The e-WOM intention of artificial intelligence (AI) color cosmetics among Chinese social media influencers

Abstract

Purpose

The recent advancements in smartphone technology and social media platforms have increased the popularity of artificial intelligence (AI) color cosmetics. Meanwhile, China is a lucrative market for various foreign beauty products and technological innovations. This research aims to investigate the adoption of AI color cosmetics applications and their electronic word-of-mouth (e-WOM) intention among Chinese social media influencers. Several key concepts have been proposed in this research, namely body esteem, price sensitivity, social media addiction and actual purchase.

Design/methodology/approach

An online questionnaire design was used in this research. A combination of purposive sampling and snowball sampling of AI color cosmetics users who are also social media influencers in China yields 221 respondents. To analyze the data, this research employs Structural Equation Modelling (SEM) method via SPSS and AMOS software. A 2-step approach, Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), is implemented to prove the hypotheses and generate the results.

Findings

1) Social media addiction is a positive predictor of AI color cosmetics usage, (2) AI color cosmetics usage is a positive predictor of actual purchase, (3) actual purchase is a positive predictor of e-WOM intention and lastly, (4) there is a full mediation effect of actual purchase.

Originality/value

This research draws on the uses and gratification (U&G) theory to investigate how specific user characteristics affect Chinese social media influencers' adoption of AI color cosmetics, as well as how this may affect their decision to purchase branded color cosmetics and their e-WOM.

Citation

Simay, A.E., Wei, Y., Gyulavári, T., Syahrivar, J., Gaczek, P. and Hofmeister-Tóth, Á. (2023), "The e-WOM intention of artificial intelligence (AI) color cosmetics among Chinese social media influencers", Asia Pacific Journal of Marketing and Logistics, Vol. 35 No. 7, pp. 1569-1598. https://doi.org/10.1108/APJML-04-2022-0352