首先,本文对国内外个性化广告的相关文献进行回顾,并对其研
宄现状进行分析和总结。在此基础上,引入了用户感知个性化、感知
相关性和用户对APP的满意度3个变量,构建了有调节的中介效应
模型。其次,采用问卷调查问卷的方式收集研宄数据,并利用SPSS23.0
和AMOS20.0对本研宄所涉及的问卷进行信度分析和验证性因素分
析,在此基础上,进行了描述性分析、中介效应分析和调节效应的分
析。并得出以下主要结论:(1)感知相关性正向作用于用户的广告品
牌态度和广告点击意愿^2)感知个性化对用户的广告品牌态度/点击
意愿有正向影响,且是通过感知相关性的中介效应起作用的,(3)信
息流广告效果受到调节因素的影响,用户的APP满意度显著调节感
知个性化与广告品牌态度之间的关系;(4)感知个性化、感知相关性、
用户对APP的满意度和品牌态度/点击意愿之间构成有调节的中介效 应模型
最后,基于假设检验和模型验证的结果,分别对信息流广告投放
平台和广告主提出了相关建议。对广告投放平台而言,应注重信息流
广告投放的相关性,充分利用用户画像和用户行为等大数据信息,了
解用户的偏好获取用户的兴趣,并为其匹配相关度高的广告。与此同
时,也要注重提升客户端用户体验与口碑,尽可能地在用户体验与商
业化之间寻求共赢。对广告主而言,应丰富广告物料样式,在达到广
告投放目的的同时也要降低广告对用户的打扰,尽可能实现广告与信
息流卡片的原生效应
关键词:信息流广告、有调节的中介效应模型、感知个性化 HOW DO USERS VIEW PERSONALIZED ADS
—A MODERATED MEDIATION MODEL
ABSTRACT
In mobile Internet era, reading the information flow has become the
mainstream way to consumption their fragmentation time. By using user
portraits and their behavior log through artificial intelligence and big data
technology, the mass of information content is delivered to each user.
Benefit form the rapid growth of mobile Internet advertising, streaming
Ads with its high exposure traffic and user label system has become
advertisers competing home. Tencent company has achieved 7.499 billion
RMB of advertising revenue through streaming Ads. And, Byte Beat is
expected to generate revenue of 6 billion RMB in revenue this year.
Because of its strong liquidity, Internet advertising platform and advertisers
are full in love with streaming Ads. However, the research of streaming
Ads is mainly in technical implementation level, few of paper study about
how user view streaming Ads, and how its affect the user’s advertising
behavior
First of all, this paper reviews the literature on the personalized
advertising, and analyzes the research status of personalized advertising.
And then, we introduce three variables, namely, user perceived
personalization, perceived relevance and user satisfaction with APP, and
constructed a moderated mediation model. Second, we analyzed the data
of questionnaire survey by using SPSS23 and AMOS20. The analysis
included reliability analysis and validity analysis, and the most important,
we analyzed the mediating effect and the moderating effect of this paper,
and draws the following main conclusions^l)Perceived relevance has a
positive effect on the effectiveness of streaming Ads;(2)Perceived
relevance plays a mediating role in the user’s perception of streaming Ads
and the attitude of the advertising brand/willingness to click on the
ads.(3)The effect of streaming Ads is affected by the adjustment factors. The user’s satisfaction with APP is regulated by the relationship between
perceived personalization and advertising brand attitude. (4)The
moderated mediation model is based with perceived personalization、
perceived relevance and the attitude of the advertising brand/willingness
to click on the ads.
At last, based on hypothesis testing and model validation results,
respectively, making recommendations for platform and advertisers. For
the platform, they should increase the relevance of ads which is based on
the user’s basic information and operation log. At the same time, the
platform should focus on the user experience and enhance product
reputation, .to seek a win-win situation between the user experience and
business purposes. For the advertisers, they should rich ad styles and create
native ads for our users.
