Demand articulation

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Demand articulation is a concept developed within the scientific field of innovation studies which serves to explain learning processes about needs for new and emerging technologies. [1] Emerging technologies are technologies in their early phase of development, which have not resulted in concrete products yet. [2] Many characteristics of these technologies, such as the technological aspects but also the needs of users concerning the technology, have not been specified yet. Demand articulation can be defined as ‘iterative, inherently creative processes in which stakeholders try to address what they perceive as important characteristics of and attempt to unravel preferences for an emerging innovation’. [3]

Contents

The approach may be applied to describing the processes by which needs for emerging technologies become more concrete over time. At the same time, demand articulation can also be perceived as learning processes that can be evaluated.

Background

The concept of demand articulation originates from the theoretical school that explains innovations as a result of the co-evolution of technological developments and societal pressures. The central idea behind this school is that innovations are not only deterministically formed following technological considerations and possibilities, but in interaction with societal aspects, such as ethical questions, user demands, implementation issues. [4] [5] [6]

In the emergent phase, several aspects of the technology remain rather ‘fluid’ and can be formed by stakeholders involved. In this period, co-evolution of society and technology takes place, and ‘societal entrenchment of a technology’ is carried by different processes in which several aspects of the technology become articulated over time. In the 1990s, the term "articulation processes" was introduced, [7] including articulation of technology specifications, of product and maintenance networks, of cultural and political acceptability, and of demands. [8]

Demand articulation processes owe much to the work of Teubal, [9] [10] in which he stated that in existing markets users have defined their needs quite precisely, and prices (also of competitors) play a major role in sales decisions. With breakthrough, radical, emerging technologies there are no markets and needs in place. Producers can only offer blueprints. However, users might not have thought of the direction of solutions the new product offers, and the regime as a whole might even change as a result of the innovation, which both can lead to different preferences of users.

In order to deal with the determination of user preferences in the context of emerging technologies, Teubal [11] introduced the term market determinateness as “the degree of specificity of the market signals received by the innovating firm and consequently to the extent to which it anticipates demand. In order to explain the concept, we introduce four types of market signals, in ascending order of specificity: (1) signals about a need; (2) signals about a product class; (3) signals about basic functions; (4) signals about product specifications.” Ideally, as a technology emerges and several of its aspects become clear, users are also becoming specific about their ‘market signals’ or demands.

Kodama [12] later picked up market determinateness or demand articulation, which he defined as “a dynamic interaction of technological activities that involves integrating potential demands into a product concept and decomposing this product concept into development agendas for its individual component technologies”. Building on this, the term ‘latent demand’ was introduced, which means that most stakeholders will not have an evident idea of what they want from the start. [13] An actor might have a certain need that is ill-defined or latent, but which, in a sense, cannot be denied. For example, there have been an evident need for communication over long distances and even a then-farfetched idea of mobile communication devices, but the precise need for mobile phones (or SMS services for that matter) could not be foreseen before the introduction of these devices. The demand articulation process, therefore, is the start of a consciousness-raising exercise in which demands become increasingly concrete.

Definition of demand

The definition of demand merits special attention in the context of demand articulation. A clear distinction should be made between two types of demands: [14]

Following the distinction made by Teubal [15] above, substantive demand are more relevant in the emergent phase of technological development. Mowery and Rosenberg [16] underline this by criticising the use of “the rather shapeless and elusive notion of [market] ‘needs’”.

Demands should be regarded as a broad concept that includes a range of concepts varying in level of determinedness and varying in content areas. Concerning the varying degree of concreteness, demands include (ranging from less to more concrete):

Concerning the content range, demands may include cultural, political, ethical, social issues, because in early stages of technology development it is unclear which issues would become important in steering, and because user preferences are diverse and partially dependent on these issues.

