Soft computing based e-commerce website service quality index measurement

Abstract

It is observed that there is a need for a quality measurement template system that is easy to understand, effective, easily updated according to different requests, contains enough variables, and gives fast results, which can be placed on websites except for general evaluation comments or 5-star rating evaluations after a customer makes a purchase from the online shopping website. For this reason, an inference system based on human reasoning is developed to measure practically the quality index of e-commerce shopping websites according to customer feedback in this study. The proposed system includes four subs and one main fuzzy inference system. 11 parameters affecting the problem are used in subsystems, while five main parameters are used in the main inference system. The main parameters are cargo and delivery performance (CDP), customer support and campaign performance (CSCP), ease of payment and return (EPR), interface quality (IQ), and privacy-security. The subsystems produce detailed outputs for the main parameters other than privacy-security. E-commerce shopping website service quality index is computed in the main system that processes the outputs of the subsystems. In addition, survey data is applied for verifying and supporting the study. Respondents in the survey were asked about the parameter values for their 1st and 2nd preferred shopping websites and it was observed that A3 e-commerce website has high quality index, and A1 e-shopping website has good quality index but should improve its CSCP dimensions. A4 website especially should improve its IQ and EPR dimensions and its quality index is not good compared to others. Finally, a graphical user interface application of the system is formed.