A new perspective and conceptual framework of institutional linkages is explored and an institutional linkage model is developed. The model incorporates the linkage patterns and characterises major policy issues affecting technological innovation and technology transfer among the participating organisations. The development of the linkage model will draw on the insights provided by the literature on innovation. Particularly, it is argued that the nature and role of the linkage in technology development is a reflection of a generalised version of an interactive and systemic model of innovation which would suggest policy implications for promoting linkages and interactions within National Systems of Innovation.
The research for this paper was undertaken at Monash University with the assistance of a Postgraduate Publications Award.
See, for example, R. Rothwell, ‘Industrial innovation: success, strategy, trends’, in M. Dodgson and R. Rothwell (eds), The Handbook of Industrial Innovation, Edward Elgar, Hants, 1994, pp. 33–53; S. Woolgar, ‘A new theory of innovation?’, Prometheus, 16, 4, 1998, pp. 441–52.
R. Nelson and S. Winter, An Evolutionary Theory of Economic Change, Belknap Press of Harvard University Press, Cambridge, 1982.
For other evolutionary theories and their relations to technological change and systems of innovation see P. P. Saviotti, Technological Evolution, Variety and the Economy, Edward Elgar, Cheltenham, 1996; C. Edquist (ed.), Systems of Innovation: Technologies, Institutions and Organisations, Pinter, London, 1997.
R. Gomory, ‘From the “Ladder of Science” to the product development cycle’, Harvard Business Review, 67, 6, 1989, pp. 99–105.
S. Kline and N. Rosenberg, ‘An overview of innovation’, in R. Landau and N. Rosenberg (eds), The Positive Sum Strategy: Harnessing Technology for Economic Growth, National Academy Press, Washington, 1986, pp. 275–306; R. Rothwell and W. Zegveld, Reindustrialization and Technology, Longman, Harlow, 1985.
Freeman, based on the Maastricht Memorandum, also summarises the main characteristics of a systemic model of innovation as: ‘1. Multidirectional links at the same point in time between the stages of technical change. 2. Cumulative processes over time can lead to feedbacks and lock-in effects. 3. Technical change is dependent on knowledge and the assimilation of information through learning. 4. The details of the development path and diffusion process for each innovation are unique. 5. Technical change is an independent and systemic process'. See C. Freeman, ‘The greening of technology and models of innovation’, Technological Forecasting and Social Change, 53, 1996, p. 31.
A recent study by Etzkowitz and Leydesdorff suggests another non-linear model of the innovation process. According to them: ‘a spiral model of innovation is required to capture multiple reciprocal linkages at different stages of the capitalisation of knowledge'. The involvement of universities, industry and governments in the process therefore results in a ‘triple helix’ model of innovation. As the biological metaphor indicates, this is an evolutionary model. Etzkowitz and Leydesdorff assert that this triple helix of university—industry—government relations is likely to be a key component of national and multinational innovation strategies. See H. Etzkowitz and L. Leydesdorff, ’The triple helix of university—industry—government relations: a laboratory for knowledge based economic development’, EASST Review, 14, 1, 1995, pp. 11–19.
Freeman, however, in a recent paper argues mat: ‘To realise large technoeconomic system transitions, society needs to develop a new model of innovation, combining some features of the much criticised linear model with features of the systemic innovation model’. For more elaboration of this argument, see C. Freeman, op. cit., p. 27.
This assumption is based on the fact that numerous case studies of innovation point to the importance of flows of information and knowledge between firms as well as within firms. Moreover, the results of empirical research point to the importance both of flows to and from sources of scientific and technical knowledge and of flows to and from users of products and processes. See B. A. Lundvall, ‘Innovation as an interactive process: from user-producer interaction to the national system of innovation’, in G. Dosi et al. (eds), Technical Change and Economic Theory, Pinter Publishers, London, 1988, pp. 349–69.
For example, according to Shohet and Prevezer intermediaries play an important role in contractual and financial/economic linkages involved in biotechnology in the UK. See S. Shohet and M. Prevezer, ‘UK biotechnology: institutional linkages, technology transfer and the role of intermediaries’, R&D Management, 26, 3, 1996, pp. 283–98.
See R. Nelson (ed.), National Innovation Systems: A Comparative Analysis, Oxford University Press, New York, 1993; B. A. Lundvall (ed.), National Systems of Innovation: Towards a Theory of Innovation and Interactive Learning, Pinter Publishers, London, 1992.
E. Dahmen, ‘Development blocks in industrial economies’, Scandinavian Economic History Review and Economic and History, xxxvi, 1, 1988, pp. 3–14.
In fact, technical exchange is an interactive process, and what is transferred takes many forms-knowledge embodied in people, and in codified form in publications and patents. It is the process of movement between actors (whether individuals or organisations) of these forms of knowledge and information, and the accompanying contractual, financial and economic relations that is also referred to as technology transfer. For a model of knowledge transfer, see M. Gilbert and M. Cordey-Hayes ‘Understanding the process of knowledge transfer to achieve successful technological innovation’, Technovation, 16, 6, 1996, pp. 301–12.
This is because it is through interaction that information is transferred and thus the interaction process can stimulate or inhibit the efficient technical exchange between the actors.
Gibbons et al., while discussing the Mode 2 knowledge production, suggest that ‘the notion of technology transfer has to be reconsidered’. They maintain that ‘technology interchange is a more appropriate phrase than technology transfer’. This is because Mode 2 knowledge production involves the close interaction of many actors. For more information, see M. Gibbons et al., The New Production of Knowledge, Sage Publications, London, 1994.
Brown and Karagozoglu also provide a systems model of technological innovation based on two specific types of inputs to the innovation systems: (1) decision inputs; and (2) implementation inputs. For more discussion about their model, see W. B. Brown and N. Karagozoglu, ‘A systems model of technological innovation’, IEEE Transactions on Engineering Management, 36, 1, 1989, pp. 11–16.
For other models of technology transfer, see, for instance, R. A. F. Seaton and M. Cordey-Hayes, ‘The development and application of interactive models of industrial technology transfer’, Technovation, 13, 1, 1993, pp. 45–53; P. Trott et al., ‘Inward technology transfer as an interactive process’, Technovation, 15, 1, 1995, pp. 25–43; and C. Chiarella et al., ‘Innovation and the transfer of technology: a leader—follower model’, Economic Modelling, October, 1989, pp. 452–6. Among these writers, Seaton and Cordey-Hayes have drawn attention to many of the limitations and deficiencies in traditional technology transfer mechanisms and presented a model of technology transfer (accessibility-mobility-receptivity) which emphasised the interactive nature of the process. Their study was followed by a subsequent paper by Trott et al. which focused on the concept of ‘receptivity’ and developed a conceptual framework which identified four major components for the inward technology transfer process in firms. These are: awareness, association, assimilation and application.
L. K. Anderson, ‘Technology transfer from federal labs: the role of intermediaries’, in S. K. Kassicieh and H. R. Radosevich (eds), From Lab to Market: Commercialization of Public Sector Technology, Plenum Press, New York, 1994, pp. 183–94.
Anderson names these two models as ‘conduit’ and ‘control system’ models. See Anderson, Ibid.
Ibid.
Ibid.
For example, in order to show that many factors are involved for a successful innovation, Dunphy el al. studied the influence of global, national and micro level factors on innovation. They argue that these factors provide the critical path through the innovation funnel. See S. M. Dunphy et al., ‘The innovation funnel’, Technological Forecasting and Social Change, 53, 1996, pp. 279–92.