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The continuation and recommendation intention of artificial intelligence-based voice assistant systems (AIVAS): the influence of personal traits
Internet Research ( IF 5.9 ) Pub Date : 2021-05-20 , DOI: 10.1108/intr-06-2020-0327
Kyung Young Lee , Lorn Sheehan , Kiljae Lee , Younghoon Chang

Purpose

Based on the post-acceptance model of information system continuance (PAMISC), this study investigates the influence of the early-stage users' personal traits (specifically personal innovativeness and technology anxiety) and ex-post instrumentality perceptions (specifically price value, hedonic motivation, compatibility and perceived security) on social diffusion of smart technologies measured by the intention to recommend artificial intelligence-based voice assistant systems (AIVAS) to others.

Design/methodology/approach

Survey data from 400 US AIVAS users were collected and analyzed with Statistical Product and Service Solutions (SPSS) 18.0 and the partial least square technique using advanced analysis of composites (ADANCO) 2.1.

Findings

AIVAS technology is presently at the early stage of market penetration (about 25% of market penetration in the USA). A survey of AIVAS technology users reveals that personal innovativeness is directly and indirectly (through confirmation and continuance) associated with a stronger intention to recommend the use of the device to others. Confirmation is associated with all four ex-post instrumentality perceptions (hedonic motivation, compatibility, price value and perceived security). Among the four, however, only hedonic motivation and compatibility are significant predictors of satisfaction, which lead to use continuance and, eventually, intention to recommend. Finally, technology anxiety is found to be indirectly (but not directly) associated with a lower intention to recommend.

Originality/value

This is the first study conducted on the early-stage AIVAS users that evaluates the influence of both personal traits and ex-post instrumentality perceptions on users' intention for continuance and recommendation to others.



中文翻译:

基于人工智能的语音助手系统(AIVAS)的延续和推荐意图:个人特质的影响

目的

本研究基于信息系统持续接受后模型(PAMISC),研究了早期用户的个人特征(特别是个人创新和技术焦虑)和事后工具感知(特别是价格价值、享乐动机)的影响。 ,兼容性和感知安全性)对智能技术的社会传播的影响,通过向他人推荐基于人工智能的语音助手系统(AIVAS)的意图来衡量。

设计/方法/方法

使用统计产品和服务解决方案 (SPSS) 18.0 和使用复合材料高级分析 (ADANCO) 2.1 的偏最小二乘技术收集和分析了来自 400 个美国 AIVAS 用户的调查数据。

发现

AIVAS 技术目前处于市场渗透的早期阶段(约占美国市场渗透率的 25%)。一项对 AIVAS 技术用户的调查显示,个人创新与向他人推荐使用该设备的强烈意愿直接和间接(通过确认和持续)相关。确认与所有四种事后工具感知(享乐动机、兼容性、价格价值和感知安全性)相关。然而,在这四者中,只有享乐动机和兼容性是满意度的重要预测因素,这导致使用持续性,并最终产生推荐意图。最后,发现技术焦虑与较低的推荐意愿间接(但不是直接)相关。

原创性/价值

这是对早期 AIVAS 用户进行的第一项研究,该研究评估了个人特征和事后工具感知对用户继续使用和向他人推荐的意图的影响。

更新日期:2021-05-20
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