Crowd Science: Measurements, Models, and Methods
It addresses the need for unified measurement and modeling in crowd science, which is incremental as it builds on existing theory to standardize the field.
The paper tackles the problem of measuring and understanding the processes and benefits of IT-mediated crowd engagement across various contexts, by establishing a theoretical foundation, measures, and research methods to test efficacy.
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.