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Role of community in user innovation generation and diffusion—Focusing on non-brand communities in the mountain climbing market

Author

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  • Yoshida, Daichi
  • Miyazawa, Jun-ichi
  • Takahashi, Shingo

Abstract

It is generally understood that manufacturers should exploit the innovation generated by users (UI: user innovation) to develop new products. UI has been observed in real world markets and the typical features of innovating users have been identified. The roles of the various communities in consumer product markets are explored as an important factor in UI. While communities foster the generation of UI and assist the diffusion of UI to the markets, it is still unclear what kind of communities managers in manufacturing firms should approach to obtain information for UI exploitation. In addition, the mechanism of UI in terms of community is also still unclear.

Suggested Citation

  • Yoshida, Daichi & Miyazawa, Jun-ichi & Takahashi, Shingo, 2014. "Role of community in user innovation generation and diffusion—Focusing on non-brand communities in the mountain climbing market," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 1-15.
    • Handle: RePEc:eee:tefoso:v:88:y:2014:i:c:p:1-15
    DOI: 10.1016/j.techfore.2014.06.013
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    References listed on IDEAS

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    Cited by:

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    2. Radaelli, Giovanni & Lettieri, Emanuele & Frattini, Federico & Luzzini, Davide & Boaretto, Andrea, 2017. "Users' search mechanisms and risks of inappropriateness in healthcare innovations: The role of literacy and trust in professional contexts," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 240-251.
    3. 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.
    4. 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.
    5. Li, Stacey & Modi, Pratik & Wu, Meng-Shan (Sharon) & Chen, Cheng-Hao (Steve) & Nguyen, Bang, 2019. "Conceptualising and validating the social capital construct in consumer-initiated online brand communities (COBCs)," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 303-310.
    6. Barnes, Stuart J. & Pressey, Andrew D., 2016. "Cyber-mavens and online flow experiences: Evidence from virtual worlds," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 285-296.

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