Research On Control Strategy Of Users' Sustained Knowledge Sharing Behavior In Crowdsourcing Innovation

Crowdsourcing innovation,as a new innovation model,refers to the business model that the enterprise carries out the innovative task which is traditionally performed by the internal staffs and transfers it to the external network users(public)in a free and voluntary form.The model has been proved to be an effective model for acquiring the external network knowledge in practice.More and more enterprises have also started to build different crowdsourcing innovation models.However,with the continuous development of the crowdsourcing innovation model,there has been a problem of the lack of users' sustained participating willingness in crowdsourcing innovation in practice.Therefore,how to design an effective control strategy for a crowdsourcing innovation platform to guide and motivate users to continue to share knowledge,and how to properly formulate strategies for recognizing users' opportunistic behavior has become a key issue that needs to be solved urgently.Based on the above problems,this paper mainly explores the issues related to the users' sustained knowledge sharing behavior control strategy in crowdsourced innovation:(1)Research on the influencing factors of sustained knowledge sharing behavior of users participating in crowdsourcing innovation.Considering that crowdsourcing innovation belongs to a new type of business model,the grounded theory,as an important inductive research method,has the advantages of emphasizing practice and comparative research.It proposes using the grounded theory to study the influencing factors of users' sustained participation in crowdsourcing innovation.Theoretical sampling from the domestic typical crowdsourcing platform(zhubajie.com,task.cn)has been uesd.Through the analysis of the specific implementation process of open coding,spindle coding,selective coding,and theoretical saturation testing,it forms the model of the influencing factors for users' sustained participation in crowdsourcing innovation.(2)Research on the dynamic optimal control of users' sustained knowledge sharing behavior.Taking into account the complexity of innovative tasks and the "stickiness" of knowledge,it needs to guide and motivate users' sustained participation in crowdsourcing innovation,which requires enterprises to take effective control strategies to ensure the sustaining knowledge acquisition to complete innovative tasks.Based on the theory of relation marketing and knowledge sharing,this paper defines the concept of knowledge commitment in crowdsourcing innovation process.The key effect factors of knowledge commitment are analyzed,and it extracts trust,perceived value satisfaction level,knowledge acquisition efforts and opportunistic tendency as key factors.The dynamic optimal decision model of knowledge acquisition in crowdsourcing innovation is established,and it is solved via the dynamic optimization techniques.The optimal decision results of knowledge acquisition are discussed with the sensitivity analysis.(3)Research on users' opportunistic behavior recognition strategies in crowdsourcing innovation.In order to ensure high quality and users' sustained knowledge in crowdsourcing innovation,it is necessary to identify and control users' opportunistic behavior.From the crowdsourcing innovation management practice,we analyze the reasons and performances of users' opportunism,and build an opportunistic behavior recognition system.A method of identifying users' opportunistic behavior based on PCA-BP neural network is proposed.We take the domestic famous crowdsourcing innovation platform(zhubajie.com)as the research object,and comduct an empirical research by grabbing webpage data.The results show that the model is feasible and effective.The above research has certain theoretical and practical significance for improving crowdsourcing innovation theories,and enhancing users' sustained knowledge-sharing performance and promoting continuous and healthy development of crowdsourcing innovation platform.