Research On Dynamic Evaluation Index System Of Goods’ Online Reviews

This paper is under the background of the rapid development of electronic commerce and big data rise, take the physical goods’ online reviews(original reviews and additional reviews) as the research object, analysis the change process of consumers’ concerns about the commodity property and the business service attitude, then put forward the corresponding evaluation index system and suggestions for improvement. Most of the previous studies only focus on one aspect of the original comments or additional comments, the relationship and the difference between them did not give enough attention.In order to make up for this deficiency, this paper collect the objective online reviews on the website, combined with the big data analysis idea, analysis consumers’ concerns and attitudes’ specific process of giving commodity original reviews and additional reviews, establish the corresponding partition model about commodity attribute, influencing factors of service attitude and the dynamic variation evaluation index system, then provide reference suggestions for grasping the consumer attitudes ’ change process and improving the quality of product and service.Through combining the ELM theory, the dynamic evaluation model of goods ’ online reviews was established, and put forward the structure distribution index, cross class changes index and the internal variable index, put forward structure ratio, translation rate and cross rate, concentration ratio, diffusion rate, commodity value concern, service sensitivity. Taking the Tmall ’s online comments of high-end phones and instant noodles as examples,conduct empirical studies, the application process of model and index system is explained in detail, and the applicability of the model is proved. With the help of the evaluation index, the network operators can assess the change of commodity online reviews and consumer attitudes ’ change trends.The main conclusions of this paper are as follows:(1) The additional reviews are more credible than the original reviews, more able to reflect consumers’ focus attention about goods and services, so businesses should give sufficient attention to additional reviews;(2) The ELM theory has a high applicability for examining and accepting online reviews;(3) Even in the process of online shopping, the commodity attribute and value are still the consumers’ first focus, businesses should improve the quality of service based on ensuring the quality of goods, because the service is the main cause of consumers ’ negative reviews;(4) The process of establishing the index system, the collection and data analysis takes a long time, under the background of the big data era, we should advocate business classify online reviews reasonably and develop the corresponding recognition and analysis software, which makes the evaluation index system more user-friendly.On one hand, the results and conclusions obtained in this paper can provide a simple and effective analysis method for the net business; On the other hand, businesses can fully aware of the potentially significant role of massive online reviews, we should encourage businesses exploit new tools, new methods for data mining, then create more value for the enterprise.