首页|Researchers’ Work from Harbin Institute of Technology Focuses on Artificial Intelligence (Emotional Expression By Artificial Intelligence Chatbots To Improve Customer Satisfaction: Underlying Mechanism and Boundary Conditions)

Researchers’ Work from Harbin Institute of Technology Focuses on Artificial Intelligence (Emotional Expression By Artificial Intelligence Chatbots To Improve Customer Satisfaction: Underlying Mechanism and Boundary Conditions)

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Current study results on Artificial Intelligence have been published. According to news reporting originating in Heilongjiang, People’s Republic of China, by NewsRx journalists, research stated, “Artificial intelligence chatbots have invaded the tourism industry owing to their low cost and high efficiency. However, the influence of emotional expressions of chatbots on service outcomes has not received much attention from researchers.” Funders for this research include National Natural Science Foundation of China (NSFC), Fundamental Research Funds for the Central Universities in UIBE, Fundamental Research Funds in DUT, Natural Science Foundation of Heilongjiang Province, Fundamental Research Funds for the Central Universities. The news reporters obtained a quote from the research from the Harbin Institute of Technology, “Drawing upon expectancy violations theory, we explored how emotional expressions of chatbots affect customer satisfaction using three experiments in the context of tourist attraction recommendations. Chatbots’ expressions of concern for customers can improve customer satisfaction by reducing expectancy violations. In particular, customer’s goal orientation, the human-likeness of chatbot’s avatars, and the relationship type between customers and chatbots can moderate the negative relationship between emotional expression and expectancy violation.”

HeilongjiangPeople’s Republic of ChinaAsiaArtificial IntelligenceEmerging TechnologiesMachine LearningTourismTravelHarbin Institute of Technology

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.1)
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