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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. 10/17/2003 Salazar & Holbrook. 1. CPROST. SIMON FRASER UNIVERSITY.
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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 10/17/2003 Salazar & Holbrook 1 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 2002. • Mid 90s: first experiments of innovation surveys in Latin America. • Bogotá Manual published 2000.
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?
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).
Dichotomies: a frame for the debate • Manufacturing industries vs service sector • Private sector vs public sector • High-tech vs low-tech • Industrial classification vs clusters • New to the firm vs new to the market: • Successful vs unsuccessful firms • Managers vs line innovators
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.
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.
Indifference (ignorance) Subordination Autonomy Djellal & Gallouj (1999) Assimilation Demarcation (in transition to) Synthesis Tether, Miles, Blind, Hipp, de Liso & Cainilli (2002) Evolution of studies on innovation in services
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)
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
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.
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).
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)
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
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
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?
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.
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?
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.