Enhancing User-Centered Excellence by Evaluating Satisfaction with the e-Magazine Admin Experience Through Quantitative Ratings

This study investigates the accuracy of user ratings provided by e-magazine applications on two different platforms: Web App and iOS. The research aims at solving the problem of slow or delayed precision of rating during users look up through the different versions of the two platforms. A sample size of N = 13 (G power: Hypothesis testing (with a 85% confidence level) was also employed to compare performance measures on the two sites. The results herein show that the Web App has a rating precision of 35.31 milliseconds; this is more efficient than the iOS app with 27.69 % efficiency. Nevertheless, it can be seen from the recorded figures that there is no much variation between the two sites’ performances (p less than 0.010). The research shows that although the Web App demonstrated the somewhat higher rating accuracy of 27.69%, the iOS app’s performance is relatively worse is only at about 34% of efficiency. As for the practical implications of this research, it can be stated that both platforms are capable of preserving the rating accuracy of e-magazine applications.