaviours associated with technology use, and the impacts of commercialization. 

Finally, the paper will identify gaps in the measurement of impacts and propose approaches to close these gaps. The importance of linking measures to policy will also be addressed.