Skip to main content

Wisdom of the Crowd within Enterprises: Practices and Challenges.

Hosseini, M., Moore, J., Almaliki, M., Shahri, A., Phalp, K. T. and Ali, R., 2015. Wisdom of the Crowd within Enterprises: Practices and Challenges. Computer Networks., 90, 121-132.

Full text available as:

Mahmood_Hosseini_et_al_ComNet_Journal_Wisdom_of_the_Crowd_within_Enterprises_Practices_and_Challenges[1].pdf - Submitted Version

Computer_networks.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


DOI: 10.1016/j.comnet.2015.07.004


The Wisdom of the Crowd advocates that decisions collectively made by a diverse crowd could be better than those made by an elite group of experts. The Wisdom of the Crowd puts preconditions on this to work correctly. This concerns the di- versity of the crowd, their independence from each other, their decentralisation, and the methods of aggregating their distributed knowledge and forming collec- tive decisions. Although the concept is inspiring, its interpretation and conduct differ significantly amongst enterprises, especially with regard to the culture and style of management. In addition, we still lack reflections on how the Wisdom of the Crowd worked in the practice of modern enterprises. To address this lack of knowledge, this paper conducts an empirical study following a mixed method approach involving 35 senior managers coming from 33 different industries in the UK. In the first phase we interview eight managers and, in the second, we con- firm and enhance the results by a survey consisting of open-ended questions and involving 27 other managers. The results shed light on the current practice of the Wisdom of the Crowd in several UK enterprises, which can inform the analysis and design of future software tools meant to aid this emerging decision-making mechanism.

Item Type:Article
Additional Information:(Special Issue on Crowdsourcing)
Uncontrolled Keywords:Wisdom of the Crowd, Collective Intelligence, Decision Making
Group:Faculty of Science & Technology
ID Code:22523
Deposited By: Symplectic RT2
Deposited On:29 Sep 2015 08:44
Last Modified:14 Mar 2022 13:53


Downloads per month over past year

More statistics for this item...
Repository Staff Only -