Crowd Science: Measurements, Models, and Methods

Prpić, J., & Shukla, P. (2016). Crowd Science: Measurements, Models, and Methods. Proceedings of the Hawaii International Conference on System Sciences #49. January 2016, Kauai, Hawaii, USA. IEEE Computer Society Press.

10 Pages Posted: 19 Sep 2015 Last revised: 11 Apr 2016

Date Written: September 14, 2015

Abstract

The increasing practice of engaging crowds, where organizations use IT to connect with dispersed individuals for explicit resource creation purposes, has precipitated the need to measure the precise processes and benefits of these activities over myriad different implementations. In this work, we seek to address these salient and non-trivial considerations by laying a foundation of theory, measures, and research methods that allow us to test crowd-engagement efficacy across organizations, industries, technologies, and geographies. To do so, we anchor ourselves in the Theory of Crowd Capital, a generalizable framework for studying IT-mediated crowd-engagement phenomena, and put forth an empirical apparatus of testable measures and generalizable methods to begin to unify the field of crowd science.

Keywords: Crowd Science, Crowdsourcing, Crowdfunding, Citizen Science, Human Computation, Meta-Analysis, Natural Experiments, Crowd Capital, Empirical Methods,

Suggested Citation

Prpić, John and Shukla, Prashant, Crowd Science: Measurements, Models, and Methods (September 14, 2015). Prpić, J., & Shukla, P. (2016). Crowd Science: Measurements, Models, and Methods. Proceedings of the Hawaii International Conference on System Sciences #49. January 2016, Kauai, Hawaii, USA. IEEE Computer Society Press., Available at SSRN: https://ssrn.com/abstract=2660638

John Prpić (Contact Author)

Thompson Rivers University ( email )

900 McGill Road
IB2008
Kamloops, BC V2C 5N3
Canada

Prashant Shukla

Accenture ( email )

Dublin
Ireland

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