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Prediction and Evaluation Method of e-Commerce Service Satisfaction Based on Intelligent Computing Method
Among the many service industries, e-commerce, which is based on the Internet and relies mainly on platforms and third-party transaction models, has developed rapidly. All localities have actively deployed their regional e-commerce development strategies to improve the core competitiveness of the re...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9448570/ https://www.ncbi.nlm.nih.gov/pubmed/36082354 http://dx.doi.org/10.1155/2022/2730660 |
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author | Tu, Fang Tu, Bo |
author_facet | Tu, Fang Tu, Bo |
author_sort | Tu, Fang |
collection | PubMed |
description | Among the many service industries, e-commerce, which is based on the Internet and relies mainly on platforms and third-party transaction models, has developed rapidly. All localities have actively deployed their regional e-commerce development strategies to improve the core competitiveness of the regional economy. The rapid development of e-commerce provides a favorable development environment and construction environment for the spatial agglomeration of e-commerce service industry. We use the intelligent computing method to calculate the e-commerce service degree prediction experimental results that show that according to the curves of the three algorithms, we can also see that the curve values of the intelligent computing and fuzzy statistical algorithm models are very stable and the experimental results are also very stable. It shows that the performance of the intelligent computing algorithm is the most superior; the second-level indicators are the after-sales service of the merchant, the popularity of the merchant, and the attitude of the merchant's customer service; in the establishment of the logistic satisfaction evaluation index system, we found that the logistic satisfaction is the first-level indicator; the secondary indicators are the speed of logistics, the safety of logistics, the service attitude of logistics, and the price of logistics; after running on the test set, the model accuracy rate of the fuzzy statistical algorithm is 89.12%, and the accuracy rate can reach 89.56%. The accuracy rate of the intelligent algorithm can reach 92.46%, and the accuracy rate can reach 93.27%, which is the one with the highest index value among the three experimental models. Among the many service industries, e-commerce, which is based on the Internet and relies on platforms and third-party transaction models, is developing rapidly. All localities have actively deployed their regional e-commerce development strategies to improve the core competitiveness of the regional economy. The rapid development of e-commerce provides a favorable development environment and construction environment for the spatial agglomeration of e-commerce service industry. |
format | Online Article Text |
id | pubmed-9448570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94485702022-09-07 Prediction and Evaluation Method of e-Commerce Service Satisfaction Based on Intelligent Computing Method Tu, Fang Tu, Bo Comput Intell Neurosci Research Article Among the many service industries, e-commerce, which is based on the Internet and relies mainly on platforms and third-party transaction models, has developed rapidly. All localities have actively deployed their regional e-commerce development strategies to improve the core competitiveness of the regional economy. The rapid development of e-commerce provides a favorable development environment and construction environment for the spatial agglomeration of e-commerce service industry. We use the intelligent computing method to calculate the e-commerce service degree prediction experimental results that show that according to the curves of the three algorithms, we can also see that the curve values of the intelligent computing and fuzzy statistical algorithm models are very stable and the experimental results are also very stable. It shows that the performance of the intelligent computing algorithm is the most superior; the second-level indicators are the after-sales service of the merchant, the popularity of the merchant, and the attitude of the merchant's customer service; in the establishment of the logistic satisfaction evaluation index system, we found that the logistic satisfaction is the first-level indicator; the secondary indicators are the speed of logistics, the safety of logistics, the service attitude of logistics, and the price of logistics; after running on the test set, the model accuracy rate of the fuzzy statistical algorithm is 89.12%, and the accuracy rate can reach 89.56%. The accuracy rate of the intelligent algorithm can reach 92.46%, and the accuracy rate can reach 93.27%, which is the one with the highest index value among the three experimental models. Among the many service industries, e-commerce, which is based on the Internet and relies on platforms and third-party transaction models, is developing rapidly. All localities have actively deployed their regional e-commerce development strategies to improve the core competitiveness of the regional economy. The rapid development of e-commerce provides a favorable development environment and construction environment for the spatial agglomeration of e-commerce service industry. Hindawi 2022-08-30 /pmc/articles/PMC9448570/ /pubmed/36082354 http://dx.doi.org/10.1155/2022/2730660 Text en Copyright © 2022 Fang Tu and Bo Tu. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Tu, Fang Tu, Bo Prediction and Evaluation Method of e-Commerce Service Satisfaction Based on Intelligent Computing Method |
title | Prediction and Evaluation Method of e-Commerce Service Satisfaction Based on Intelligent Computing Method |
title_full | Prediction and Evaluation Method of e-Commerce Service Satisfaction Based on Intelligent Computing Method |
title_fullStr | Prediction and Evaluation Method of e-Commerce Service Satisfaction Based on Intelligent Computing Method |
title_full_unstemmed | Prediction and Evaluation Method of e-Commerce Service Satisfaction Based on Intelligent Computing Method |
title_short | Prediction and Evaluation Method of e-Commerce Service Satisfaction Based on Intelligent Computing Method |
title_sort | prediction and evaluation method of e-commerce service satisfaction based on intelligent computing method |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9448570/ https://www.ncbi.nlm.nih.gov/pubmed/36082354 http://dx.doi.org/10.1155/2022/2730660 |
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