KEY WORDS: streaming ads, the moderated mediation model,perceived
personalization 目录
第一章绪论 1
1.1研宄背景 1
1.2研宄目的与意义1,2.1研宄目的 3
1.2.2研宄意义 4
1.3研宄方法和技术路线1.3.1研宄方法 4
1.3_2研究的技术路线1.4研究框架 6
第二章理论基础与文献综述2.1相关理论 8
2.1.1有调节的中介效应模型2.1.2涉入理论2.1.3精细加工可能性模型理论(ELM)2.2国内外研宄综述2.2.1感知个性化2.2.2感知相关性2.2.3用户APP满意度第三章研究设计3.1研究模型的构建3.2研究假设 17
3.2.1感知相关性的中介作用3.2.2用户APP满意度的调节作用3.3变量操作化定义3.3.1感知个性化3.3.23.3.3品牌态度
21
3.3.4点击意愿
22
3_3.5用户APP满意度
22
3.4问卷设计 23
第四章实证研究
25
4.1数据收集及样本特征
25
4.1.1数据收集
25 4.1.2样本特征
25
4.2信度与效度分析
26
4.2.1探索性因子分析
26
4.2.2信度分析
27
4.2.3效度分析
28
4_3结构方程建模分析
30
4.3.1模型的整体拟合度分析
30
4.3.2中介效应分析
31
4.3.3调节效应分析
33
第五章分析与讨论
36
5..1假设验证结果
36
5.2感知相关性的中介效应分析
36
5.3用户APP满意度的调节效应分析
38
5.4本章小结 39
第六章结论与展望
40
6.1主要结论 40
6.2营销建议 41
6.2.1广告投放平台
41
6.2.2广告主 42
6.3可能的创新点
43
6.4研究局限与展望
44
45
m M 51
致 m 54
攻读硕士期间发表的学术论文目录
55
第…帘绪论
第一章绪论
1.1研究背景
随着互联网的高速发展,每个人都处于一个信息爆炸的时代,海量的资讯内
容充斥在各类网站和手机软件中,如何让用户获取到自己感兴趣的资讯内容己经
成为各大互联网公司争相投入资源的重要领域。在国外,诸如Twitter、News
Master和News Republic等资讯类APP如雨后春劈1般快速纟屈起,并迅速占据了
移动端个性化阅读市场。在国内,个性化阅读市场也正竞争的如火如荼,不管是
作为新闻类应用市场领军人物的腾讯新闻和今日头条还是作为后起之秀的一点
资讯、UC头条和天天快报等资讯类个性化阅读APP都己经取得了巨大的成功,
并占据了相当大一部分的信息流资讯类应用市场份额。作为上述互联网企业主要
盈利模式的信息流广告也因此备受重视
刚刚过去的一年,中国广告市场出现了一个关键的转折点,移动广告支出第
一次超过桌面广告。eMarketer在最新的关于中国移动广告增速的报告中揭示了
这一趋势。eMarketer预计,中国移动广告支出相比之前飙升一倍以上,在2015
年达到158.2亿美元,占中国全部媒体广告预算的22.3% —高于全球任何一个
市场
表1-1 2014-2019中国移动网络广告支出
年份
移动广告支出
电子广告占比 综合广告占比
mobile internet ad
% of digital ad % of total ad
Year
spending (billions)
spending
spending
2014
￥7.36
30. 8%
11.7%
2015
￥15.82
51.0%
22.3%
2016
￥24.99
62.9%
30.9%
2017
￥33.99
69.6%
37.4%
2018
￥43.33
75.2%
43.1%
2019
￥52.00
79. 8%
47. 8%
注:数据来源于www.eMarketr
受益于移动互联网广告的高速增长,移动信息流广告以其高曝光流量和完善
的用户标签体系成为了广告主争相投放的主场。腾讯公司凭借微信朋友圈、QQ
空间和腾讯新闻等产品的信息流广告,在2016年Q3实现了 74.49亿元的广告
收入,字节跳动公
==>>