Alexa, what's on my shopping list? Transforming customer experience with digital voice assistants

期望理论 连续性 感知 客户体验 心理学 社会影响力 计算机科学 知识管理 应用心理学 营销 社会心理学 业务 神经科学
作者
Eugene Cheng‐Xi Aw,Garry Wei‐Han Tan,Tat‐Huei Cham,Ramakrishnan Raman,Keng‐Boon Ooi
出处
期刊:Technological Forecasting and Social Change [Elsevier BV]
卷期号:180: 121711-121711 被引量:190
标识
DOI:10.1016/j.techfore.2022.121711
摘要

Artificial intelligence is disrupting the retail industry. Digital voice assistants as one of the most popular AI technologies are poised to revolutionize consumers’ shopping journeys yet we have a sparse understanding of their role in fostering customer experience. The present study seeks to address this issue by proposing and validating a research model encompassing human-like attributes (i.e., perceived anthropomorphism, perceived animacy, and perceived intelligence), technology attributes (i.e., performance expectancy, effort expectancy, and perceived security), and contextual factors (i.e., social influence and facilitating conditions) as the antecedents to continuance usage of digital voice assistants to shop. The effects are facilitated by the formation of several perceptual-based outcomes such as parasocial interactions, smart-shopping perception, and AI-enabled customer experience. Data (n = 411) was collected through an online questionnaire-based survey and analysed using Partial Least Squares Structural Equation Modelling. The results indicated (i) all human-like and technology attributes, except effort expectancy, have a significant impact on parasocial interactions, (ii) perceived intelligence, perceived security, and performance expectancy significantly influence smart-shopping perception, (iii) parasocial interactions and smart-shopping perception foster AI-enabled customer experience, and (iv) AI-enabled customer experience and social influence determine the continuance intention to shop using digital voice assistants. Theoretical and practical implications are discussed.
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
LI发布了新的文献求助10
1秒前
1秒前
1秒前
万能图书馆应助DZQ采纳,获得10
2秒前
科研通AI2S应助呆萌的蚂蚁采纳,获得10
2秒前
圆圆发布了新的文献求助10
3秒前
柿柿如意发布了新的文献求助10
3秒前
lvvln完成签到 ,获得积分10
3秒前
3秒前
4秒前
懿范完成签到 ,获得积分10
4秒前
隐形曼青应助zyyin采纳,获得10
4秒前
4秒前
日日唔冲梁先生完成签到,获得积分10
4秒前
5秒前
Chen发布了新的文献求助10
5秒前
6秒前
爆米花应助墙雨轩采纳,获得10
6秒前
6秒前
爱学习的向日葵完成签到,获得积分10
7秒前
7秒前
AidenTao完成签到 ,获得积分10
7秒前
木木发布了新的文献求助10
8秒前
8秒前
8秒前
8秒前
piggy完成签到,获得积分10
8秒前
8秒前
9秒前
9秒前
丘比特应助anon采纳,获得10
9秒前
李云晴发布了新的文献求助30
10秒前
10秒前
10秒前
慕青应助琪琪采纳,获得10
11秒前
羊羊羊发布了新的文献求助10
11秒前
11秒前
全力以赴先生完成签到,获得积分10
11秒前
Akim应助coward采纳,获得10
12秒前
汉堡包应助感动秋白采纳,获得10
12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
Römisch-Germanische Forschungen 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Green Fire Retardants for Polymeric Materials 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7615835
求助须知:如何正确求助?哪些是违规求助? 9191066
关于积分的说明 19694880
捐赠科研通 7188362
什么是DOI,文献DOI怎么找? 3271457
关于科研通互助平台的介绍 2434611
邀请新用户注册赠送积分活动 2266528