Research On Bilateral Matching Of Process Crowdsourcing Tasks In Automobile Molds

With the rapid development of Internet technology and in-depth study of crowdsourcing model in China,more and more enterprises begin to use crowdsourcing to solve R&D and manufacturing problems within enterprises.Automobile has a huge consumer market in the world,and the automobile industry and its related industries,as the pillar industries in many countries,largely reflect the level of national economic development.How to use crowdsourcing to integrate social resources,make full use of our country’s huge market advantages and extensive talent advantages,and realize the reasonable matching of design tasks and technical personnel by crowdsourcing platform is of great significance to improve the quality and efficiency of automobile die process design and promote the innovation and development of automobile die industry.In order to solve the above problems,this dissertation considers the matching degree between crowdsourcing task requirements and crowdsourcing user capabilities,and takes the preference degree of crowdsourcing user for crowdsourcing task selection into consideration.It also analyses and studies the bilateral matching problem based on crowdsourcing task and user satisfaction.Firstly,the organization mode,matching principle and influencing factors of crowdsourcing activities are discussed,and the bilateral matching decision-making is studied.The problem of bilateral matching based on crowdsourcing tasks and user satisfaction is analyzed in detail,and the process framework of bilateral matching between crowdsourcing tasks and users is constructed.Secondly,this paper evaluates the user’s satisfaction with tasks in bilateral matching,regards the competency level of users to crowdsourcing tasks as the satisfaction degree of tasks in bilateral matching,analyses and studies the evaluation of user’s competence in crowdsourcing design,establishes the competency evaluation model of users in crowdsourcing design,and obtains the evaluation number of task’s satisfaction to users in bilateral matching.Thirdly,it evaluates the user’s satisfaction with tasks in bilateral matching.The user’s preference degree for different types of tasks in crowdsourcing task selection is regarded as the user’s satisfaction with tasks in bilateral matching.The user’s task orientation is analyzed,and the classification model of crowdsourcing tasks in automobile die and die process is established.On this basis,the user’s task orientation is evaluated.Directional evaluation is analyzed and studied.User satisfaction evaluation data of bilateral matching are obtained.Finally,a two-sided matching model of crowdsourcing task and design user is constructed,and a method for calculating the satisfaction degree of crowdsourcing task and design user is proposed.An example is given to verify the data information of crowdsourcing task and design user in the crowdsourcing platform of automotive die process.The matching result is obtained by calculating the satisfaction degree of both matching parties and solving the model.The matching results are compared,which proves the validity of the matching method in this dissertation.