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Aligning the crowdsourcing type with the problem attributes to improve solution search efficacy

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  • Gurca, Andrei
  • Bagherzadeh, Mehdi
  • Velayati, Rezvan

Abstract

Drawing on the concept of bounded rationality and extant evidence, we argue that for specific problems (broad and ill-defined, urgent, highly technical), the prevailing approach to crowdsourcing (metaphorically labeled as “fishing” in this study) has several limitations that affect the quality of emerging solutions. For such problems, we argue that other types of crowdsourcing (i.e., collective production and “hunting”) may generate more appropriate solutions. Our insights regarding the solution search process advance the literature by highlighting the importance of alignment between crowdsourcing type and problem attributes. We also provide a decision framework for managers suggesting how they can select the most appropriate type of crowdsourcing for their solution searching efforts.

Suggested Citation

  • Gurca, Andrei & Bagherzadeh, Mehdi & Velayati, Rezvan, 2023. "Aligning the crowdsourcing type with the problem attributes to improve solution search efficacy," Technovation, Elsevier, vol. 119(C).
    • Handle: RePEc:eee:techno:v:119:y:2023:i:c:s0166497222001602
    DOI: 10.1016/j.technovation.2022.102613
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    References listed on IDEAS

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    Cited by:

    1. Evangelos Mourelatos & Jaakko Simonen & Simo Hosio & Daniil Likhobaba & Dmitry Ustalov, 2024. "How has the COVID-19 pandemic shaped behavior in crowdsourcing? The role of online labor market training," Journal of Business Economics, Springer, vol. 94(9), pages 1201-1244, November.
    2. Mahotra, Arvind & Majchrzak, Ann, 2024. "Digital innovations in crowdsourcing using AI tools," Technovation, Elsevier, vol. 133(C).
    3. Bonazzi, Riccardo & Viscusi, Gianluigi & Solidoro, Adriano, 2024. "Crowd mining as a strategic resource for innovation seekers," Technovation, Elsevier, vol. 132(C).

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