电子商务环境下动态团购模型及团购算法

Xiaoxiao Wang
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引用次数: 0

摘要

近年来,由于我国互联网电子商务产品服装行业的快速发展,b2c、b2b等一批全球性的电子商务模式应运而生,使得线上的虚拟购物和线下的实体消费模式迅速兴起。b2c网络团购商业模式以其诸多特点和优势,在欧美等发达国家稳步推进。网络团购作为一种新型的电子商务模式,以其不断完善的特点,受到了越来越多网民的广泛喜爱和青睐。如何让网络上的用户和商家共同从团购中获得收益的最大化,是近年来许多研究者关注的问题。本文主要从传统的电子商务模式出发,通过文献研究法、案例研究法、问卷调查法和归纳推演法,探讨和分析电子商务环境下企业集团形成的动态和集团管理模式及其算法。对现有的网络团购进行分析,基于现有网络团购中的消费者满意度和消费者购买价格两个方面,提出了一种新的动态团购模型,并在此基础上提出了一种新的团购算法。具有相同偏好的消费者聚集在一起,使消费者在数量上占有优势,在价格上获得折扣。在此动态团购模型的基础上,利用群体算法为消费者选择满意度和价格综合指数较高的产品,也能有效提高商家的销售额,从而在一定程度上保证商家和消费者的利益最大化。实验结果表明,我国网络购物市场规模已达1.89万亿,显示出我国网络购物市场的巨大潜力。电子商务平台B2C市场也在快速增长,更多的传统行业将加入B2C电子商务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Group Purchase Model and Group Algorithm in E-commerce Environment
In recent years, due to the rapid development of my country's Internet e-commerce product apparel industry, a number of global e-commerce models such as b2c and b2b have emerged, making online virtual shopping and offline physical consumption models rapidly emerging. The b2c online group buying business model has been steadily promoted in developed countries such as Europe and the United States due to its many characteristics and advantages. Online group buying, a new e-commerce model with its continuous improvement characteristics, has been widely loved and favored by more and more Internet users. How to let users and merchants on the network jointly obtain the maximization of revenue from group buying has been a problem that many researchers have paid close attention to in recent years. This article mainly aims to discuss and analyze the dynamics of enterprise group formation and group management mode and its algorithm in the e-commerce environment, through the literature research method, case study method, questionnaire survey method and inductive deduction method from the perspective of the traditional e-commerce model. Analyze the existing online group buying, and propose a new dynamic group buying model based on the two aspects of consumer satisfaction and consumer purchase price in the existing online group buying, and put forward a new group buying algorithm based on this group buying model. Consumers with the same preferences gather together, so that consumers have an advantage in quantity and can get discounts on prices. On the basis of this dynamic group buying model, the group algorithm is used to select products with higher satisfaction and price comprehensive index for consumers, which can also effectively increase the sales of the merchants, thereby ensuring the maximum benefits of the merchants and consumers to a certain extent. The experimental results show that the scale of our online shopping market has reached 1.89 trillion, showing the huge potential of my country's online shopping market. The e-commerce platform B2C market is also growing rapidly, and more traditional industries will join B2C e-commerce.
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