跨境电商作为国际贸易的重要形式,在全球化与数字化的推动下迅速发展,其相关研究对于行业实践与学术进步具有重要意义。本研究采用基于CiteSpace的知识图谱可视化分析、作者及机构合作分析等方法,全面梳理了跨境电商领域的研究进展。一方面,通过对关键词共现、聚类和突现分析,展现了跨境电商研究主题的演变轨迹、热点变化以及不同阶段的特点;另一方面,通过分析作者分布,探讨了学术合作网络的层级结构、复杂性以及机构间的合作模式。研究表明,跨境电商的研究呈现出多维度交织且动态发展的态势,作者与机构合作具有不同特点并发挥各自的作用。在此基础上,本文对未来研究进行了展望,提出了在理论构建中融合多学科视角、在实践应用中关注新兴技术的影响,以及加强作者与机构间的合作等方向,以期进一步深化跨境电商研究,推动行业的持续发展,并为国际贸易的进步贡献力量。Cross border e-commerce, as an important form of international trade, has rapidly developed under the promotion of globalization and digitization. Its related research is of great significance for industry practice and academic progress. This study comprehensively reviewed the research progress in the field of cross-border e-commerce using methods such as CiteSpace based knowledge graph visualization analysis and author institution collaboration analysis. On the one hand, through the analysis of keyword co-occurrence, clustering, and emergence, the evolution trajectory, hot topic changes, and characteristics of cross-border e-commerce research themes at different stages have been demonstrated;On the other hand, by analyzing the distribution of authors, the hierarchical structure, complexity, and inter institutional cooperation patterns of academic collaboration networks were explored. Research has shown that the study of cross-border e-commerce presents a multidimensional and dynamic development trend, and the collaboration between authors and institutions has different characteristics and plays their respective roles. On this basis, this article looks forward to future research and proposes directions such as integrating multidisciplinary perspectives in theoretical construction, paying attention to the impact of emerging technologies in practical applications, and strengthening cooperation between authors and institutions, in order to further deepen cross-border e-commerce research, promote the sustainable development of the industry, and contribute to the progress of international trade.
在信息技术不断进步和农村基础设施日益完善的背景下,电子商务已逐步渗透到农村市场,并成为推动农业现代化的重要动力。然而,农村电商的发展仍面临诸多挑战,如商品质量参差不齐、专业人才缺乏、物流效率低下等问题。为了更准确地预测农村电商的市场趋势,为电商企业和政策制定者提供科学的数据支持,本研究提出了一种基于长短时记忆网络(Long-Short Term Memory, LSTM)的时间序列预测模型,并结合注意力机制(Attention Mechanism)和卡尔曼滤波(Kalman filter)技术,对2024~2026年农村网络零售额进行预测。实验结果表明,引入注意力机制和卡尔曼滤波后,模型的预测精度显著提升,均方误差(mean-square error, MSE)、均方根误差(root-mean-square error, RMSE)和平均绝对误差(Mean absolute error, MAE)均有所降低。研究结果为农村电商的市场趋势分析和政策制定提供了科学依据,具有重要的现实意义。With continuous advancements in information technology and the gradual improvement of rural infrastructure, e-commerce has increasingly penetrated rural markets, becoming a key driver of agricultural modernization. However, its development still faces numerous challenges, such as inconsistent product quality, a shortage of skilled professionals, and low logistics efficiency. To more accurately predict market trends in rural e-commerce and provide scientific data support for e-commerce enterprises and policymakers, this study proposes a time series prediction model based on Long Short-Term Memory (LSTM) networks, incorporating an attention mechanism and Kalman filter techniques to forecast rural online retail sales from 2024 to 2026. The experimental results indicate that the introduction of the attention mechanism and Kalman filter significantly improves the model’s prediction accuracy, reducing the mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE). The findings provide a scientific basis for market trend analysis and policy formulation in rural e-commerce, offering important practical significance.
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