Research On Identification And Avoidance Strategy Of Solver's Opportunistic Behaviorin Crowdsourcing Innovation

As a new type of innovation model,crowdsourcing innovation refers to the business model that the company or organization transfers the internal innovation problems solved by employees to the external network public in the past.By adopting crowdsourcing innovation mode to acquire and integrate external network knowledge,enterprises can transform creativity,wisdom and skills into business value and social value.However,as a new business model,its network operation mode,high demand for knowledge sharing,multi-agent participation in the cooperation process and other characteristics lead to opportunistic behaviors such as scheme fraud,intellectual property theft,induced bid selection,malicious evaluation and so on,which seriously affect the final solution quality and platform reputation.Therefore,it is of great guiding value to scientifically identify the opportunistic behaviors of contractors and adopt targeted governance strategies for the effective implementation of crowdsourcing innovation mode and the creation of a good crowdsourcing environment.Based on this,this paper mainly explores the recognition of opportunistic behavior of the receiver under the crowdsourcing innovation mode and the related problems of the evasion strategy.(1)The reason and main performance of solver's opportunistic behaviors in crowdsourcing innovation.Starting from the specific management practice of crowdsourcing innovation,combining the characteristics of crowdsourcing innovation mode,analyze and summarize the reasons for the opportunistic behavior of the receiving party and the main performance of the opportunistic behavior,which is the foundation for the subsequent research.(2)Research on recognition methods of solver's opportunistic behaviors in crowdsourcing innovation.This paper constructs the recognition system of the solvers' opportunistic behaviors involved in crowdsourcing innovation by analyzing the main manifestations and reasons of their opportunistic behaviors.Using the MIV(Mean Impact Value)algorithm to screen the sensitivity indicators in the recognition system,and an opportunistic behaviors recognition model of solvers' participation in crowdsourcing innovation based on MIV-BP neural network is proposed.The empirical analysis is carried out in combination with zbj.com to verify the feasibilityof the recognition method.(3)In order to effectively deal with the solver's opportunistic behavior in crowdsourcing innovation,this paper builds an evolutionary game model based on the punishment mechanism between the solver and the crowdsourcing platform.Explore the impact of platform supervision mechanism,punishment mechanism and contractor exposure on the strategic choices of both parties.Through the analysis of the model evolutionary stability strategy establishment conditions,to find the key factors that affect the strategic choices of both parties.The research shows that the punishment mechanism has a certain degree of restraint on the solver's opportunistic behavior,but it has a limited impact on the strategy of the crowdsourcing platform.With the increase of punishment,it can effectively restrict the dishonest behavior of solvers and reduce the adverse selection caused by information asymmetry.(4)From the perspective of reputation,to find out the key factors that affect the solver's behavior,so as to more effectively suppress the opportunistic behavior of the solver.Based on the original evolution model,the influence of the reputation effect of the solver and the crowdsourcing platform is introduced to analyze the strategic choices of both sides of the game.By analyzing the evolution of the model and stabilizing the strategic conditions,the key factors affecting the strategic choices of both parties are found.The research found that with the deepening of the reputation effect,the solvers and crowdsourcing platforms will pay more and more attention to their own reputation and social effects.In this state,the solvers will consciously correct their behavior,and the platform will choose strict supervision to establish a fair image,and the crowdsourcing model can develop healthily in a fair and honest environment.The above research is of great significance for expanding the theoretical research perspective of crowdsourcing innovation,effectively identifying and circumventing solver's opportunistic behavior,and reducing the risk of crowdsourcing innovation.