基于灰色关联度网络购物商品销量影响因素研究

发布时间：2019-01-27 10:32

【摘要】：随着互联网的发展、大数据时代的到来,互联网平台上呈几何级数增长的的信息量成为国内外学者关注的焦点,其中蕴含着重要的价值,通过这巨大的信息量可以进行相关的分析、决策。可以从仅凭分析者的经验、直觉、分析对象过去和现在的延续状况及最新的信息资料的旧式的定性分析来推测客户的偏好转向现代定性分析,进而通过定量分析统计数据、建立数学模型科学准确的反映民众的想法以便做出更有针对性的决策。本学位论文的研究目的就是通过对天猫手机商品的每月的相关销售数据进行分析后,得出影响其销售量的因素及影响因素与其关联程度的大小,从而为商家在激烈的竞争中如何抓住机遇吸引更多的顾客,提高网店销售量给予一定的思路。除此之外,也为今后做类似影响因素分析及关联程度大小提供一种新的思路、工具和方法——灰色关联度。本文的研究思路是在大量阅读相关文献的基础上,从定性分析和定量分析两个方面入手,通过实证分析法解决销量与价格、累计评价数、收藏商品(人气)、好评率等是否存在相关关系以及它们与销量的关联程度大小排序的问题。首先,通过问卷调查的方法收集有关信息,并答卷结果进行分析。在听取有关专家意见的基础上,初步形成定性分析的结论,即从人们熟知的在网购时所关注的商品或店铺信息中找出了影响比较大的因素等一些信息。然后,在此基础上,通过网络爬虫“集搜客”软件对有关的数据抓取,通过SPSS Modeler软件工具对数据进行预处理后,利用灰色系统理论知识结合灰色关联分析模型对有关影响因素进行定量分析。在灰色关联分析模型上的选取上,总结常见模型的优点和不足之处,并进行改进完善,使用改进后的模型进行有关定量分析,最终计算出销量与影响因素之间是否存在关联及关联程度的大小,初步得到定量分析的结论。最后,通过对所有定性、定量分析结论的综合考虑,得出最终结论,并为提高网店销售量给予一定的可行性建议,并为今后进行类似分析提供了一种思路、方法。
[Abstract]:With the development of the Internet and the arrival of big data's era, the amount of information on the Internet platform has become the focus of attention of scholars at home and abroad, which contains important value. Through this huge amount of information can be related to analysis, decision-making. From the past qualitative analysis of the past and present status of the object and the latest information, we can speculate that the customer's preference can be changed to the modern qualitative analysis based on the experience and intuition of the analyst, and then through the quantitative analysis of the statistical data. Create mathematical models that scientifically and accurately reflect people's ideas in order to make more targeted decisions. The purpose of this dissertation is to analyze the monthly sales data of Tmall's mobile phone products, and to find out the factors that affect the sales volume and the degree of correlation between them. So how to seize the opportunity in the fierce competition to attract more customers and improve the sales of online stores to give some ideas. In addition, it also provides a new way of thinking, tools and methods for the analysis of similar influencing factors and the degree of correlation in the future. On the basis of reading a large number of related documents, this paper starts with qualitative analysis and quantitative analysis, and solves the problem of sales volume and price, accumulative evaluation number, collection of commodities (popularity) through empirical analysis. Whether there is a correlation between the acclaim rate and the degree of correlation between them and the sales volume. Firstly, the information is collected by questionnaire, and the results are analyzed. On the basis of listening to the relevant experts' opinions, the conclusion of qualitative analysis is preliminarily formed, that is to say, some information such as the factors which have a great influence on the information of goods or shops that people are familiar with when buying online are found out. Then, on this basis, through the web crawler "collection search" software to grab the relevant data, through the SPSS Modeler software tools to pre-process the data, The influence factors are quantitatively analyzed by using grey system theory and grey relational analysis model. In the selection of grey relational analysis model, the advantages and disadvantages of common models are summarized, and improved, using the improved model to carry out quantitative analysis. Finally, the relationship between the sales volume and the influencing factors is calculated and the degree of correlation is calculated, and the conclusion of quantitative analysis is obtained. Finally, through the comprehensive consideration of all the qualitative and quantitative conclusions, the final conclusion is drawn, and some feasible suggestions for increasing the sales volume of online stores are given, and a kind of thinking and method are provided for similar analysis in the future.
【学位授予单位】：云南财经大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F724.6;F274

【参考文献】