Research On Customer Satisfaction Model Of Search-Experience Composite Intelligent Hardware Products

Thanks to the development of artificial intelligence,the smart hardware field,as the best application scenario of artificial intelligence,has become an emerging field where entrepreneurs get together and investors pay close attention.The product features of the combination of hardware and software of intelligent hardware are representative of products that have both search attributes and experience attributes.As domestic major Internet companies have successively entered the field of smart hardware,more and more consumers have begun to pay attention to and purchase smart hardware.On e-commerce platforms such as Jingdong Mall,the huge sales ofintelligent hardware products have brought consumers.The real use experience of intelligent hardware products is maintained on major e-commerce platforms in the form of online reviews,providing scholars with the ability to use on-line comment data from smart hardware to study customer satisfaction and provide a convenient precondition.Therefore,this paper takes the search-experience composite product type as the research perspective to explore the influencing factors of customer satisfaction in intelligent hardware products.Based on the theory of classical customer satisfaction model,this paperc consructs a search-experience composite intelligent hardware product customer satisfaction(SEIHCS)model based on the search-experience composite product type perspective.In the empirical research part,a smart speaker was used as an example to study,based on grabbed 17642 smart speaker online review data,by writing a Python program,based on self-constructed intelligent hardware domain emotional dictionary,SEIHCS model evaluation index system,SEIHCS model latent variable evaluation index Sentiment analysis algorithm completes the calculation of latent variable emotion score of SEIHCS model.Based on the latent variable emotional score data set,the SEIHCS model was tested using structural equation modeling tools.The results show that perceived hardware performance and perceived industrial design significantly positively affect perceived price value and perceived brand value,respectively;perceived content richness positively impacts perceived brand value,perceived intelligent interactivity positively affects perceived price value,and perceived third-party service quality positively influences perceived price value;perceived price value and perceived brand value positively affect customer satisfaction;customer satisfaction positively affects customer loyalty,and customer complaint negatively affects customer loyalty.This study has some theoretical and practical significance.The research conclusions provide a new product type perspective for existing research and amend the classic customer satisfaction model and provide intelligent hardware manufacturers with some product marketing and after-sale management recommendations.In addition,textual sentiment analysis is introduced in this paper.Using network data as research data source and structural equation model as research methods of analysis methods can be used as the main data sources for current online commentary related research,scenario experiment,questionnaire survey,and network data.And the important complement of the research system of the core analysis method is the structural equation model and regression analysis.