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Social network markets: a new definition of the creative industries

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Abstract

We propose a new definition of the creative industries in terms of social network markets. The extant definition of the creative industries is based on an industrial classification that proceeds in terms of the creative nature of inputs and the intellectual property nature of outputs. We propose, instead, a new market-based definition in terms of the extent to which both demand and supply operate in complex social networks. We review and critique the standard creative industries definitions and explain why we believe a market-based social network definition offers analytic advance. We discuss some empirical, analytic and policy implications of this new definition.

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Notes

  1. See Howkins (2001), Hartley (2005), Cunningham (2006).

  2. See, for example, Roodhouse (2001), Florida (2002), Garnham (2005), Hartley (2005: 26–31).

  3. See Beinhocker (2006) and Foster (2006).

  4. ‘Culture proceeds incrementally, building on whatever was available before, sometimes using a well-tried and established formula, other times innovating radically. No-one is sure what is going to “work”, the failure rate is high. … Culture creates its own markets and the pleasure of consumption is also the pleasure of possession because the consumer never faces the object of consumption as an isolated individual. We want some things few people have, but we also want things everyone has. Being in a market is a social activity.’ (Sassoon 2006: xvi).

  5. See Howkins (2001), Cunningham (2006), Potts (2006), Potts and Cunningham (2008).

  6. See White (1981) and Dopfer and Potts (2008a).

  7. For the importance of moving beyond the ‘industry’ metaphor, see Hartley (2008b).

  8. For example, Baumol and Bowen (1966), Throsby (1994), Heilbrun and Gray (2000).

  9. This position is also advanced by Caves (2000), but in terms of information and transaction cost economics, as opposed to a conception of the market process.

  10. See for example Castronova (2006), Chai et al. (2007), Potts et al. (2008).

  11. Watts (1999), Earl and Potts (2004).

  12. See Potts et al. (2008).

  13. This explains why contemporary emergent producer-consumer integration (as in the neologisms: prosumer or produser) and the so-called pro-am revolution (Leadbeater and Miller 2004) is a feature of this process, along with the emergence of new organizations and markets.

  14. cf. DCSM: ‘Those industries which have their origin in individual creativity, skill and talent and which have a potential for wealth and job creation through the generation and exploitation of intellectual property.’

  15. A rule is defined here generically as an operationalized idea (Dopfer and Potts 2008a). Behaviours, organizations and technologies are all instances of rules. See also Nelson and Sampat (2001).

  16. E.g., Strogatz (2001) or Barabasi (2002).

  17. E.g., see the work of Paul Samuelson, J. K. Gailbraith, Michael Porter or Oliver Williamson. This is most clearly expressed in cultural economics through the work of Will Baumol.

  18. See Shy (2001) on the economics of network industries.

  19. In general equilibrium theory, everything is connected to everything else (Potts 2000), but in evolutionary theory structural sub-systems are defined that demarcate the complex order of the economic system (Simon 1962).

  20. As the science studies scholars have explained, e.g., see the work of Philip Mirowski, Deirdre McCloskey, Steve Fuller, etc.

  21. See also Swedberg (2006).

  22. An obvious problem here is the term ‘industries’ itself, as what we are essentially arguing is that the creative industries is better defined in terms of social networks and markets. The term ‘creative economy’ is preferable.

  23. On this point, see Foster and Potts (2006) and Dopfer and Potts (2008a).

  24. Cf. Garnham (2005).

  25. See cultural science: http://www.cultural-science.org/.

  26. A network (or a graph) is formally defined as a set of vertices, or elements, with edges, or connections between them. Models of complex networks have been widely developed in sociology over the past three decades and have sought to model networks through several key dimensions including size (number of vertices), degree (average number of edges per vertex), centrality (measure of degree distribution), diameter (longest shortest path) clustering or transitivity (measure of triadic probability of vertices) and the existence of hubs (measure of preferential attachment of new edges differential degree vertices). An excellent overview of this general literature is Newman (2003) and of social networks in particular, see Vega-Redondo (2007). These methods have been greatly advanced in recent years with the application of computational techniques developed in statistical physics (Ormerod 2005). Models of social networks have been widely used in sociology to study the topology of social network interaction to estimate the connectivity of the social system (which is then applied for the study of e.g., the spread of sexually transmitted diseases, political opinions, fashions, etc.). Social network models have also been in economics (see Kirman (1993), Ormerod (1998), Potts (2000)) in the similar context of adoption/diffusion of new messages and technologies in order to explain how market (i.e., social) structure affects market dynamics (whether of prices or technological adoption).

  27. Small world networks have the property of balancing high clustering with low diameter, see Watts (1999) and Strogatz (2001).

  28. Scale-free networks with power-law degree distributions in which hubs occur at all scales, Albert and Barabasi (2000).

  29. See De Vany (2004), Earl and Potts (2004), Chai et al. (2007).

  30. This enables us to further develop work, such as by Benkler (2006), who recognises the centrality of networks to the new production-innovation-consumption synthesis, by bringing a network theory (as opposed to model/metaphor) in terms of social and economic systems.

  31. This is in particular in relation to what Dopfer and Potts (2008a) call the phase of Meso 1, or origination.

  32. Hesmondhalgh and Pratt (2005).

  33. Note this last point implies a dynamic approach to welfare, which is consistent with the evolutionary approach to policy (see Pelikan and Wegner 2003).

  34. Heilbrun (1991), Cowen (2002).

  35. Interestingly, this would move the CIs from irrelevance to the forefront of innovation policy, when understood as a supervening set of industry, competition, cultural and education policy (Cunningham 2006).

  36. This will be adaptive economic policy (Pelikan and Wegner 2003).

  37. See Beinhocker (2006), Benkler (2006).

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Acknowledgments

Authors Potts, Cunningham and Hartley acknowledge the support of the Australian Research Council. This research was conducted at the ARC Centre of Excellence for Creative Industries and Innovation (project number CE0561908). John Hartley is the recipient of an ARC Federation Fellowship (project number FF0561981). Special thanks also to Bridget Rosewell and Kate Morrison for useful comments on earlier drafts, and to the insightful comments of referees, which have improved this article considerably. All remaining errors are of course due to global warming.

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Authors and Affiliations

  1. CCI, Queensland University of Technology, 515, Z1, Musk Ave., Kelvin Grove, Brisbane, Australia

    Jason Potts, Stuart Cunningham & John Hartley

  2. School of Economics, University of Queensland, Brisbane, Australia

    Jason Potts

  3. Volterra Ltd, London, UK

    Paul Ormerod

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  1. Jason Potts
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Correspondence to Jason Potts.

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Potts, J., Cunningham, S., Hartley, J. et al. Social network markets: a new definition of the creative industries. J Cult Econ 32, 167–185 (2008). https://doi.org/10.1007/s10824-008-9066-y

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