Who's Bad? - The Influence of Perceived Humanness on Users' Intention to Complain about Conversational Agent Errors to Others

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Abstract

The perception of humanness in a conversational agent (CA) has been shown to strongly impact users' processing and reaction to it. However, it is largely unclear how this perception of humanness influences users' processing of errors and subsequent intention for negative word-of-mouth (WoM). In this context, we propose two pathways between perceived humanness and negative WoM: a cognitive pathway and an affective pathway. In a 2x2 online experiment with chatbots, we manipulated both the occurrence of errors and the degree of humanlike design. Our findings indicate that perceived humanness effects users' intentions towards negative WoM through the cognitive pathway: users' confirmation of expectations is increased by perceived humanness, reducing negative WoM intentions. However, it has no effect on users' anger and frustration and does not interact with the effects of errors. For practice, our results indicate that adding humanlike design elements can be a means to reduce negative WoM.

Details

Original languageEnglish
Title of host publicationProceedings of the 44th International Conference on Information Systems (ICIS)
Number of pages17
Publication statusPublished - Dec 2023
Peer-reviewedYes

Conference

TitleInternational Conference on Information Systems 2023
SubtitleRising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies
Abbreviated titleICIS 2023
Conference number44
Duration10 - 13 December 2023
Website
Degree of recognitionInternational event
LocationHyderabad International Convention Center
CityHyderabad
CountryIndia

External IDs

ORCID /0000-0002-0842-4364/work/149082086
ORCID /0000-0002-0038-007X/work/150884813

Keywords