Designing for Social Presence and Leveraging the Outcomes of Customer Service Chatbots
Journal
Academy of Management Annual Meeting (AOM)
Type
conference paper
Date Issued
2019
Author(s)
Research Team
IWI6
Abstract
Chatbots are innovative text-based dialogue systems that are oftentimes used in digital customer service encounters, since chatbots offer a lot of potential to optimize the relationship with the customer. However, chatbots face various problems, such as low adoption and satisfaction rates as well as other negative reactions from the customer. Companies therefore need to consider different design features when developing their chatbots. Key for designing chatbots is the use of anthropomorphic design elements. In this study, we examine the two anthropomorphic design elements of personification, which includes a human like appearance of the chatbot, and socially oriented communication, which means a more sensitive and extensive communication behavior. We tested the influence of the two design elements on social presence, satisfaction, trusting beliefs and empathy. The results of our experiment support a significant influence of the two anthropomorphic design elements on social presence. In addition, our findings show the central role of social presence concerning chatbot perceptions. First, social presence has a strong direct influence on trusting beliefs, empathy and satisfaction. Second, social presence acts as a mediator for both anthropomorphic design elements on satisfaction with a chatbot. The derived implications provide a theory for understanding anthropomorphic design elements related to chatbots and we offer design principles for practitioners that enable more effective chatbot implementations.
Language
English
Keywords
Anthropomorphic Design
Chatbots
Conversational Agents
Social Presence
Trust
HSG Classification
contribution to scientific community
Number
79
Event Title
Academy of Management Annual Meeting (AOM)
Event Location
Boston, Massachusetts, USA
Event Date
09.08.2019-13.08.2019
Subject(s)
Division(s)
Eprints ID
256963
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Name
JML_737.pdf
Size
20.05 KB
Format
Adobe PDF
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