现状偏差
现状
后悔
价值(数学)
心理学
社会心理学
抗性(生态学)
对偶(语法数字)
计算机科学
技术接受模型
政治学
可用性
统计
哲学
数学
人机交互
法学
生物
语言学
生态学
作者
Janarthanan Balakrishnan,Yogesh K. Dwivedi,Laurie Hughes,Frederic Boy
标识
DOI:10.1007/s10796-021-10203-y
摘要
Abstract This study investigates the factors that build resistance and attitude towards AI voice assistants (AIVA). A theoretical model is proposed using the dual-factor framework by integrating status quo bias factors (sunk cost, regret avoidance, inertia, perceived value, switching costs, and perceived threat) and Technology Acceptance Model (TAM; perceived ease of use and perceived usefulness) variables. The study model investigates the relationship between the status quo factors and resistance towards adoption of AIVA, and the relationship between TAM factors and attitudes towards AIVA. A sample of four hundred and twenty was analysed using structural equation modeling to investigate the proposed hypotheses. The results indicate an insignificant relationship between inertia and resistance to AIVA. Perceived value was found to have a negative but significant relationship with resistance to AIVA. Further, the study also found that inertia significantly differs across gender (male/female) and age groupings. The study's framework and results are posited as adding value to the extant literature and practice, directly related to status quo bias theory, dual-factor model and TAM.
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