Consumer's acceptance of retail service robots: mediating role of pleasure and arousal

Alam, S., Abdullah, S. ORCID: 0000-0001-7249-8512, Kokash, H., Ahmed, S. and Omar, N., 2024. Consumer's acceptance of retail service robots: mediating role of pleasure and arousal. Journal of Decision Systems. ISSN 1246-0125

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Abstract

Service robots, driven by cutting-edge technologies have the potential to revolutionize service delivery and enhance customer experiences leading to service innovation, particularly in the retail sector. The acceptance of retail service robots is a topic of increasing interest, yet there are contradicting influencers of consumers' intention towards these robots. Specifically, the mediating role of pleasure and arousal in the relationship between consumers' perceptions of retail service robots and their behavior intention is not adequately explored. Therefore, this study aims to investigate the mediating role of pleasure and arousal in the relationship between consumers' perceptions of retail service robots and their usage intention in retail settings. Quantitative data was collected from 323 participants using online snowball sampling method and analysed using PLS-SEM technique. Results indicated that subjective norms, technological self-efficacy, habit and attitude had a strong influence on behavior intention. While the emotional domain of pleasure played a more significant mediating role compared to arousal. Overall, the integration of Theory of Reasoned Action (TRA), self-efficacy theory, and the pleasure, arousal and dominance (PAD) model allows for the advancement of theoretical framework and deeper understanding in the field of human-robot interaction. These findings also provide practical insights for businesses to understand the influence of consumer emotions and utilize this knowledge to design marketing strategies, service encounters, and experiences that enhance their usage of service robots.

Item Type:	Journal article
Publication Title:	Journal of Decision Systems
Creators:	Alam, S., Abdullah, S., Kokash, H., Ahmed, S. and Omar, N.
Publisher:	Taylor & Francis
Date:	15 February 2024
ISSN:	1246-0125
Identifiers:	Number Type 10.1080/12460125.2024.2318527 DOI 1864429 Other
Rights:	This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Decision Systems on 15/02/2024, available at: https://doi.org/10.1080/12460125.2024.2318527
Divisions:	Schools > Nottingham Business School
Record created by:	Laura Ward
Date Added:	22 Feb 2024 09:10
Last Modified:	22 Feb 2024 09:10
URI:	https://irep.ntu.ac.uk/id/eprint/50910

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