Ajou University repository

Is it the best for barista robots to serve like humans? A multidimensional anthropomorphism perspective
Citations

SCOPUS

36

Citation Export

Publication Year
2023-01-01
Publisher
Elsevier Ltd
Citation
International Journal of Hospitality Management, Vol.108
Keyword
AnthropomorphismAutonomyCaféService robotUncanny valleyVisual features
All Science Classification Codes (ASJC)
Tourism, Leisure and Hospitality ManagementStrategy and Management
Abstract
The COVID-19 pandemic has accelerated the use of contactless service robots in hospitality industries. However, the key drivers of consumer behaviors against service robots have been ill-understood. This study examines the interactive relationships between the physical (visual features) and psychological (service autonomy) dimensions of service-robot anthropomorphism and their impacts on consumer acceptance of service robots. Adopting an experimental vignette method (EVM) with 402 participants, the study reveals that the impacts of visual features on consumers’ intention are affected by the level of service robots’ autonomy; particularly, consumers showed the highest intention when the robots have medium visual features and high autonomy while their intention became lower for the same level of visual features with low autonomy. Interestingly, consumers showed the lowest intention with high level visual features, regardless of the levels of autonomy. Our results also show that human identity threats and consumer resistance play a significant counterproductive mechanism between service robot anthropomorphism and consumers’ intention.
ISSN
0278-4319
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/33009
DOI
https://doi.org/10.1016/j.ijhm.2022.103358
Fulltext

Type
Article
Funding
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea ( NRF-2021S1A5A2A01062441 ).
Show full item record

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Kang, Ju Young Image
Kang, Ju Young강주영
Department of Business Intelligence
Read More

Total Views & Downloads

File Download

  • There are no files associated with this item.