Analyzing the Relationship between Consumer Satisfaction and Fresh E-Commerce Logistics Service Using Text Mining Techniques
| Autor: | Changyuan Zheng, Wei Hong, Xujin Pu, Linhai Wu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Knowledge management
Geography Planning and Development TJ807-830 convolutional neural network E-commerce Management Monitoring Policy and Law TD194-195 Renewable energy sources Text mining 0502 economics and business GE1-350 fresh e-commerce Reliability (statistics) Consumption (economics) Service (business) Environmental effects of industries and plants Renewable Energy Sustainability and the Environment business.industry customer satisfaction 05 social sciences Sentiment analysis Environmental sciences logistics service sentiment analysis 050211 marketing Customer satisfaction The Internet business 050203 business & management |
| Zdroj: | Sustainability Volume 11 Issue 13 Sustainability, Vol 11, Iss 13, p 3570 (2019) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su11133570 |
| Popis: | The rapid development of the Internet and the transformation of consumption patterns have prompted consumers to purchase fresh products online. For fresh e-commerce enterprises, logistics is an important aspect of customer satisfaction. Therefore, this study focused on online review information and used a convolutional neural network text mining model for its analysis. Logistics service elements concerned with customer satisfaction are convenience, communication, integrity, responsiveness, and reliability. Thereafter, comment information was converted to digital information using sentiment analysis. Finally, a correlation analysis was carried out to compare the significance of various influencing factors. The results confirm that convenience, communication, reliability, and responsiveness had a significant impact on customer satisfaction, whereas integrity had none. Fresh e-commerce logistic services need to improve for the development of the companies. |
| Databáze: | OpenAIRE |
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