Demand articulation and innovation

Users of products and services have the potential to contribute to innovation processes and to the success of eventual innovations. In the 1970s the Science Policy Research Unit (SPRU) conducted the SAPPHO-study in which resembling successful and unsuccessful innovations were compared. “The single measure that discriminated most clearly between success and failure was ‘user needs understood’”. [20] Building on this finding, Von Hippel and his colleagues found that users were major sources or “loci” of innovations in several sectors. [21] [22] Not only do users point to directions of future needs, but they could also have first-hand information on new research directions, ideas, problems, and solutions.

The role of demand-side actors has also been studied in a more holistic way in the innovation system literature. [23] Here, users – and also intermediary organizations – appear as major actors that are engaged in demand articulation processes. Innovation occurs at the intersection of needs and opportunities, both of which show a large degree of variability and unpredictability. This requires not only exchange of information on qualities and costs of innovations, but also of information on the (technological and user-related) contents of these innovations. This content needs to be communicated. The major role of knowledge in user-producer interactions calls for an emphasis on interactive learning; to innovate successfully, producers constantly need to learn about the technological possibilities as well as about user needs.

These interactive learning processes in which demands for (characteristics of) innovations are increasingly better understood can be regarded as demand articulation.

Demand articulation in public innovation policy

In the light of the benefits of understanding user needs, poorly articulated demand is regarded as one of the systemic failures that innovation systems can face. [24] Demand articulation, strategy and vision development should be stimulated. [25] Public innovation policy can contribute to this by contemplating the use of demand-oriented policy instruments, besides supply-, diffusion- and infrastructure-oriented instruments. Examples of demand-oriented innovation policy instruments are public procurement, [26] visioning exercises to produce R&D agendas [27] and facilitate user-producer interactions in local, experimental transdisciplinary settings. [28]

In several countries, including Germany [29] and the Netherlands, [30] demand-oriented innovation policy gradually gained momentum.

