Crowdsourced Knowledge in Organizational Decision Making
Abstract
Inefficiencies naturally form as organizations grow in size and complexity. The knowledge required to address these inefficiencies is often stove-piped across different organizational silos, geographic locations, and professional disciplines. Crowdsourcing provides a way to tap into the knowledge and experiences of diverse groups of people to rapidly identify and more effectively solve inefficiencies. We developed a prototype crowdsourcing system based on design thinking practices to allow employees to build a shared mental model and work collaboratively to identify, characterize, and rank inefficiencies, as well as to develop possible solutions. We conducted a study to assess how presenting crowdsourced knowledge (votes/preferences, supporting argumentation, etc.) from employees affected organizational Decision Makers (DMs). In spite of predictions that crowdsourced knowledge would influence their decisions, presenting this knowledge to DMs had no significant effect on their voting for various solutions. We found significant differences in the mental models of employees and DMs. We offer various explanations for this behavior based on rhetorical analysis and other survey responses from DMs and contributors. We further discuss different theoretical explanations, including the effects of various biases and decision inertia, and potential issues with the types of knowledge elicited and presented to DMs.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 02, 2022
- Source ID
- 10.3390/knowledge2010002
Entities
People
- Leeann R. Maryeski
- Lillian K. E. Asiala
- Samantha B. Harper
- Stephen L. Dorton
Organizations
- Office of Naval Research