Creative Industries and Big Data: A Business Model for Service Innovation

Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 279)


Creative Industries have largely contributed to employment, GDP growth and social cohesion, even during recent economic crises. Despite their relevance, there is a lack for monitoring the impacts, especially for new technologies involved into their business. The paper aims to appraise it when specifically related to the use of Big Data. It evaluates the considerable economic benefit on creative business performance linked to exploiting vast new flows of information. A multi-criteria methodology for assessing these effects on Creative Industries, and a model for implementing business performance through collaborative and virtual value chains are presented. The model shows positive spillovers resulting from the collaboration among Digital Creative Industries usually in the fields of innovation, technology and intellectual property benefitting from Big Data applications, distinguishing a macro from a microeconomic level of effectiveness, since transforming data into captured value for the firms, despite their size and volume capacity, increases business performance.


Creative Industries Digital Creativity Big Data ICT Impact Assessment (IA) Organisational semiotics 


  1. 1.
    Department for Culture Media and Sport: Creative Industries Mapping Documents 2001. DCMS, London (2001)Google Scholar
  2. 2.
    Newbigin, J.: The Creative Economy: An Introductory Guide. Creative Economy Unit. British Council, London (2010)Google Scholar
  3. 3.
    United Nations: Creative Economy Report 2013. Widening Local Development Pathways. UNDP/UNESCO, New York/Paris (2013)Google Scholar
  4. 4.
  5. 5.
    Caves, R.E.: Contracts between arts and commerce. J. Econ. Persp. 17, 73–83 (2003)CrossRefGoogle Scholar
  6. 6.
    O’Connor, J.: The Cultural and Creative Industries: A Literature Review. Creativity, Culture and Education, Newcastle (2010)Google Scholar
  7. 7.
    Bakhshi, H., Throsby, D.: Culture of innovation. An economic analysis of innovation in arts and cultural organisations. Research report, NESTA, London (2010)Google Scholar
  8. 8.
    Campbell, D.F., Carayannis, E.G., Dubina, I.N.: Creativity, economy and a crisis of the economy? Coevolution of knowledge, innovation, and creativity, and of the knowledge economy and knowledge society. J. Know. Econ. 3, 1–24 (2012)CrossRefGoogle Scholar
  9. 9.
    ESSnet Culture: European Statistical System Network on Culture. Final Report, Eurostat, Luxembourg (2012)Google Scholar
  10. 10.
  11. 11.
    Florida, R.: The Rise of the Creative Class. Basic Books, New York (2002)Google Scholar
  12. 12.
    Beer, S.: The viable system model: its provenance, development, methodology and pathology. J. Oper. Res. Soc. 35, 7–25 (1984)CrossRefGoogle Scholar
  13. 13.
    Chen, H., Chiang, R.H., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36, 1165–1188 (2012)Google Scholar
  14. 14.
    Tsai, C.W., Lai, C.F., Chao, H.C., Vasilakos, A.V.: Big Data analytics: a survey. J. Big Data 2, 21–53 (2015)CrossRefGoogle Scholar
  15. 15.
    McAfee, A., Brynjolfsson, E.: Big Data: the management revolution. HBR 90, 60–66 (2012)Google Scholar
  16. 16.
    Bakhshi, H., Hargreaves, S., Mateos-Garcia, J.: A Manifesto for the Creative Economy. NESTA, London (2013)Google Scholar
  17. 17.
    Tomczak, P., Stachowiak, K.: Location patterns and location factors in the cultural and creative industries. Quaestiones Geographicae 34, 7–27 (2015)CrossRefGoogle Scholar
  18. 18.
    Chapain, C., Cooke, P., De Propris, L., MacNeill, S., Mateos-Garcia, J.: Creative Clusters and Innovation. NESTA, London (2010)Google Scholar
  19. 19.
    Christensen, C.M.: The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business School Press, Brighton (1997)Google Scholar
  20. 20.
    Markides, C.: Disruptive innovation: in need of better theory. J. Prod. Innov. Manag. 23, 19–25 (2006)CrossRefGoogle Scholar
  21. 21.
    Nadkarni, A., Vesset, D.: Worldwide Big Data technology and services forecast, 2016–2020. Doc. no. US40803116. IDC FutureScape, Framingham (2016)Google Scholar
