Usability Evaluation of Artificial Intelligence for Image Recognition Features in Online Shopping Applications Using the UTAUT Method

Abstract

This study has the purpose of measuring the usability level of the image recognition feature on the Shopee and Lazada applications using the UTAUT method to measure the usability level. The variables used in this study are performance expectancy, effort expectancy, social influence, facilitating conditions, usability expectancy, and use behavior. Meanwhile, four moderate variables were involved: age, gender, experience, and voluntariness of use. This study performs structural equation modeling (SEM) using partial least square (PLS) to investigate the relationship between variables. Based on the R-square value, it can be concluded that the UTAUT method is better at evaluating the usability of the image recognition feature in Lazada than in the Shopee application. The reason is the R-square value of the dependent variable usability expectancy in the Lazada application has the highest R-square value of 0.957. This result means that the BI variable can be explained by the independent variables performance expectancy, effort expectancy, and social influence of 95.7%.