Research On The Network Structure,user Roles And Their Contribution Behavior Of Crowdsourcing Innovation Community

As a new innovation business model,the essence of crowdsourcing innovation is companies break through traditional organizational boundaries and acquire and integrating external network knowledge.Crowdsourcing community gathers the outside public,sets up appropriate guidance and reward mechanisms to obtain product effectively or service ideas to achieve the purpose of innovation through building a virtual environment.Compared with the traditional innovation model,crowdsourcing innovation based on virtual communities has the characteristics of unlimited time and place of participation,rich means of participating in innovation,supporting synchronous and asynchronous communication methods.How to manage the crowdsourcing innovation virtual community better to make the public can participate in the process of crowdsourcing innovation better and achieve more effective innovation results has become a management problem for many enterprises.Therefor this paper,based on the data form typical crowdsourcing innovation community—MIUI community,explores the issues related to evolution mechanism of the knowledge sharing network of public participation,the users’ roles and the impact of users’ network structure on their contribution behavior:(1)Research on the network structure of crowdsourcing innovation communities.Based on social network theory,explore the MIUI community static network structure analysis and dynamic network evolution trend.Through the study of the static network structure of the MIUI community,it is found that the network has the characteristics of small world,4 condensed subgroups,and the existence of a large number of structural holes.Through the study of MIUI community dynamic network evolution,it is found that its network scale growth rate conforms to the exponential contraction model,and the network evolution trend has stabilized since the 17 th quarter.Moreover,the evolution trends of network density,average closeness to center,average path and network centrality are all non-monotonic.(2)Research on identifying Users’ Roles of Crowdsourcing Innovation.After analyzing the necessity of user role recognition,This paper proposes a model integrating social network analysis(SNA)and K-means clustering algorithm to identify users’ roles,and conducting empirical.The result indicates that users’ roles can be divided into five categories: superstars,faithful supporters,positive crowds,potential creative users and negative crowds.These roles present heterogeneous characteristics in the three dimensions: interaction behavior,power and contribution behavior.Therefore,the platform must adopt targeted governance strategies to promote development healthy.(3)Research on the impact of users’ network structure and knowledge absorption capacity on their innovation contribution behavior.This paper constructs a model of the impact of uses’ network structure and knowledge absorption capacity on their contribution behavior,basing on the network theory and individual ability view,combined with social network analysis methods and related theories,and conducting empirical research with Xiaomi MIUI community.Research shows that users in the center of the network are more likely to contribute to the behavior,and the user’s knowledge absorption ability helps to stimulate the user’s crowdsourcing innovation contribution behavior.And the probability of user’s network structure advantage translating to innovative contribution behavior is depended on users’ knowledge absorption ability.The above research has certain theoretical value and practical significance for improving the related theory of crowdsourcing innovation,guiding the healthy and sustainable development of the crowdsourcing innovation platform and improving the performance of users’ crowdsourcing innovation.