  22. 22.
    Larson, J.: Big (Data) insights. HIS Q. 2, 20–27 (2014)Google Scholar
  23. 23.
    BDVA: European Big data value strategic research and innovation agenda. The New Economic Asset for Europe, Version 2.0, BDVA, Bruxelles (2016)Google Scholar
  24. 24.
    Liu, K., Li, W.: Organisational Semiotics for Business Informatics. Routledge, Abingdon (2015)Google Scholar
  25. 25.
    Bahkshi, H., Davies, J., Freeman, A., Higgs, P.: The Geography of the UK’s Creative and High-Tech Economies. NESTA, London (2015)Google Scholar
  26. 26.
    Marasco, A., Masiello, B., Izzo, F.: Client involvement and innovation in creative-intensive business services: a framework for exploring co-innovation in advertising agency-client relationships. Economies et sociétés 47, 445–478 (2013)Google Scholar
  27. 27.
    Latinović, T.S., Preradović, D.M., Barz, C.R., Latinović, M.T., Petrica, P.P., Pop-Vadean, A.: Big Data in industry. In: IOP Conference Series: Materials Science and Engineering, vol. 144, p. 012006. IOP Publishing, Bristol (2016)Google Scholar
  28. 28.
    Chen, M., Mao, S., Liu, Y.: Big Data: a survey. Mob. Netw. Appl. 19, 171–209 (2014)CrossRefGoogle Scholar
  29. 29.
    European Commission: Green Paper. Unlocking the Potential of Cultural and Creative Industries. COM(2010) No.183. European Commission, Brussel (2010)Google Scholar
  30. 30.
    UK Trade & Investments: UK Creative Industries – International Strategy. Driving Global Growth for the UK Creative Industries. UK Trade & Investments, London (2015)Google Scholar
  31. 31.
    Boardman, A.E., Greenberg, D.H., Vining, A.R., Weimer, D.L.: Cost-Benefit Analysis: Concept and Practice, 3rd edn. Pearson Prentice Hall, Upper Saddle River (2007)Google Scholar
  32. 32.
    Köksalan, M., Wallenius, J., Zionts, S.: An early history of multiple criteria decision making. J. Multi-Crit. Decis. Anal. 20, 87–94 (2013)CrossRefGoogle Scholar
  33. 33.
    Galloway, S., Dunlop, S.: Deconstructing the concept of ‘creative industries’. In: Eisenberg, C., Gerlach, R., Handke, C. (eds.) Cultural Industries: The British Experience in International Perspective, pp. 33–52. Humboldt University, Berlin.
  34. 34.
    Lee, N., Rodríguez-Pose, A.: Creativity, Cities and Innovation: Evidence from UK SMEs, WP no. 13/10. NESTA, London (2013)Google Scholar
  35. 35.
    Creative Industries Council: Create UK. Creative Industries Strategy. CIC, London (2013)Google Scholar
  36. 36.
    Potts, J., Cunningham, S.: Four models of the creative industries. Int. J. Cult. Pol. 14, 233–247 (2008)CrossRefGoogle Scholar
  37. 37.
    Bakhshi, H., Windsor, G.: The Creative Economy and the Future of the Employment. NESTA, London (2015)Google Scholar
  38. 38.
    Qiu, J., Wu, Q., Ding, G., Xu, Y., Feng, S.: A survey of machine learning for Big Data processing. EURASIP J. Adv. Sign. Proc. 1, 1–16 (2016)Google Scholar
  39. 39.
    Schroeder, R.: Big Data business models: challenges and opportunities. Cogn. Soc. Sci. 1166924 (2016).
  40. 40.
    Clarke, R., Nilsson, A.: Business services as communication patterns: a work practice approach for analysing service encounters. IBM Syst. J. 47, 129–141 (2008)CrossRefGoogle Scholar
  41. 41.
    Ernst &Young: Cultural times. The First Global Map of Cultural and Creative Industries. EY Ltd., London (2015)Google Scholar
  42. 42.
    Larson, R.C.: Service science: at the intersection of management, social and engineering sciences. IBM Syst. J. 47, 41–51 (2008)CrossRefGoogle Scholar
  43. 43.
    Matzler, K., Veider, V., Kathan, W.: Adapting to the sharing economy. MIT Sl Man Rev. 56, 71–77 (2015)Google Scholar
  44. 44.
    Puschmann, T., Alt, R.: Sharing economy. Bus. Inf. Syst. Eng. 58, 93–99 (2016)CrossRefGoogle Scholar
  45. 45.
    Baumol, W.J., Bowen, W.J.: Performing Arts: The Economic Dilemma. Twentieth Century Fund, New York (1966)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Università di TeramoTeramoItaly
  2. 2.Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiFrascati, RomeItaly

Personalised recommendations