© Imperial College LondonPage 1 Future of the UK Innovation Survey An Innovation Management Researcher’s Perspective Ammon Salter Innovation Studies Centre Tanaka Business School DTI CIS Users Group Meeting

© Imperial College LondonPage 2 Personal perspective Complex and subtle link between managerial choice and innovative performance Managerial choices – sources of ‘dynamic capabilities’ –Innovation and corporate strategy –New product development process –Organisational design and routines –Relationship to external environment – ‘distributed innovation systems’ or ‘open innovation’ –Processes commercialisation of new innovations –Use and integration of different knowledge sources Shaped by age, size and industry Combination of methods –Case studies – fly-by interviews, in-depth cases, observation etc. –Statistical methods – CIS, Patent data, OECD STAN, Innovation databases, Ad-hoc surveys etc.

© Imperial College LondonPage 3 Pavitt on Data and Theory in S&T One danger is that improvement in databases in scientific and technological activities will greatly increase the emphasis given to the professionally safe option in academic careers; namely, regression analysis to test established theories. This would be a pity, since new theories emerge from new data (Pavitt, 1998, emphasis added).

© Imperial College LondonPage 4 Status of CIS Popular - gaining acceptance in academic and policy communities Flexible - used by different communities Powerful – opportunity to better understand innovation processes Open – access enabled different perspectives Persistent – embedded in policy and academic communities Bountiful – new links between innovation and firm behaviour

© Imperial College LondonPage 5 Problems Poor fit with previous research –Start-up variable Overly focused on innovative outcomes not managerial choices –‘Effects’ vs. ‘objectives’ Hard and soft measures –The ‘phony’ war – false sense of tangibility Breadth and depth –E-commerce questions –U-I links Common method bias –Performance data collected at the same time as explanatory variables Stand alone –Connection to production statistics –Other ONS surveys – R&D data, e-commerce etc.

© Imperial College LondonPage 6 Issues for discussion What should be kept for purposes of consistency and what should be improved? What is the balance between innovative ‘output’ and managerial choice? What is the UK ‘distinctive’ perspective?

© Imperial College LondonPage 7 Modernising the CIS? Retain Sources of ideas Appropriability Performance questions Drop Use of government programmes Other major changes E-commerce Some innovation expenditure variables Add University-industry links Organisational change Competitive environment Links to other data sets Revise Innovation co-operation Start-up variable Effects of innovation Core innovation expenditure variables