基于数据驱动模式的网络消费者购买行为特点及算例探讨

基于Internet的网络营销虚拟世界及其烟波浩淼的网上消费数据,网上消费者购买行为特点的研究模式与传统营销比较具有迥然不同的特点。文章将消费者购买行为特点的研究模式归纳成三类:经验驱动模式、理论驱动模式、数据驱动模式,并通过比较指出数据驱动模式最适用于网上消费者的购买行为特点分析。为应对互联网上庞大的数据集和提高识别效率,尝试改进了传统的SOM神经网络,并以之作为数据驱动工具对网上消费者的购买行为特点进行算例分析,运算结果具稳定健壮性。数据驱动模式用于网上消费者购买行为特点的研究是一种比较新颖的思路和方法,其有助于商家和消费者博弈双赢状态达成Pareto均衡最优。

Analysis and Simulation of Consumers' Online Purchasing Behavior Based on the Mode Driven by Data

There are vast data of consumers＇ purchasing behavior in the virtual world, which make the online shopping totally different from the traditional purchasing. This paper proposes three kinds of modes to research the consumers＇ online purchasing behavior, namely, the experience-driven mode, theory-driven mode and data-driven mode. Through comparison, the paper points out that the data-driven mode is the best to analyze the consumers＇ purchasing behavior on Internet. To cope with the vast data and increase the recognition rate, this paper tries to improve the SOM Neural Network and use it as a data-driven tool to analyze consumers＇ behavior on the Internet. It is methodologically novel to analyze the consumers＇ purchasing behavior based on data-driven mode, and will contribute to the win-win relationships between the merchants and consumers.