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The Role of the Organization Structure in the Diffusion of Innovations

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  • Carlos Sáenz-Royo
  • Carlos Gracia-Lázaro
  • Yamir Moreno

Abstract

Diffusion and adoption of innovations is a topic of increasing interest in economics, market research, and sociology. In this paper we investigate, through an agent based model, the dynamics of adoption of innovative proposals in different kinds of structures. We show that community structure plays an important role on the innovation diffusion, so that proposals are more likely to be accepted in homogeneous organizations. In addition, we show that the learning process of innovative technologies enhances their diffusion, thus resulting in an important ingredient when heterogeneous networks are considered. We also show that social pressure blocks the adoption process whatever the structure of the organization. These results may help to understand how different factors influence the diffusion and acceptance of innovative proposals in different communities and organizations.

Suggested Citation

  • Carlos Sáenz-Royo & Carlos Gracia-Lázaro & Yamir Moreno, 2015. "The Role of the Organization Structure in the Diffusion of Innovations," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-13, May.
    • Handle: RePEc:plo:pone00:0126076
    DOI: 10.1371/journal.pone.0126076
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    References listed on IDEAS

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    Cited by:

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    2. Leihan Zhang & Ke Xu & Jichang Zhao, 2017. "Sleeping beauties in meme diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 383-402, July.
    3. Kibaek Lee & Jaeheung Yoo, 2019. "How does open innovation lead competitive advantage? A dynamic capability view perspective," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-18, November.
    4. Smaldino, Paul E. & Russell, Adam & Zefferman, Matthew & Donath, Judith & Foster, Jacob & Guilbeault, Douglas & Hilbert, Martin & Hobson, Elizabeth A. & Lerman, Kristina & Miton, Helena, 2024. "Information Architectures: A Framework for Understanding Socio-Technical Systems," SocArXiv c7vrw, Center for Open Science.
    5. K D S Fernald & H P G Pennings & J F van den Bosch & H R Commandeur & E Claassen, 2017. "The moderating role of absorptive capacity and the differential effects of acquisitions and alliances on Big Pharma firms' innovation performance," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-22, February.
    6. Petr Hajek & Roberto Henriques, 2017. "Modelling innovation performance of European regions using multi-output neural networks," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-21, October.

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