Attitude and behavior towards chatbots: case of the beauty care industry

Purpose This paper aims to provide a model that expands the technology acceptance model (TAM) by identifying aspects that influence consumers’ attitude and behavioral intention toward chatbots in the beauty care industry. Design/methodology/approach This study is based on an online questionnaire responded by 211 Generation Z individuals from Morocco. Data was collected based on a convenience nonprobability sampling technique, and a partial least squares-structural equation modeling was used to validate the model and test the hypotheses. Findings Perceived ease of use, perceived usefulness and subjective norms are significant influencers of the attitude toward chatbot. Perceived risk was not found to be influencing behavioral intention to use chatbot, and personality does not moderate the relationship between perceived ease of use and attitude. Research limitations/implications This paper provides insights into the motives behind customers’ attitude and behavior toward chatbots in the beauty care industry and can be relied on as a guideline for implementations technology to boost sales and build strong relationship with customers. Practical implications This research provides new insight for retailers on the implementation of chatbots at the point of sale. Marketers and business owners should be aware of the usefulness and ease of use of technology for Generation Z and be able to interact with them on this basis in order to generate increased economic performance and better brand image. Originality/value The model extends the original TAM and introduces two new constructs, subjective norms and perceived risk, in addition to including personality as a moderating factor. The data was gathered from the under-studied region of North Africa.

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Publication Details

Journal
International Journal of Pharmaceutical and Healthcare Marketing
Published
2024-10-08
DOI
https://doi.org/10.1108/ijphm-09-2023-0086
Citations
5
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
1.74
Controls
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article

Attitude and behavior towards chatbots: case of the beauty care industry

Sara Dassouli, Harit Satt, Nissrine Senhaji
5 citations
International Journal of Pharmaceutical and Healthcare Marketing
AI in Service Interactions
1.74
article

Attitude and behavior towards chatbots: case of the beauty care industry

Sara Dassouli, Harit Satt, Nissrine Senhaji
article en
5 citations

Abstract

Purpose This paper aims to provide a model that expands the technology acceptance model (TAM) by identifying aspects that influence consumers’ attitude and behavioral intention toward chatbots in the beauty care industry. Design/methodology/approach This study is based on an online questionnaire responded by 211 Generation Z individuals from Morocco. Data was collected based on a convenience nonprobability sampling technique, and a partial least squares-structural equation modeling was used to validate the model and test the hypotheses. Findings Perceived ease of use, perceived usefulness and subjective norms are significant influencers of the attitude toward chatbot. Perceived risk was not found to be influencing behavioral intention to use chatbot, and personality does not moderate the relationship between perceived ease of use and attitude. Research limitations/implications This paper provides insights into the motives behind customers’ attitude and behavior toward chatbots in the beauty care industry and can be relied on as a guideline for implementations technology to boost sales and build strong relationship with customers. Practical implications This research provides new insight for retailers on the implementation of chatbots at the point of sale. Marketers and business owners should be aware of the usefulness and ease of use of technology for Generation Z and be able to interact with them on this basis in order to generate increased economic performance and better brand image. Originality/value The model extends the original TAM and introduces two new constructs, subjective norms and perceived risk, in addition to including personality as a moderating factor. The data was gathered from the under-studied region of North Africa.

International Journal of Pharmaceutical and Healthcare MarketingVol. 19(1)
Al Akhawayn University (MA)
Openalex Percentile: Top 13%
AI in Service Interactions
1.74
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