| With the development of high quality of economy and society and the continuous upgrade of Internet technology,smart phones are increasingly becoming an essential part of people’s lives.With the increasing penetration rate of smart phones,the acceleration of technological upgrading,and the frequent updating and iteration of personal mobile phones,the number of used smart phones has increased sharply,and a large number of replaced old mobile phones have not been properly disposed of.Different from ordinary electronic waste,used smart phones contain not only lead,mercury,zinc and other harmful substances that harm the natural environment and cause serious pollution,but also gold,silver,copper and other heavy metals with high recycling value.If it cannot be properly recycled,it will inevitably cause environmental pollution and waste of resources.Therefore,how to promote more waste smart phones from the hands of consumers to the recycling network has become the focus of the whole society.In 2017,China launched the Implementation Plan of the Extended Producer Responsibility System to encourage producers to shoulder the responsibility of recycling.Therefore,under the background of extended producer responsibility system(EPR),this paper studies the influencing factors of waste smart phones from consumers to recycling network nodes from different consumer preferences.According to the empirical results,the model design is carried out,and the BP neural network is used to construct the recycling mode selection model.The research finds that the neural network model is effective.It is an effective method to use BP neural network for pattern recognition and classification to help mobile phone manufacturers choose the correct recycling pattern.First of all,this paper explains the research background and significance in detail,reviews the domestic and foreign literature on the recycling mode of waste electronic products and the research on the influencing factors of waste electronic products recycling,and then defines the concept of waste smart phones studied in this paper by integrating the definitions of waste electronic products and waste mobile phones.At the same time,combined with the background of EPR,It is clear that the recycling mode studied in this paper refers to the front-end recycling mode of mobile phone manufacturers;Secondly,according to the factors that influence consumers’ willingness to participate in the recycling of used smart phones,the theoretical research model of this paper is constructed.The empirical research is mainly conducted by using reliability and validity test,correlation analysis and regression analysis,and the conclusion is drawn that the recycling price,information security,smart phone technology,service quality of recycling point and convenience of recycling channel have a significant impact on consumers’ willingness to participate in the recycling of used smart phones,and the impact degree decreases gradually.Thirdly,considering the significant influencing factors and combined with the background of extended producer responsibility system(EPR),the recycling modes of used smart phones were designed: direct recycling mode,indirect recycling mode and mixed recycling mode,and explained in detail.Then,based on the principal component analysis,the BP neural network recycling mode selection model was constructed,and the model was simulated.Through training and testing the sample data,the consumers with different preferences were selected and matched with the recycling mode of the designed waste smart phones,and the effectiveness of the model was found.Finally,an example of the application scenario of the pattern is given to prove the application value of the design pattern,and some suggestions are provided for the mobile phone manufacturers.In this paper,through the construction of BP neural network recycling mode selection model,help mobile phone manufacturers to choose the most suitable recycling mode for consumers according to the research data,in different recycling modes,analyze the consumer recycling factors and take targeted improvement measures,so as to improve the recycling efficiency of waste smart phones. |