The Impact of Human–Chatbot Interaction on Human–Human Interaction: A Substitution or Complementary Effect

Abstract

Chatbots have been used in various contexts, enabling users to continually increase their trust in human-chatbot interaction (HCI). However, salient theoretical research and risk supervision remain insufficient. It is thus unclear whether HCI generates a substitution effect that threatens human–human interaction (HHI) or a complementary effect that facilitates HHI. Grounded in interdependence theory and trust transfer theory, this study proposes a theoretical model that explains how users’ established trust in HCI can affect their interpersonal communication intention. This theoretical model has been tested in both the task context and the social context. The results show that the effect of HCI on HHI varies in different contexts. In the task context, users prefer to interact only with the better service provider. There is thus a substitution effect of HCI on HHI. Users’ established trust in HCI makes them perceive that chatbot service providers offer more value than human service providers, thereby reducing their intention to interact with the latter. In the social context, users are open to interacting with multiple social partners instead of only the better partner. Hence, HCI has a complementary effect on HHI. Users’ established trust in HCI can also be extended to category-based trust in interaction with other unfamiliar social partners (unfamiliar people), thereby enhancing their intention to interact with unfamiliar people. Accordingly, these findings can enable the formulation of more targeted measures that mitigate the potential risks of HCI for HHI and promote future human-human relationships.

Keywords:

• Human–chatbot interaction
• human–human interaction
• interdependence theory
• trust transfer theory

Disclosure statement

No potential conflicts of interest were reported by the author(s).

Additional information

Funding

This research was supported by the National Social Science Fund of China (No. 20BJY131).

Notes on contributors

Hui Xia

Hui Xia is a professor at the Business School, Shandong University, China. She was a postdoctoral fellow at Fudan University. Her research interests include robotic technology, virtual reality, and artificial intelligence marketing. Her work has been published in Industrial Marketing Management.

Junjie Chen

Junjie Chen is a postgraduate student at the Business School, Shandong University, China. His research interests include the area of psychology, human–robot interaction, and artificial intelligence. He has rich experience in structural equation modeling and experimental surveys.

Yuying Qiu

Yuying Qiu received a Master’s degree from Shandong University, China. She is currently a lecturer at Yantai Vocational College. Her research interests include artificial intelligence marketing and human-computer interaction.

Pei Liu

Pei Liu is an associate professor at the Business School, Shandong University, China. He was a postdoctoral fellow at Tsinghua University. His research interests include advanced technology adoption and system dynamics. He has published more than 20 papers in various journals.

Zhangxin Liu

Zhangxin Liu is a lecturer and researcher at the UWA Business School, University of Western Australia, Australia. He received PhD from the University of Queensland. His research interests include blockchain and intelligent technologies.