数字营销市场规模影响因素及预测的研究
[毕业论文关键词]：数字营销；回归分析；主成分分析；逐步回归；ARIMA模型
Abstract
In recent years, digital marketing industry is developing rapidly and continuously in China, researching on the influence factors of digital marketing’s market scale becomes an important subject, which can find out the important factors and bring entrepreneurs useful information when they do marketing, but also can provide entrepreneurs with how to develop digital marketing channels and expand market. Firstly, according to the reference data and personal judgment, I selected 20 primary factors, and collected these index data of 2000 -2013. I use principal component analysis method to merge the six of these factors that have the possibility of coincidence. And then analyze with the method of descriptive statistics analysis on the remaining 15 factors that may influence digital marketing’s scale, which shows the trends of these indexes from 2000 to 2013. Then, I remove 3 indexes by using Pearson correlation analysis. Then, this paper focuses on the research on the effect factors of digital marketing market scale, doing regression analysis for the remaining 12 variables, but I found that the effect is not good. So I combine the stepwise regression method with the principal component analysis method to select the optimal regression equation. The factors that influence development of the digital marketing can be pided into two categories, one is consumer participation external factors, the other is digital marketing platform of internal factors. Finally, I predict the enterprise digital marketing market scale with the time series method, which can be expected to generally return digital marketing brings and give enterprises some useful message.
[Key Words]：digital marketing, regression analysis, stepwise regression, principal component analysis, ARIMA model
目 录
摘 要 ……………I
Abstract II
1. 绪论 1
1.1 研究背景 ...1
1.2 国内外研究状况 1
1.3 主要研究工作 2
2. 数字营销 2
2.1 数字营销概述 2
2.2 数字营销近年来的发展状况 2
3.数据处理 3
3.1 数据选择——初选因子 3
3.2 数据合并 4
3.2.1 主成分分析的概述 4
3.2.2 基于主成分分析方法合并各渠道用户规模变量 5
3.3 基本统计特征 5
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