TY - GEN
T1 - Key Factors Influencing the Degree of Acceptance of an Intelligent Customer Service System - A Literature Review
AU - Jia, Yunhuan
AU - Chen, Zhe
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - In the context of artificial intelligence offensive markets, intelligent customer service robots have joined the traditional customer service system. Although intelligent customer service is widely used in e-commerce, finance, education and the phenomenon of rejecting intelligent customer service services often turned directly to manual. This article searches and investigates the current intelligent customer service market through a large number of literature. The purpose is to explore the key factors that affect the success of intelligent customer service, and propose the intelligent customer service system that can be more accepted by the public. The work done in the article is to use the existing Systematic Satisfaction Evaluation Model and TAM to explore the key factors affecting the acceptance of the intelligent customer service system. From the analysis of the three elements of tasks, intelligent customer service robots, and users five indicators of Flexibility, Integration, Accessibility, and Timelits’ starting points to change the system’s perception and usefulness and perception to improve the user experience, and the user is willing to accept and trust intelligent customer service. Finally, make predictions on the customer service industry in the future: intelligent customer service and manual customer service coexist, division of labor cooperation, and complementary advantages, so that intelligent customer service can be used, creating intelligent and empathized customer service systems.
AB - In the context of artificial intelligence offensive markets, intelligent customer service robots have joined the traditional customer service system. Although intelligent customer service is widely used in e-commerce, finance, education and the phenomenon of rejecting intelligent customer service services often turned directly to manual. This article searches and investigates the current intelligent customer service market through a large number of literature. The purpose is to explore the key factors that affect the success of intelligent customer service, and propose the intelligent customer service system that can be more accepted by the public. The work done in the article is to use the existing Systematic Satisfaction Evaluation Model and TAM to explore the key factors affecting the acceptance of the intelligent customer service system. From the analysis of the three elements of tasks, intelligent customer service robots, and users five indicators of Flexibility, Integration, Accessibility, and Timelits’ starting points to change the system’s perception and usefulness and perception to improve the user experience, and the user is willing to accept and trust intelligent customer service. Finally, make predictions on the customer service industry in the future: intelligent customer service and manual customer service coexist, division of labor cooperation, and complementary advantages, so that intelligent customer service can be used, creating intelligent and empathized customer service systems.
KW - anthropomorphic
KW - human-computer interaction
KW - intelligent customer service
UR - https://www.scopus.com/pages/publications/85169465709
U2 - 10.1007/978-3-031-35939-2_28
DO - 10.1007/978-3-031-35939-2_28
M3 - 会议稿件
AN - SCOPUS:85169465709
SN - 9783031359385
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 386
EP - 396
BT - Cross-Cultural Design - 15th International Conference, CCD 2023, Held as Part of the 25th International Conference, HCII 2023, Proceedings
A2 - Patrick Rau, Pei-Luen
PB - Springer Science and Business Media Deutschland GmbH
T2 - 15th International Conference on Cross-Cultural Design, CCD 2023, held as part of the 25th International Conference on Human-Computer Interaction, HCII 2023
Y2 - 23 July 2023 through 28 July 2023
ER -