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Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web

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  • von Hippel, Eric
  • Kaulartz, Sandro

Abstract

All innovations consist of a need paired with a responsive solution - a need-solution pair (von Hippel and von Krogh 2016). Today, technical advances in machine learning techniques for natural language understanding, such as semantic word space models and semantic network analytics, have made it practical to capture descriptions of early-stage, need-solution pairs mentioned anywhere in the open, textual content of the Internet. Producers - and anyone - can now thus look for user innovations posted on the web that may involve either known or newly defined needs coupled to new solutions that are gaining traction. This is important because, as is now understood, users, rather than producers, tend to pioneer functionally new products and services for which both the need and the solution may be novel.

Suggested Citation

  • von Hippel, Eric & Kaulartz, Sandro, 2021. "Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web," Research Policy, Elsevier, vol. 50(8).
    • Handle: RePEc:eee:respol:v:50:y:2021:i:8:s0048733320301347
    DOI: 10.1016/j.respol.2020.104056
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    References listed on IDEAS

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    Cited by:

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    2. Yu, Xin & Zhang, Ting & Bogers, Marcel L.A.M., 2023. "Why do user innovators want to pursue user entrepreneurship? On the influence of the communitarian identity," Journal of Business Venturing Insights, Elsevier, vol. 20(C).
    3. Pierre Barbaroux & Victor Santos Paulino, 2022. "Why do motives matter? A demand-based view of the dynamics of a complex products and systems (CoPS) industry," Journal of Evolutionary Economics, Springer, vol. 32(4), pages 1175-1204, September.
    4. de Jong, Jeroen P.J. & Ben-Menahem, Shiko M. & Franke, Nikolaus & Füller, Johann & von Krogh, Georg, 2021. "Treading new ground in household sector innovation research: Scope, emergence, business implications, and diffusion," Research Policy, Elsevier, vol. 50(8).
    5. Just, Julian, 2024. "Natural language processing for innovation search – Reviewing an emerging non-human innovation intermediary," Technovation, Elsevier, vol. 129(C).
    6. Lu, Keying & Zou, Tengjian & Du, Jian, 2024. "Two forms of customer involvement and new product development performance in the digital context: The moderating role of new product development stage," Technovation, Elsevier, vol. 134(C).
    7. von Hippel, Christiana D. & Cann, Andrew B., 2021. "Behavioral innovation: Pilot study and new big data analysis approach in household sector user innovation," Research Policy, Elsevier, vol. 50(8).
    8. Mulhuijzen, Max & de Jong, Jeroen P.J., 2023. "The rich or the poor? Personal resources, do-it-yourself, and innovation in the household sector," Research Policy, Elsevier, vol. 52(3).
    9. Abi Saad, Elie & Tremblay, Nathalie & Agogué, Marine, 2024. "A multi-level perspective on innovation intermediaries: The case of the diffusion of digital technologies in healthcare," Technovation, Elsevier, vol. 129(C).

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