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  4. The Anatomy of User Experience with Conversational Agents: A Taxonomy and Propositions of Service Clues
 
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The Anatomy of User Experience with Conversational Agents: A Taxonomy and Propositions of Service Clues

Journal
International Conference on Information Systems (ICIS)
Type
conference paper
Date Issued
2020
Author(s)
Zierau, Naim  
Wambsganss, Thiemo  
Janson, Andreas  
Schöbel, Sofia
Leimeister, Jan Marco  orcid-logo
Research Team
IWI6
Abstract
Conversational agents (CAs) represent a paradigm shift in regards to how humans use information systems. Although CAs have recently attracted considerable research interest, there is still limited shared knowledge about the distinctive characteristics of CAs from a user experience-based perspective. To address this gap, we conducted a systematic literature review to identify CA characteristics from existing research. Building on classifications from service experience theory, we develop a taxonomy that classifies CA characteristics into three major categories (i.e. functional, mechanic, humanic clues). Subsequently, we evaluate the usefulness of the taxonomy by interviewing six domain experts. Based on this categorization and the reviewed literature, we derive three propositions that link these categories to specific user experience dimensions. Our results support researchers and practitioners by providing deeper insights into service design with CAs and support them in systematizing and synthesizing research on the effects of specific CA characteristics from a user experience-based perspective.
Language
English
Keywords
Conversational Agent
Service Clues
Taxonomy
User Experience
HSG Classification
contribution to scientific community
Event Title
International Conference on Information Systems (ICIS)
Event Location
Hyderabad, India
Event Date
13.12.2020-16.12.2020
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/113193
Subject(s)

information managemen...

Division(s)

IWI - Institute of In...

Eprints ID
261080
File(s)
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Thumbnail Image

open.access

Name

JML_785.pdf

Size

729.45 KB

Format

Adobe PDF

Checksum (MD5)

30944affe9d65eafaa2234cdc6cb915e

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