User Satisfaction with an AI-Enabled Customer Relationship Management Chatbot

被引：3
|
作者：
Sohail, Maarif [1 ]
Mohsin, Zehra [2 ]
Khaliq, Sehar [3 ]
机构：
[1] McMaster Univ, DeGroote Sch Business, Hamilton, ON, Canada
[2] Lahore Coll Women Univ, Lahore, Pakistan
[3] Fdn Univ Islamabad, Islamabad, Pakistan
来源：
HCI INTERNATIONAL 2021 - LATE BREAKING POSTERS, HCII 2021, PT I | 2021年 / 1498卷
关键词：
Artificial Intelligence (AI); Customer Relationship Management (CRM); Electronic Commerce (E-Commerce); Expectation Confirmation Theory (ECT); Uncertainty Reduction Theory (URT); SELF-SERVICE TECHNOLOGY; MODEL; INFORMATION; ADOPTION; CONSEQUENCES; ANTECEDENTS; ACCEPTANCE; COMMERCE; QUALITY; TRUST;
D O I：
10.1007/978-3-030-90176-9_36
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Chatbots' ability to carry out focused, result-oriented online conversations with human end-users impacts user experience and user satisfaction. Using "Chatbots" as key identifiable examples utilized by Electronic Commerce (E-Commerce) firms in Customer Relationship Management (CRM), this study offers a user satisfaction model in the context of Artificial Intelligence (AI) enabled CRM in E-Commerce. The model is based on Expectation Confirmation Theory (ECT) and Uncertainty Reduction Theory (URT) within the Chatbot context. This model will allow us to investigate if chatbots can provide both businesses and consumers the opportunity to complete a journey from normal through abnormal to the new normal in situations similar to a covid pandemic.
引用
收藏
页码：279 / 287
页数：9
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