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Identification of innovation solvers in open innovation communities using swarm intelligence

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  • Martinez-Torres, Rocio
  • Olmedilla, Maria

Abstract

Open innovation communities represent an effective strategy to provide organizations with a wider range of ideas, reducing the costs associated to R&D. Its main problem is the large volume of information generated in the form of proposed innovations that should be internally processed and executed by employed experts. The purpose of this work consists of identifying the profiles of the so-called innovation solvers using only their participation characteristics extracted from open innovation communities, which are modelled as social networks, and applying particle swarm optimization. Findings can improve the absorptive capacity of organizations by focusing on those users with more chances of generating potentially adoptable ideas.

Suggested Citation

  • Martinez-Torres, Rocio & Olmedilla, Maria, 2016. "Identification of innovation solvers in open innovation communities using swarm intelligence," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 15-24.
    • Handle: RePEc:eee:tefoso:v:109:y:2016:i:c:p:15-24
    DOI: 10.1016/j.techfore.2016.05.007
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    Cited by:

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    4. Arenas-Márquez, F.J. & Martínez-Torres, M.R. & Toral, S.L., 2021. "How can trustworthy influencers be identified in electronic word-of-mouth communities?," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    5. Divakaran, Pradeep Kumar Ponnamma, 2017. "The netnographic method as early warning: Linking antecedents of pre-release behavior of technology-enabled community to future market trends," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 245-257.
    6. Silva, Sergio Evangelista & Venâncio, Ana & Silva, Joaquim Ramos & Gonçalves, Carlos Alberto, 2020. "Open innovation in science parks: The role of public policies," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    7. Dell'Era, Claudio & Di Minin, Alberto & Ferrigno, Giulio & Frattini, Federico & Landoni, Paolo & Verganti, Roberto, 2020. "Value capture in open innovation processes with radical circles: A qualitative analysis of firms’ collaborations with Slow Food, Memphis, and Free Software Foundation," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    8. Olmedilla, M. & Send, H. & Toral, S.L., 2019. "Identification of the unique attributes and topics within Smart Things Open Innovation Communities," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 133-147.
    9. Ghasemzadeh, Khatereh & Bortoluzzi, Guido & Yordanova, Zornitsa, 2022. "Collaborating with users to innovate: A systematic literature review," Technovation, Elsevier, vol. 116(C).

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