Formulating Method to Improve Web Quality: Integrating Fuzzy Logic, Web Quality, and Refined Kano

Abstract

Disruption of technology requires businesses to perform digital transformation in its product marketing, one of which includes owning an e-commerce website. By having an e-commerce website, businesses get detailed consumer behavior patterns from their visits. This pattern of behavior can be utilized for future business process development. The importance of the existence of this e-commerce website requires businesses to be able to provide the best service when consumers access the website. In this research, the appropriate methods are formulated for businesses to improve the quality of their e-commerce services. In previous studies, Web Quality and Refined Kano methods are often used to improve the quality of e-commerce services. Although the two methods are often integrated to find more accurate recommendations, the recommendations produced are still subjective and have a high level of ambiguity. To reduce the level of subjectivity and ambiguity, it is necessary to integrate fuzzy logic into Web Quality and Refined Kano. The integration of fuzzy, Web Quality, and Refined Kano methods is expected to provide the most accurate and objective recommendations for businesses to improve the quality of their e-commerce services.