Factors Analysis of Interest in Using Pay Later in E-commerce Applications Using Principal Component Analysis and Maximum Likelihood Estimation Methods

Abstract

Pay later is one of the fastest growing payment methods in E-Commerce Applications. Although the use of pay later is increasing, pay later is not the main payment tool that people choose. The purpose of this study is to determine the factors that influence the interest in using Pay later, especially in the Shopee application, and the most dominant factors by comparing two-factor extraction methods, namely Principal Component Analysis and Maximum Likelihood Estimation. Respondents in this study were 125 Shopee application users who had used Shopee Pay later which was carried out by purposive sampling method. The method used in this research is the quantitative method. The results of this study indicate that the principal component analysis method is a feasible method to use because it has a low value on the RMSE and has a strong loading factor value (close to 1) so it can explain the formation of factors. The Principal Component Analysis method produces 3 factors that are formed from 11 variables. The most dominant factor in the influence of interest in using Shopee Pay later with the Principal Component Analysis method is the effect of benefits because the variable of benefit influence has the highest loading factor in decision making.