Affiliation:
1. Department of Strategy and Entrepreneurship, NEOMA Business School , 59 Rue Pierre Taittinger, Reims 51100, France . e-mail: mehdi.bagherzadeh@neoma-bs.fr ; e-mail: rezvan.velayati-shokouhi@neoma-bs.fr
2. Queen's Business School, Queen's University , 185 Stranmillis Road, Belfast BT9 5EE, Northern Ireland . e-mail: a.gurca@qub.ac.uk
Abstract
Abstract
As different crowdsourcing routines (metaphorically labeled as “fishing” and “hunting” in this study) are available to address highly technical problems, solution-seeking organizations need to mindfully design, select, and deploy crowdsourcing routines that account for the behavior and motivation of experts. Drawing on a survey involving 260 experts in science, technology, engineering, and math fields, we found that elite experts (individuals with seniority, aged over 40, and a proven track record in the field with numerous publications and patents) are generally less inclined to search for crowdsourcing open calls and prefer to be contacted by solution seekers. In contrast, non-elite experts (early career experts, aged under 40, and with fewer patents and publications) actively search to find open calls. Regarding their motivational underpinnings, our findings suggest that elite experts are motivated more by non-financial incentives than non-elite experts. Furthermore, as the frequency with which they are contacted increases, non-elite experts tend to prefer more non-financial over financial incentives. These results indicate that the fishing crowdsourcing routine generally elicits solutions from unproven, non-elite experts who demand more financial rewards. However, the hunting routine taps a pool of elite experts with proven capabilities who are less financially oriented and thus may provide better, yet less expensive solutions.
Publisher
Oxford University Press (OUP)
Subject
Economics and Econometrics,General Economics, Econometrics and Finance,Management of Technology and Innovation