The Dynamic Prediction Model of Number of Participants in Software Crowd Sourcing Collaboration Development Project

Abstract

Many online platforms providing crowd with opportunities to participate in software development projects have been existed for a while. Meanwhile, many enterprises are using crowd source to collaboratively develop their software via these platforms in recent years. However, some software development projects in these platforms hardly attract users to join. Therefore, these project owners need a way to effectively predict the number of participants in their projects and accordingly well plan their software and project specifications, such as the program language and the size of the documentation, in order to attract more individuals to participant in the projects. Compared with the past prediction models, our proposed model can dynamically add the factors, such as number of participants in the initial stage of the project, within the project life cycle and make the adjustment to the prediction model. The proposed model was also verified by using cross validation method. The results show that: 1) The models with the factor "the number of user participation" is more accurate than the model without it. 2) The factors of crowd dimension are more influential on the prediction accuracy than those of software project and owner dimensions. It is suggested that the project owners not only just consider those factors of the software project dimension in the initial stage of the project life cycle but also those factors of crowd and interaction dimensions in the late stage to attract more participants in their projects.