A decision support model for estimating participation-oriented designs of crowdsourcing platforms based on quality function deployment

The designs presented in crowdsourcing platforms for supporting, facilitating, and regulating solvers' behaviors have significantly effect on solvers' decision to participate. To estimate those important designs, referred to as participation-oriented designs in this study, a decision support model is developed based on quality function deployment (QFD). This model connects participation-oriented designs to solvers' motives through the matched incentives, ensuring the estimated designs could activate solvers' motives most. Specifically, the relations among these three aspects are represented by two house of quality (HoQ) models in which one links solver motives and incentives and the other connects the incentives and participation-oriented designs. Moreover, a combination of the fuzzy Delphi method (FDM), fuzzy Best-Worst method (BWM), and fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL) is developed to handle information in these two HoQ models. Therein, the FDM is employed to screen and map solver motives, incentives, and participation-oriented designs. The fuzzy BWM is used to determine the relationship weights between solver motives and incentives and incentives and participation-oriented designs respectively. The fuzzy DEMATEL is employed to describe and calculate the inner dependencies of incentives and participation-oriented designs respectively. A case of the crowdsourcing platforms for graphic design contests is presented to demonstrate the effectiveness and practicability of the proposed model.