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

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.

Citation

Dassouli, S., Satt, H. and Senhaji, N. (2024), "Attitude and behavior towards chatbots: case of the beauty care industry", International Journal of Pharmaceutical and Healthcare Marketing, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJPHM-09-2023-0086