Consumers acceptance of artificially intelligent (AI) device use in service delivery

被引:713
作者
Gursoy, Dogan [1 ,2 ]
Chi, Oscar Hengxuan [1 ]
Lu, Lu [3 ]
Nunkoo, Robin [2 ,4 ,5 ]
机构
[1] Washington State Univ, Sch Hospitality Business Management, Carson Coll Business, Pullman, WA 99164 USA
[2] Univ Johannesburg, Sch Tourism & Hospitality, Johannesburg, South Africa
[3] Temple Univ, Dept Tourism & Hospitality Management, 1810 North 13th St,Speakman Hall 308, Philadelphia, PA 19122 USA
[4] Univ Mauritius, Dept Management, Reduit, Mauritius
[5] Griffith Univ, Griffith Inst Tourism, Gold Coast, Qld, Australia
关键词
Artificial intelligence; AI devices; Technology; Intention; Adoption; Services; TECHNOLOGY ACCEPTANCE; SOCIAL-INFLUENCE; INFORMATION-TECHNOLOGY; BEHAVIORAL INTENTIONS; DECISION-MAKING; UNIFIED THEORY; ADOPTION; MODEL; MOTIVATION; IMPACT;
D O I
10.1016/j.ijinfomgt.2019.03.008
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
This study develops and empirically tests a theoretical model of artificially intelligent (AI) device use acceptance (AIDUA) that aims to explain customers' willingness to accept AI device use in service encounters. The proposed model incorporates three acceptance generation stages (primary appraisal, secondary appraisal, and outcome stage) and six antecedents (social influence, hedonic motivation, anthropomorphism, performance expectancy, effort expectancy, and emotion). Utilizing data collected from potential customers, the proposed AIDUA model is tested. Findings suggest that customers go through a three-step acceptance generation process in determining whether to accept the use of AI devices during their service interactions. Findings indicate that social influence and hedonic motivation are positively related to performance expectancy while anthropomorphism is positively related to effort expectancy. Both performance and effort expectancy are significant antecedents of customer emotions, which determines customers' acceptance of AI device use in service encounters. This study provides a conceptual AI device acceptance framework that can be used by other researchers to better investigate AI related topics in the service context.
引用
收藏
页码:157 / 169
页数:13
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