Monitoring the internet media opinion information quickly triggered by the implementation of the “double reduction” policy, and identifying the hot spots, tendencies, communication trends, and characteristics of media opinion are of great significance to government departments to grasp the dynamics of media opinion in time and assist them in decision-making. This paper uses the web crawler to dynamically collect the internet media opinion big data related to the “double reduction” of main media and utilizes text analysis and data mining technologies to dynamically monitor the hot spots, topic tendencies, and communication characteristics of media opinion. Taking the internet media opinion data on the implementation of the “double reduction” policy from January 1, 2021 to November 15, 2021 as the sample, the paper analyzes the media opinion of the implementation of the “double reduction” policy. The high incidence period of media opinion is consistent with the opening of primary and secondary schools, holidays, and the introduction of relevant policies. The topics of internet media opinion are highly targeted and cover a wide range. The media focuses on the implementation measures, new problems, new phenomena, effects, and evaluation of the “double reduction” policy in education. Strong provinces of education, large provinces of education, and difficult provinces of education are the main areas for media public opinion monitoring. The media opinion is in the fermentation stage, and there is no sign of heat reduction. The propagation of media opinion is in line with the theoretical characteristics of information propagation life cycle. This paper only takes the internet media opinion of the main network media as the monitoring object. Whether it is suitable for the media opinion of the whole network media needs to be further tested.

This article explores the opportunities, challenges, as well as the activities of the Chinese governmental and commercial stakeholders to promote cross-border e-commerce trade between China and Africa, based on the classification and correlation analysis of the literature from 2011 to 2019. The results show that the biggest driver for the development of China-Africa cross-border e-commerce trade is the gap between the rapid growth of the African population, especially the middle class, and the limited local capability to satisfy their demand. The rapid development of the internet and mobile internet is another driving factor. The biggest challenge is the last mile delivery of logistics, and online payment issues in Africa. At the macro-level the Chinese government has promoted measures such as infrastructure investment, e-commerce test zones and the establishment of pilot projects. At the firm level, Chinese companies have focused on solving practical micro-level local operational problems such as logistics, online payment, and talent training. The results also show that the referred literature is still in its infancy, mostly theoretical and less practical, and requires more in-depth domain specific analysis in the future.

Sustainable development integrates business, environmental, and social objectives into a unified effort to achieve a common goal. Sustainable customer relationship management (CRM) combines company strategy, customer-focused business processes, and computer technologies. From the consumer’s perspective, it lowers psychological, energy, time, and other costs; from the company’s perspective, it offers a means of engaging with customers to build lasting and reliable relationships. The sustainable CRM program provides advantages to businesses in various industries, particularly online commerce. It alludes to a comprehensive strategy that promotes solid interactions between buyers and sellers of goods and services. Since current customer retention is less costly than new customer attraction in competitive markets, especially online shopping, identifying the factors affecting relationship management with stable customers is essential. This investigation intends to evaluate the effect of the use of management information systems (MIS), as well as insights on employee behavior and knowledge, and customer behavior (satisfaction and loyalty), on the effectiveness of sustainable CRM in online shopping. The model is validated using the PLS–SEM technique, and study sample of 293 employees and managers from private organizations. According to the results, the MIS, employee behavior and knowledge, customer satisfaction, and customer loyalty influence the effectiveness of sustainable CRM in online shopping. Furthermore, employee behavior and knowledge positively moderate the relationship between customer loyalty and the effectiveness of sustainable CRM. However, the moderating role of employee behavior and knowledge on customer satisfaction and the effectiveness of sustainable CRM is not confirmed. Overall, taking these characteristics into account might help organizations to take significant steps toward increasing the efficacy of sustainable CRM.

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With the advent of the crossborder e-commerce (CE) boom, more and more traditional enterprises have transformed into the field of crossborder e-commerce. It has become a new outlet for enterprises in the international trade environment, and at the same time, it has some problems in the utilization of resources and the maximization of benefits. In response to this problem, it is very important to optimize the export operation model of crossborder e-commerce enterprises (CEE). With the development of intelligent algorithms, research on the application of intelligent algorithms to the economic field has gradually been carried out. Its characteristics and advantages are of great significance to the optimization of CEE export operation mode. The purpose of this paper is to study the CEE export operation mode and optimization strategy based on data mining algorithm (DMA). Through the analysis and research of DMA, it can be applied to the optimization of CEE export operation mode to cope with the world trade in the new environment. This paper explains the basic theory of DMA and CEE export operation mode. Its effect is experimentally analyzed, and the relevant theoretical formulas are used to explain. The results show that the comprehensive trade quality index of the CEE export operation mode integrating DMA is higher, and the adaptability is stronger. Compared with the traditional operating model, the difference between the two indices is 3.175 index points. It has guiding significance in terms of CEE export operation mode and optimization strategy.