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Innovation: A data-driven approach

  • Kusiak, Andrew
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    A newly introduced product or service becomes an innovation after it has been proven in the market. No one likes the fact that market failures of products and services are much more common than commercial successes. A data-driven approach to innovation is proposed. It is a natural extension of the system of customer requirements in terms of their number and type and the ways of collecting and processing them. The ideas introduced in this paper are applicable to the evaluation of the innovativeness of planned introductions of design changes and design of new products and services. In fact, blends of products and services could be the most promising way of bringing innovations to the market. The most important toll gates of innovation are the generation of new ideas and their evaluation. People have limited ability to generate and evaluate a large number of potential innovation alternatives. The proposed approach is intended to evaluate many alternatives from a market perspective.

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    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 122 (2009)
    Issue (Month): 1 (November)
    Pages: 440-448

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    Handle: RePEc:eee:proeco:v:122:y:2009:i:1:p:440-448
    Contact details of provider: Web page: http://www.elsevier.com/locate/ijpe

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    1. Gallouj, Faiz & Weinstein, Olivier, 1997. "Innovation in services," Research Policy, Elsevier, vol. 26(4-5), pages 537-556, December.
    2. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-51, March.
    3. Koskinen, Kaj U. & Vanharanta, Hannu, 2002. "The role of tacit knowledge in innovation processes of small technology companies," International Journal of Production Economics, Elsevier, vol. 80(1), pages 57-64, November.
    4. Bordoloi, Sanjeev & Guerrero, Hector H., 2008. "Design for control: A new perspective on process and product innovation," International Journal of Production Economics, Elsevier, vol. 113(1), pages 346-358, May.
    5. Philippe Aghion & Peter Howitt, 1997. "Endogenous Growth Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262011662, June.
    6. Gilbert, Nigel & Ahrweiler, Petra & Pyka, Andreas, 2007. "Learning in innovation networks: Some simulation experiments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 100-109.
    7. Henkel, Joachim, 2006. "Selective revealing in open innovation processes: The case of embedded Linux," Research Policy, Elsevier, vol. 35(7), pages 953-969, September.
    8. Eric von Hippel, 1986. "Lead Users: A Source of Novel Product Concepts," Management Science, INFORMS, vol. 32(7), pages 791-805, July.
    9. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth Through Creative Destruction," Scholarly Articles 12490578, Harvard University Department of Economics.
    10. Albino, Vito & Carbonara, Nunzia & Giannoccaro, Ilaria, 2006. "Innovation in industrial districts: An agent-based simulation model," International Journal of Production Economics, Elsevier, vol. 104(1), pages 30-45, November.
    11. Hacklin, Fredrik & Marxt, Christian & Fahrni, Fritz, 2006. "Strategic venture partner selection for collaborative innovation in production systems: A decision support system-based approach," International Journal of Production Economics, Elsevier, vol. 104(1), pages 100-112, November.
    12. de Vries, Erik J., 2006. "Innovation in services in networks of organizations and in the distribution of services," Research Policy, Elsevier, vol. 35(7), pages 1037-1051, September.
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