虽然新产品扩散领域有各种各样的宏观和微观层面的扩散模型，但试图将这两个

Although there are various macro- and micro-level diffusion models in the field of new product diffusion, there are still few studies trying to integrate these two-level models. This study uses an improved infectious disease model to describe the state transition probability of consumers under different new product information release methods. At the same time, the heterogeneity factors of individual consumers and the characteristics of the network topology are added to HAM to obtain target consumers and potential The probability of consumers buying a new product. The coupling model obtained by the integration of the two models overcomes the shortcomings of a single model and solves the problem of considering the influence mechanism of new product information release methods on the diffusion of new products.

Although there are various diffusion models at the macro and micro levels in the field of new product diffusion, there is still very little research to try to integrate the models at these two levels. In this study, the improved infectious disease model is used to describe the probability of change of the consumer's state under different new product information release methods, and to add the heterogeneity factors and network topology characteristics of individual consumers to HAM to obtain the probability of target consumers and potential consumers to purchase new products. The coupling model resulting from the integration of the two models overcomes the defects of a single model and solves the problem of considering the influence mechanism of new product information release on the diffusion of new products.

Although there are a variety of macro and micro diffusion models in the field of new product diffusion, there are still few studies trying to integrate the two models. In this study, an improved infectious disease model is used to describe the state transition probability of consumers under different new product information release modes, and the heterogeneity factors and network topology characteristics of individual consumers are added to ham to obtain the probability of target consumers and potential consumers to purchase new products. The coupling model obtained by the integration of the two models overcomes the defects of single model and solves the problem of considering the influence mechanism of new product information release mode on new product diffusion.<br>