This paper studies the participation behaviors in design crowdsourcing by modeling associations between participants and design contests as a bipartite network. Such a network consists of two types of nodes, participant nodes and design contest nodes, and the links indicating participating relations. Our hypothesis is that participants’ decisions are interdependent. For example, one participant’s decision on whether to participate in a contest depends on whether other participants have participated in the same contest or not. To test the hypothesis, the exponential random graph model (ERGM) is adopted. ERGM enables the utilization of various network configurations (e.g., stars and triangles) to characterize different forms of interdependencies and identify the factors that influence link formation process. Using the field data of GrabCAD — an online design crowdsourcing platform, a case study is performed. Four groups of factors are found influential to participants’ behaviors in design crowdsourcing, including designer-related, contest-related, incentive-related and decision interdependence-related factors. Our results indicate the network-based approach can successfully identify the most important factors and quantify the interdependent effects. Our results reveal interesting features about the incentives of GrabCAD, e.g., the absolute amount of the first prize does not play a significant role in attracting participants whereas the fraction does, but negatively. These insights are useful to system designers for initiating effective crowdsourcing in support of product design and development.

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