Artificial intelligence in social media: a catalyst for impulse buying behavior?

脉冲(物理) 广告 业务 社会化媒体 心理学 计算机科学 万维网 物理 量子力学
作者
Afiqah Amin
出处
期刊:Young Consumers: Insight and Ideas for Responsible Marketers [Emerald Publishing Limited]
卷期号:26 (5): 765-785 被引量:13
标识
DOI:10.1108/yc-10-2024-2297
摘要

Purpose This study aims to explore the largely under-researched area of user perceptions of artificial intelligence (AI)-driven recommendations and how the visibility of AI-driven labels influences impulsive buying behavior on social media platforms. Addressing a gap in existing literature, it further examines the moderating effects of generational differences and the mediating role of consumer knowledge, providing new insights into how these factors shape consumer responses to AI-driven content in social media. Design/methodology/approach This study used a quantitative approach, using consumer surveys to explore the direct and indirect impacts of AI-driven recommendations and the visibility of AI-driven labels on impulsive buying behavior through social media. A conditional process analysis was conducted to examine how generational differences act as a moderator and how consumer knowledge of AI serves as a mediator in these relationships. This analysis integrated these factors into a single framework to provide a detailed understanding of how consumers respond to AI-driven personalization in social media. Findings This study confirms that AI-driven personalization effectively nudges impulsive buying on social media, with personalized recommendations impacting behavior more subtly than AI labels. Consumer knowledge does not mediate this effect, while generational differences emerge as a significant moderator; Millennials are found to be more responsive to both recommendations and labels in comparison to Gen Z, possibly due to less familiarity with AI technologies present in social media. Research limitations/implications This study identifies limitations such as its reliance on consumer perceptions from a questionnaire rather than direct interactions with AI-driven features. While insightful, future research should incorporate actual user data, like clickstreams, and include a wider range of generational cohorts to deepen the understanding of AI’s impact on impulsive buying behavior. Originality/value This study bridges gaps in the literature by examining the combined effects of AI-driven recommendations and visibility of AI-driven labels on impulsive buying behavior, offering new insights into the role of generational differences and consumer knowledge in AI-based social media marketing.
最长约 10秒,即可获得该文献文件

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
Little5发布了新的文献求助10
刚刚
梵高晚风发布了新的文献求助10
1秒前
今夜白完成签到,获得积分10
1秒前
彭于晏的应助被彗星来了采纳,获得10
2秒前
Zzz完成签到,获得积分0
2秒前
2秒前
xr完成签到,获得积分10
2秒前
CZ完成签到,获得积分10
3秒前
Owen的应助被oooaaa采纳,获得10
3秒前
图假期小主完成签到 ,获得积分10
3秒前
dasfsdf的应助被郝丰富采纳,获得10
4秒前
范Fine发布了新的文献求助10
4秒前
Hq完成签到 ,获得积分10
4秒前
ddd发布了新的文献求助20
4秒前
花木兰完成签到,获得积分10
5秒前
cocaco的应助被fisher采纳,获得30
5秒前
英姑的应助被动听的襄采纳,获得10
5秒前
蓝胖子完成签到,获得积分10
5秒前
5秒前
SIMON发布了新的文献求助10
6秒前
6秒前
7秒前
7秒前
勤奋的烧鹅完成签到 ,获得积分10
7秒前
7秒前
Jay完成签到,获得积分10
7秒前
bkagyin的应助被小陈采纳,获得10
8秒前
菠萝吹雪发布了新的文献求助10
8秒前
遥雪完成签到,获得积分20
8秒前
小桓栀禾完成签到,获得积分10
8秒前
J-wwwww完成签到,获得积分10
9秒前
9秒前
cloud发布了新的文献求助10
9秒前
9秒前
10秒前
lucky完成签到,获得积分10
10秒前
1134117009发布了新的文献求助10
10秒前
丘比特的应助被SherlockJia采纳,获得10
10秒前
科研通AI6.4的应助被ddd采纳,获得20
10秒前
皇帝新衣发布了新的文献求助10
11秒前
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
Les Mantodea De Guyane 2000
Guidelines for fracture-safe and fatigue-reliable design of steel structures 600
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization 600
Organizational Behavior 510
Atelier, 2nd edition 500
Study of structural arctic steel in a friction pair with ice 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 7995086
求助须知:如何正确求助?哪些是违规求助? 9449873
关于积分的说明 21126883
捐赠科研通 7568391
什么是DOI,文献DOI怎么找? 3379556
关于科研通互助平台的介绍 2513187
邀请新用户注册赠送积分活动 2413402