As the platformization of Crowd Intelligence Design (CID) advances and online collaboration deepens, crowd intelligence design platforms have evolved into digital ecosystems constituted by interactions between requesters and designers. Consequently, understanding agent heterogeneity and the underlying knowledge-value interaction mechanisms is critical for achieving precision incentives and effective governance within these ecosystems. Existing research predominantly relies on system-level macro indicators to describe evolutionary trends, often lacking detailed characterization of specific knowledge structures and their processes of entry, turnover, and utilization; consequently, it remains difficult to uncover the micro-level evolutionary behavioral characteristics of Crowd Intelligence Design Ecosystems. To fill this gap, this paper proposes an evolutionary analysis framework based on a dual perspective of the Knowledge Network and the Value Network. Empirical results based on data from the EPWK platform demonstrate that this framework achieves an integrated analysis bridging resource evolution and population evolution. It reveals major migration channels and possible upward mobility patterns observed in the EPWK platform dataset, providing an empirical basis for discussing stratified governance in crowd intelligence design platforms.
Wang et al. (Thu,) studied this question.