基于Vague集的电子商务购物决策的模型及应用研究

发布时间：2019-01-05 21:53

【摘要】：近年来,中国电子商务产业发展迅猛,电商平台上的海量信息为消费者提供更多购物选择的同时,也极大地增加了消费者实现最优购物决策的难度.文章提出了一种模拟消费者在电商平台上实现最优购物决策的方案——基于Vague集的两阶段模糊决策算法,模拟了消费者网购过程中的搜索路径,并最终得到最优购买决策方案.该算法首先根据目标商品的价格和质量特征对目标商品进行分类,并运用DEMATEL方法完成不同类别商品的统一化处理;然后,以消费者购物时最关心的商品价格和质量两个方面为切入点对消费者进行分类,并据此得到消费者对目标商品价格偏好系数的取值;最终,通过对传统的理想点算法进行改进,提出一套完整可行的多目标模糊算法,模拟消费者实现最优网购决策.在算法实证中,选取典型的代表性商品进行算法检验,证明了该算法的可行性及其有效性.相较于以往的研究,文章给出的算法适用于模拟各类消费者在电商平台上的购物决策,为消费者在海量信息的电商平台上实现更高效的购物策略选择提供了有效的参考.
[Abstract]:In recent years, the e-commerce industry in China has developed rapidly. The huge amount of information on the e-commerce platform provides consumers with more shopping options, but also greatly increases the difficulty for consumers to realize the optimal shopping decision. In this paper, a two-stage fuzzy decision algorithm based on Vague set is proposed to simulate the optimal shopping decision of consumers on the e-commerce platform. The search path in the process of consumer online shopping is simulated, and the optimal purchase decision scheme is obtained. Firstly, the algorithm classifies the target goods according to the price and quality characteristics of the target commodities, and uses DEMATEL method to complete the unified processing of different categories of commodities. Then, the consumers are classified from the two aspects of commodity price and quality, which are most concerned about by consumers, and the value of consumers' preference coefficient to the target commodity price is obtained. Finally, by improving the traditional ideal point algorithm, a set of complete and feasible multi-objective fuzzy algorithm is proposed to simulate the consumers to achieve the optimal online purchase decision. In the demonstration of the algorithm, typical representative commodities are selected to test the algorithm, which proves the feasibility and effectiveness of the algorithm. Compared with the previous research, the algorithm presented in this paper is suitable for simulating the shopping decisions of various consumers on the e-commerce platform, and provides an effective reference for consumers to realize more efficient shopping strategy selection on the e-commerce platform with mass information.
【作者单位】：河南师范大学数学与信息科学学院;河南财经政法大学计算机与信息工程学院;
【基金】：2017年度教育部人文社会科学研究规划基金项目(17YJA630010) 2018年河南省科技厅软科学项目资助课题
【分类号】：F724.6

【相似文献】