Aligning the crowdsourcing type with the problem attributes to improve solution search efficacy. (January 2023)

• Record Type: Journal Article
• Authors: Gurca, Andrei; Bagherzadeh, Mehdi; Velayati, Rezvan
• Is Part Of: Technovation. Volume 119(2023)
• Publication Date: 2023-01
• Subjects: Crowdsourcing -- Problem attributes -- Bounded rationality; Technological innovations -- Periodicals; Industrial management -- Periodicals; Innovations -- Périodiques; Gestion d'entreprise -- Périodiques; Electronic journals; 658.57
• DOI: 10.1016/j.technovation.2022.102613
• Languages: English
• ISSNs: 0166-4972

Abstract

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. Highlights: The prevailing type of crowdsourcing has several limitations and usually fails to address problems with certain attributes. Emerging types of crowdsourcing may generate appropriate solutions for problems that are broad, urgent, and highly technical. Our insights highlight the importance of alignment between crowdsourcing type and problem attributes.