Human Computer / Robot Interaction
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Paper Number
1752
Paper Type
short
Description
Owing to the rapid development of artificial intelligence, especially, natural language processing, service chatbot has been pervasively applied in online service. However, it remains to be a challenge for online retailers to attract and convert consumers with service chatbots. Various design artifacts have been studied to promote service chatbot effectiveness, among which anthropomorphism is considered one of the most influential factors. This study draws upon interpersonal attraction theory to reveal how human-machine communication traits influence consumer unplanned purchase decisions (i.e., urge to purchase and actual purchase behavior). Specifically, we examine the rule of attractions between chatbots with specific personalities and consumers with different communication styles. A mixed-method approach was adopted to examine the research model. The results will advance our understanding of human-machine communication and provide practical insights into the design of chatbots in online service.
Recommended Citation
Tan, Ran; Li, Yang; and Huang, Qian, "Enhancing Service Chatbot Effectiveness: The Effect of Dyadic Communication Traits on Consumer Unplanned Purchase" (2021). ICIS 2021 Proceedings. 9.
https://aisel.aisnet.org/icis2021/hci_robot/hci_robot/9
Enhancing Service Chatbot Effectiveness: The Effect of Dyadic Communication Traits on Consumer Unplanned Purchase
Owing to the rapid development of artificial intelligence, especially, natural language processing, service chatbot has been pervasively applied in online service. However, it remains to be a challenge for online retailers to attract and convert consumers with service chatbots. Various design artifacts have been studied to promote service chatbot effectiveness, among which anthropomorphism is considered one of the most influential factors. This study draws upon interpersonal attraction theory to reveal how human-machine communication traits influence consumer unplanned purchase decisions (i.e., urge to purchase and actual purchase behavior). Specifically, we examine the rule of attractions between chatbots with specific personalities and consumers with different communication styles. A mixed-method approach was adopted to examine the research model. The results will advance our understanding of human-machine communication and provide practical insights into the design of chatbots in online service.
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