Improved Bayesian Causal Map Approach for Community-Based Product Design Project Feasibility Analysis

The development of sharing economy and social media technology leads to a new design mode-community-based product design (CPD), including crowdsourcing design, open source design, and maker product design. CPD projects have the potential to use socialized design resource for creative product development because they are openly participated by a large number of socialized designers. However, CPD projects are unreliable, unpredictable, and usually endure low success rate. We believe that the reason for these problems is that many unreliable factors caused by the nature of CPD mode are disturbing the implementation of CPD projects, but few research works can provide systematic and quantitative understanding of the relationship between these factors and CPD project feasibility, which makes it difficult for stakeholders to evaluate and manage their CPD projects. To mitigate these problems, in this paper an improved Bayesian causal map approach is developed and used to build a CPD project feasibility analysis model. The model can reveal the interaction relationship among the factors, and provide quantitative evaluation of CPD project feasibility given the states of the factors. In this way, the model can help the stakeholders in CPD project management by showing them which factors require priority processing and providing them with the prediction of project success rate, and eventually improve the overall reliability of CPD projects. The model has been verified through sensitivity analysis and post analysis on real CPD projects.