Trust in the chatbot: a semi-human relationship

Moez Ltifi ()
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Moez Ltifi: Shaqra University

Future Business Journal, 2023, vol. 9, issue 1, 1-12

Abstract: Abstract Today, the use of chatbots for different functions in various industries has become a very interesting business for companies. Chatbots are promising types of interfaces. It is therefore necessary to understand how customers interact with retailers' interfaces in order to provide them with a better experience. In this study, we mobilise two theories, such as Stimilus-Organism-Response and Social Presence Theory, to formulate our research hypotheses. We have made major contributions to the interactive marketing and artificial intelligence literature by focusing on an emerging interactive technology: text chatbots. Our aim is to test the hedonic attributes of consumer trust in text chatbots by integrating the social and emotional aspects of this interaction. We also want to look at the moderating effects of text chatbot disclosure and task complexity. Based on the responses, we ran a questionnaire survey. A total of 353 people were polled for data. Participants were chosen at random. The structural equation modelling technique was used. First, the findings revealed that empathy and friendliness are major hedonic predictors of consumers' confidence in text chatbots. Second, the results demonstrate that the chatbot's task complexity and disclosure partially affect the empathy-trust relationship and the usability-trust relationship. We have made significant contributions to the field of interactive marketing research and artificial intelligence by focusing on new interactive technologies such as text-based chatbots. Our study is one of the first to look at the hedonic determinants of customer belief in text-based chatbots (1). All previous research has concentrated on the practical application of chatbots for digital customer service. The moderating effects of human-chatbot contact are investigated in our study (2). These two contributions make our research original. The findings give additional information that e-service providers and chatbot developers may utilise to improve their services, understand their effects on user experience, and provide a guide for strategy development and relationship building.

Keywords: Artificial intelligence; Chatbot empathy and usability; e-trust; Moderating effects; Experience; Structural equation method (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1186/s43093-023-00288-z

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