电子商务的蓬勃兴起,正以前所未有的力量为全球经济的繁荣与发展注入崭新的活力源泉。特别是在农村地区,电子商务的广泛普及与深入应用,犹如一股强劲的春风,为乡村振兴战略的深入实施与共同富裕目标的稳步实现开辟了全新的路径。本文特以安徽省枞阳县为例,深入剖析并系统阐述电子商务如何凭借其独特的优势与功能,有效赋能农村地区的经济社会发展。在枞阳县,电子商务不仅极大地拓宽了农产品的销售渠道,推动了农民收入的稳步增长,还显著促进了农村消费市场的转型升级与繁荣发展。通过电子商务的桥梁作用,枞阳县的优质农产品得以跨越地域限制,走向全国乃至全球的市场,实现了价值的最大化。同时,电子商务还带动了农村地区的物流、金融等相关产业的发展,为乡村振兴注入了强大的动力,也为实现共同富裕奠定了坚实的基础。The vigorous rise of e-commerce is injecting a new source of vitality into the prosperity and development of the global economy with unprecedented strength. Especially in rural areas, the widespread popularity and in-depth application of e-commerce, like a strong spring breeze, has opened up a new path for the in-depth implementation of the rural revitalization strategy and the steady realization of the goal of common prosperity. Taking Zongyang County in Anhui Province as an example, this article deeply analyzes and systematically expounds how e-commerce can effectively empower the economic and social development of rural areas by virtue of its unique advantages and functions. In Zongyang County, e-commerce has not only greatly expanded the sales channels of agricultural products, promoted the steady growth of farmers’ income, but also significantly promoted the transformation and upgrading of the rural consumer market and the prosperity and development. Through the bridge role of e-commerce, the high-quality agricultural products of Zongyang Co
随着智能媒体技术的快速发展,算法推荐系统已成为电子商务平台的核心功能之一。本文通过文献研究和理论分析,探讨了算法推荐对消费者网购决策的心理影响,重点关注信息茧房效应和消费行为极化现象。研究结果表明,算法推荐在提升购物效率的同时,也可能通过个性化推送限制消费者的选择范围,加剧品牌忠诚度极端化和品类选择单一化。最后,本文提出了电商平台优化算法推荐和消费者教育的建议。With the rapid development of intelligent media technology, algorithm recommendation systems have become one of the core functions of e-commerce platforms. Through literature research and theoretical analysis, this paper explores the psychological impact of algorithm recommendations on consumers’ online shopping decisions, with a focus on the information cocoon effect and the phenomenon of consumption behavior polarization. The research results indicate that while algorithm recommendations enhance shopping efficiency, they may also restrict consumers’ choice range through personalized push notifications, exacerbating extreme brand loyalty and simplified category selection. Finally, this paper puts forward suggestions for e-commerce platforms to optimize algorithm recommendations and for consumer education.
