Research On The Selection Of Partners Of Customer Collaborative Innovation

Customer collaborative innovation is the concept proposed by Professor Sloan, in American MIT Management Institute's, Based on researching massive American Enterprise, in 2002. Customer collaborative innovation is one of key part of product innovations which makes use of network-based collaborative work surroundings, innovative design tools and knowledge blending method makes customers and professional designers carry out product innovative development. Customer collaborative innovation can increase value for enterprise value.Customer innovation does not mean that all users can participate in the innovative activities, when the enterprise and the customer carry on the collaborative innovation, because the difference existence in customer community at the knowledge experience and et al. there have manifest difference between difference customer. if the enterprise did not differentiate customer participates in customer innovation, there will waste the massive precious enterprise resources.Due RS is a theoretical method which is applied to study the expression, learning and inducing of incomplete and uncertain data. It can reduce the knowledge expression space; cancel the redundant information via describing the importance of different attribute in knowledge expression without prior knowledge. and SVM's high fitting precision, perfect generalization ability, global optimization and good compatibility with small samples. Based on previous studies, a partner selection model based on Support Vector Machine and Rough Sets theory is proposedFirst, introduce the representative outcome in innovation source theory and applied research and main conclusions of the measurement and correlative research in innovation customers' characteristics,Secondly, analysis the particularities of selection customer collaborative innovation partner choices, decision-making attributes are varies and the sample data used for decision-making and analysis are insufficient. and commonly used partner choice's method is suitable with difficulty for the question solution. Based on statistics theory of learning, support vector machines and in the rough collection correlation theorist's foundation, a partner selection model based on Support Vector Machine and Rough Sets theory is proposed, The key point of this model is the use of rough sets theory to pick out the important attributes as the pretreatment of data so that unimportant attributes in decision table can be deleted. Then support vector machine is used for customer classification because of its advantage of doing better than others on dealing with small sample sets and non-liner problems. This method which not affects classification performance can reduce the data dimensions and the complexity in classification process.Finally, this method is applied to the process of partner selection in customer collaborative innovation, and elaborated in detail solution process, including the data pretreatment, the parameter's selection and so on, and analysis to the model simulation result, the result of application proves the feasibility and availability of this method.