Chatbot usage at fast food restaurants in Ghana: Exploring the perception-attitude-behaviour nexus

As hospitality businesses including fast food restaurants continue to rebound after COVID-19, immersive technologies (e.g., chatbots) have become essential tools for the industry’s survival. Chatbots allow for accurate orders to be made at restaurants as well as enhancing seamless business transactions. Grounded on the Technology Acceptance Model 1 (perception-attitude-behaviour), this paper aims to investigate the attitude and use behaviour of chatbots at fast food restaurants among hospitality students. Set in the context of an emerging economy (Ghana) where the adoption of immersive technologies is still infant, this study employs a quantitative approach to offer valuable insights into chatbot usage in resource-limited settings. Results were analysed with Partial Least Squares-Structural Equation Modelling (PLS-SEM). Results revealed that perceived experience, usefulness, and ease of use have positive effects on attitude. However, regarding the effect of the same predictors on use behaviour, only perceived experience was found to be significant. Attitude was also found to have had a significant positive effect on use behaviour. This study sheds insight into the literature by exploring the relationships within the technology acceptance model via perception-attitude-behaviour linkage. Unlike prior studies, that concentrates on users’ intentions of technology adoption, this study concentrates on the users’ actual use behaviour. Further, the study provides practical suggestions and further points out the need for hospitality businesses including restaurants, to adopt chatbot as self-ordering systems for customers.

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Publication Details

Journal
Tourism and Hospitality Research
Published
2024-11-28
DOI
https://doi.org/10.1177/14673584241303861
Citations
3
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
1.04
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article

Chatbot usage at fast food restaurants in Ghana: Exploring the perception-attitude-behaviour nexus

Ricky Yao Nutsugbodo, Benjamin Appiah Osei, Bridget Emefa Aflakpui, Francis Nartey Amponsah Adamtey
3 citations
Tourism and Hospitality Research
AI in Service Interactions
1.04
article

Chatbot usage at fast food restaurants in Ghana: Exploring the perception-attitude-behaviour nexus

Ricky Yao Nutsugbodo, Benjamin Appiah Osei, Bridget Emefa Aflakpui, Francis Nartey Amponsah Adamtey
article en
3 citations

Abstract

As hospitality businesses including fast food restaurants continue to rebound after COVID-19, immersive technologies (e.g., chatbots) have become essential tools for the industry’s survival. Chatbots allow for accurate orders to be made at restaurants as well as enhancing seamless business transactions. Grounded on the Technology Acceptance Model 1 (perception-attitude-behaviour), this paper aims to investigate the attitude and use behaviour of chatbots at fast food restaurants among hospitality students. Set in the context of an emerging economy (Ghana) where the adoption of immersive technologies is still infant, this study employs a quantitative approach to offer valuable insights into chatbot usage in resource-limited settings. Results were analysed with Partial Least Squares-Structural Equation Modelling (PLS-SEM). Results revealed that perceived experience, usefulness, and ease of use have positive effects on attitude. However, regarding the effect of the same predictors on use behaviour, only perceived experience was found to be significant. Attitude was also found to have had a significant positive effect on use behaviour. This study sheds insight into the literature by exploring the relationships within the technology acceptance model via perception-attitude-behaviour linkage. Unlike prior studies, that concentrates on users’ intentions of technology adoption, this study concentrates on the users’ actual use behaviour. Further, the study provides practical suggestions and further points out the need for hospitality businesses including restaurants, to adopt chatbot as self-ordering systems for customers.

Tourism and Hospitality Research
Kwame Nkrumah University of Science and Technology (GH), University of Energy and Natural Resources (GH), University of Westminster (GB)
Openalex Percentile: Top 18%
AI in Service Interactions
1.04
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