Ready for Take-off?–Gestaltung und Wahrnehmung von Reiseimpfberatungschatbots
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
The rise of digital speech-based assistants (e.g., Amazon’s Alexa, Apple’s Siri, or Hellofresh’s chatbot) gained increased popularity and has also found its way into healthcare. A current example is WHO’s WhatsApp chatbot that informs users about COVID-19. Such assistants can educate patients, independent of location and time, which is an incredible benefit for patients. However, in addition to existing technical challenges (including the development and optimization of speech recognition algorithms), there are also challenges in human-chatbot-interactions. This study investigates the role of a human-like design (including human name, greeting, and human avatar) of a travel vaccination advice chatbot on the perception of its users. Specifically, we aim to understand whether and how anthropomorphism (the perception of humanness and social presence in objects, animals, and machines) affects perceived trustworthiness and ultimately service satisfaction. In an online experiment with 78 participants, two chatbot designs (with human-like design elements vs. without these elements) were compared. The results show that perceived social presence significantly increases perceived trustworthiness and service satisfaction. Thus, we recommend that practitioners implement a human-like design travel vaccination counseling and similar counseling processes via chatbots.
| Translated title of the contribution | Ready for Take-off?—Design and Perception of Chatbots for Travel Vaccination Counseling |
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Details
| Original language | German |
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| Pages (from-to) | 1626-1639 |
| Number of pages | 14 |
| Journal | HMD Praxis der Wirtschaftsinformatik |
| Volume | 59 |
| Issue number | 6 |
| Early online date | 2 Nov 2022 |
| Publication status | Published - Dec 2022 |
| Peer-reviewed | Yes |
External IDs
| ORCID | /0000-0001-5389-427X/work/160478603 |
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| Mendeley | 84b93445-c525-3038-8ad4-3b53c1e7d344 |
| PubMed | 40477988 |