亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Measuring the influence of mere exposure effect of TV commercial adverts on purchase behavior based on machine learning prediction models

学习效果 计算机科学 人工智能 机器学习 经济 微观经济学
作者
Elisa Claire Alemán Carreón,Hirofumi Nonaka,Asahi Hentona,Hirochika Yamashiro
出处
期刊:Information Processing and Management [Elsevier]
卷期号:56 (4): 1339-1355 被引量:22
标识
DOI:10.1016/j.ipm.2019.03.007
摘要

Since its introduction, television has been the main channel of investment for advertisements in order to influence customers purchase behavior. Many have attributed the mere exposure effect as the source of influence in purchase intention and purchase decision; however, most of the studies of television advertisement effects are not only outdated, but their sample size is questionable and their environments do not reflect reality. With the advent of the internet, social media and new information technologies, many recent studies focus on the effects of online advertisement, meanwhile the investment in television advertisement still has not declined. In response to this, we applied machine learning algorithms SVM and XGBoost, as well as Logistic Regression, to construct a number of prediction models based on at-home advertisement exposure time and demographic data, examining the predictability of Actual Purchase and Purchase Intention behaviors of 3000 customers across 36 different products during the span of 3 months. If we were able to predict purchase behaviors with models based on exposure time more reliably than with models based on demographic data, the obvious strategy for businesses would be to increase the number of adverts. On the other hand, if models based on exposure time had unreliable predictability in contrast to models based on demographic data, doubts would surface about the effectiveness of the hard investment in television advertising. Based on our results, we found that models based on advert exposure time were consistently low in their predictability in comparison with models based on demographic data only, and with models based on both demographic data and exposure time data. We also found that there was not a statistically significant difference between these last two kinds of models. This suggests that advert exposure time has little to no effect in the short-term in increasing positive actual purchase behavior.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
4秒前
305发布了新的文献求助10
4秒前
懒惰扼杀激情完成签到 ,获得积分10
5秒前
包容明辉完成签到 ,获得积分10
6秒前
Niniiii发布了新的文献求助10
8秒前
sauncaiyu发布了新的文献求助30
11秒前
12秒前
Panacea完成签到 ,获得积分10
14秒前
pinecone发布了新的文献求助10
17秒前
CodeCraft应助安年采纳,获得10
21秒前
Lin.隽发布了新的文献求助40
23秒前
27秒前
305完成签到,获得积分10
29秒前
科研通AI6.2应助pinecone采纳,获得10
31秒前
金林彤发布了新的文献求助10
33秒前
Lin.隽完成签到,获得积分10
34秒前
38秒前
qianyixingchen完成签到 ,获得积分10
45秒前
方文发布了新的文献求助10
45秒前
misa完成签到 ,获得积分10
56秒前
舟舟完成签到 ,获得积分10
58秒前
赘婿应助wqwweqwe采纳,获得10
1分钟前
1分钟前
池雨完成签到 ,获得积分10
1分钟前
楚明允完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
沉潜完成签到,获得积分10
1分钟前
碳酸芙兰完成签到,获得积分10
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
wab完成签到,获得积分0
1分钟前
今后应助金林彤采纳,获得10
1分钟前
痞老板死磕蟹黄堡完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
1分钟前
共享精神应助科研通管家采纳,获得10
1分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 化学工程 生物化学 物理 计算机科学 内科学 复合材料 催化作用 物理化学 光电子学 电极 冶金 细胞生物学 基因
热门帖子
关注 科研通微信公众号,转发送积分 6020845
求助须知:如何正确求助?哪些是违规求助? 7623082
关于积分的说明 16165681
捐赠科研通 5168555
什么是DOI,文献DOI怎么找? 2766100
邀请新用户注册赠送积分活动 1748479
关于科研通互助平台的介绍 1636086