10/17/2003 Salazar & Holbrook 1 CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology A DEBATE ON INNOVATION SURVEYS Paper presented at the Conference in honour of Keith Pavitt “What do we know about innovation?” Mónica Salazar & Adam Holbrook Vancouver

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology A little bit of history Late 80s early 90s: first experiments of innovation surveys in Europe. Oslo Manual first published 1992 (OECD, Eurostat), second edition 1996, a new revision underway. First Community Innovation Survey (CIS) 1992; CIS II 1999, CIS III Mid 90s: first experiments of innovation surveys in Latin America. Bogotá Manual published 2000.

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Why do we need a debate? Do innovation surveys provide the information required by policy- makers (and researchers) in order to understand innovation processes? Do the surveys provide adequate information to analyse industrial and regional clusters? Do the surveys provide useful information that facilitate the analysis of national and regional innovation systems? What should the unit of analysis be, the firm, the innovation as such, or the innovation network? Should these surveys probe the functioning of innovation teams and other human capital issues within the firm?

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Innovation surveys and innovation policies Public R&D and innovation policies are mainly directed to the supply-side (creation of S&T capabilities at firm and national/regional level). Supply-side policies are mainly based in the linear model of innovation. Innovation surveys focus mainly on (R&D) inputs to innovation (supply side) Are innovation surveys are implicitly supporting the linear model of innovation? Innovation systems approach focus on demand-side policies, but… innovation surveys throw some light on innovation systems, but some areas are not adequately covered: linkages between firms and other technology-related agents, diffusion of knowledge, education and learning (human capital).

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Dichotomies: a frame for the debate 1.Manufacturing industries vs service sector 2.Private sector vs public sector 3.High-tech vs low-tech 4.Industrial classification vs clusters 5.New to the firm vs new to the market: 6.Successful vs unsuccessful firms 7.Managers vs line innovators

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology 1. Manufacturing vs service sectors Main focus of innovation surveys has been technological innovation (‘hard’ technologies). Service sector is the predominant economic activity in developed and developing countries. Service sector is highly segmented, heterogeneous, and some services are highly innovative. Not all services are technology backward and non-innovative (laggards, passive adopters). Innovation surveys have started to include services, but terminology still biased to technological innovation.

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Innovation in manufacturing different from innovation in services Distinction between product and process innovation adequate for manufacturing but not for services: Services are often produced and delivered at the same time they are consumed. Exclusion of organizational and managerial innovation is a problem for service innovation. R&D activities less frequent in services. Client relationship: customized services equal innovation? Distinction between products and services has blurred.

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Evolution of studies on innovation in services Indifference (ignorance) Subordination Autonomy Djellal & Gallouj (1999) Assimilation Demarcation (in transition to) Synthesis Tether, Miles, Blind, Hipp, de Liso & Cainilli (2002)

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology 2. Private sector vs public sector Government is a major service provider. Public sector is an early adopter of new technologies, but … it is also an innovator: New services mainly based on ICTs, Organizational innovation, Technological innovation (usually left aside)

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology 3. High tech vs low tech Surveys on advanced manufacturing technologies preceded innovation surveys. Traditional sectors = low tech and non-innovative ? New tech industries = innovative sectors ? Innovation in the resource-based sectors often originates in the machinery and equipment sector. Who are the users of product innovation (Stat Canada) Mining, logging and forestry, oil and gas extraction, utilities

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology 4. Industrial classifications vs clusters Industrial classifications have problems (ISIC, NACE, NAICS) i.e. biotechnology is not a distinctive industry How to deal with clusters, industrial districts, value/competitive chains? Unit of analysis? Firms, innovation networks, clusters? Need to track relationships, for example collaborative and cooperative agreements: type of partner, type of collaboration, importance, and location. ISRN type of studies: characterization of clusters and networks.

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology 5. New to the firm vs new to the market 3 levels of novelty: new to the firm, new to the nation, new to the world. Commercial success vs technical success. What about the competitive environment? World first ok Firm from a developed country vs a firm from a developing nation? Innovativeness and uniqueness: new is a necessary but not sufficient condition, sense of being ‘unique’ A better approach: New to the market A methodological problem for statisticians and academics but not for business people. (e.g. CIS III first step).

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology 6. Successful vs unsuccessful firms Level of innovation activity: performance indicators, resources devoted to innovation activities (input indicators) Innovators vs non-innovators: TPP innovation (results) is the defining characteristic It freezes the picture of the innovation process Subject vs object approach Subject approach is much more than having the firm as the unit of analysis, should be to focus on processes (activities) rather than results (TPP innovation)

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Successful vs unsuccessful cont. New category: Potentially innovative firms Moving picture, evolutionary process Elimination of extensive definition of innovation, ask just about activities related to innovation, posteriori classification of innovative firms Learn not only from success stories but also from failures Technical successes, commercial failures Projects abandoned

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology 7. Managers vs line innovators Targeted respondent : high-rank managers (resources devoted to innovation) Line innovators and middle managers: ones who deal with innovation on a daily basis Different interpretation of innovation: Will we get similar responses from equally informed managers? Gender-bias overlay in innovation surveys: Not language bias, social and power structure bias Female employment is concentrated in the services sector Women innovators are far less visible in organizations Women are in less senior positions in organizations WAGIS project

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Conclusions: research proposals 1 Definitions that need further development and refinement: innovation, novelty, and uniqueness. Innovation is more and more a collaborative, cooperative, globalized process: How do innovation networks work? How knowledge is created and diffused within those networks?

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Conclusions: research proposals 2 Need to design new methodological tools that measure capacities and disposition to innovation: Explain firm’s innovative propensity and ability to innovate Account for firm’s most important assets: human capital. Need to encompass different types of innovative firms avoiding the ‘black and white’ categorization of innovators and non- innovators.

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Conclusions: research proposals 3 Usefulness of standardization and account for representative behaviour: Degree of interpretation of what constitutes innovation Value of innovation expenditures are highly variable What can be compared? Comparability among innovations (innovation is about change) Proportions of innovators (different from proportion of households with a car) Should we abandon innovation surveys?

CPROST SIMON FRASER UNIVERSITY Centre for Policy Research on Science and Technology Conclusions: research proposals 4 We need more diversity in the way we approach innovation, and we need to develop more meaningful studies: To better understand innovation processes, To better understand collaborative innovation and the role of networks, To better understand clusters and national and regional innovation systems, and To better understand innovation in services and resource-based industries.