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References

  1. ↑ R.E.H.M. Smits, Innovation studies in the 21st century, Technological Forecasting and Social Change 69 (2002) 861-883.
  2. ↑ Van Merkerk, R. and H. Van Lente (2005). “Tracing emerging irreversibilities in emerging technologies: The case of nanotubes.” Technological Forecasting and Social Change 72(9): 1094-1111.
  3. ↑ Boon, W.P.C., E.H.M. Moors, S. Kuhlmann, R.E.H.M. Smits (2010) Demand articulation in emerging technologies: Intermediary user organisations as co-producers? Research policy, 40 (2011) 242–252.
  4. ↑ Mowery, D. C. and N. Rosenberg (1979). “The influence of market demand upon innovation: a critical review of some recent empirical studies.” Research Policy 8(2): 102-153.
  5. ↑ Nelson, R. R. and S. G. Winter (1982). An evolutionary theory of economic change. Cambridge/London, The Belknap Press of Harvard University Press.
  6. ↑ Van den Belt, H. and A. Rip (1987). The Nelson-Winter-Dosi model and synthetic dye chemistry. The social construction of technological systems; new directions in the sociology and history of technology. W. Bijker, T. P. Hughes and T. Pinch. Cambridge, MIT Press: 135-158.
  7. ↑ Rip, A. (1995). “Introduction of new technology: making use of recent insights from sociology and economics of technology.” Technology Analysis & Strategic Management 7(4): 417-431.
  8. ↑ Nelis, A. (1998). DNA diagnostics in the Netherlands (original title: ‘DNA-diagnostiek in Nederland’). Enschede, Twente University Press.
  9. ↑ Teubal, M., A. Arnon and M. Trajtenberg (1976). “Performance in innovation in the Israeli electronics industry: a case study of biomedical electronics instrumentation.” Research Policy 5(4): 354-379.
  10. ↑ Teubal, M. (1979). On user needs and need determination: aspects of the theory of technological innovation. Industrial innovation: technology, policy and diffusion. M. Baker. London, Macmillan: 266-289.
  11. ↑ Teubal, M., A. Arnon and M. Trajtenberg (1976). “Performance in innovation in the Israeli electronics industry: a case study of biomedical electronics instrumentation.” Research Policy 5(4): 354-379.
  12. ↑ Kodoma, F. (1995). Emerging Patterns on Innovation: Sources of Japan’s Technological Edge. Boston, Harvard Business School Press.
  13. ↑ Orihata, M. and C. Watanabe (2000). “The interaction between product concept and institutional inducement: a new driver of product innovation.” Technovation 20: 11-23.
  14. ↑ Klerkx, L., K. de Grip and C. Leeuwis (2006). “Hands off but Strings Attached: The Contradictions of Policy-induced Demand-driven Agricultural Extension.” Agriculture and Human Values 23(2): 189-204.
  15. ↑ Teubal, M. (1979). On user needs and need determination: aspects of the theory of technological innovation. Industrial innovation: technology, policy and diffusion. M. Baker. London, Macmillan: 266-289.
  16. ↑ Mowery, D. C. and N. Rosenberg (1979). “The influence of market demand upon innovation: a critical review of some recent empirical studies.” Research Policy 8(2): 102-153.
  17. ↑ Borup, M., N. Brown, K. Konrad and H. Van Lente (2006). “The sociology of expectations in science and technology.” Technology Analysis & Strategic Management 18(3/4): 285-298.
  18. ↑ Grin, J., A. Grunwald, M. Decker, P. Mambrey, R. Reuzel and G. Van der Wilt (1999). The lessons we learnt: first outline of strategy and a methodical repertoire for vision assessment. Vision assessment: shaping technology in 21st century society – Towards a repertoire for technology assessment. J. Grin and A. Grunwald. Berlin, Springer: 169-189.
  19. ↑ Teubal, M. (1979). On user needs and need determination: aspects of the theory of technological innovation. Industrial innovation: technology, policy and diffusion. M. Baker. London, Macmillan: 266-289.
  20. ↑ Rothwell, R., C. Freeman, A. Horlsey, V. T. P. Jervis, A. B. Robertson and J. Townsend (1974). “SAPPHO updated – project SAPPHO phase II.” Research Policy 3(3): 258-291.
  21. ↑ Von Hippel, E. (1976). “The dominant role of users in the scientific instrument innovation process.” Research Policy 5: 212-239.
  22. ↑ Von Hippel, E. (2005). Democratizing innovation: the evolving phenomenon of user innovation. Advancing knowledge and the knowledge economy, Washington.
  23. ↑ Lundvall, B. A. (1992). National Systems of Innovation: Towards a Theory of Innovation and Interactive Learning. London, Pinter Publishers.
  24. ↑ Edquist, C. (2005). "Systems of innovation - Perspectives and challenges" In: J. Fagerberg, D.C. Mowery and R.R. Nelson (2005) The Oxford handbook of innovation. Oxford University Press: Oxford
  25. ↑ Smits, R. and S. Kuhlmann (2004). “The rise of systemic instruments in innovation policy.” International Journal of Foresight and Innovation Policy 1(1/2): 4-32.
  26. ↑ Edler, J. and L. Georghiou (2007). "Public procurement and innovation – Resurrecting the demand side. Research Policy 36,949–963.
  27. ↑ Roelofsen, A., J. E. W. Broerse, Tj. de Cock Buning and J. F. G. Bunders (2008). “Exploring the future of ecological genomics: Integrating CTA with vision assessment.” Technological Forecasting and Social Change 75(3): 334-355.
  28. ↑ Geels, F. W. (2002). “Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study.” Research Policy 31(8/9): 1257-1274.
  29. ↑ Edler, J. (2007). "Nachfrageorientierte Innovationspolitik" (Demand Oriented Innovation Policy). Berlin: Edition Sigma.
  30. ↑ Dutch Ministry of Economic Affairs, Agriculture and Innovation. (2011) "Naar de top: de hoofdlijnen van het nieuwe bedrijfslevenbeleid" (To the top: starting points for new business policy. Den Haag: Ministry of Economic Affairs, Agriculture and Innovation
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