Evaluation of E-Commerce Sites using Novel Similarity Measure of Neutrosophic Hypersoft Sets

Abstract

E-commerce has become a common method of making online purchases. Doorstep delivery, multiple options and variety of products to be bought, discounts and rewards are some of the advantages of online shopping. However, selection of the right shopping website is a challenge for online buyers across all markets. The multiple tangible and intangible factors involved in the e-commerce domain has made it a problem of MCDM. This paper proposes a new MCDM approach to develop a model for the necessary assessment of e-commerce websites. The notion of similarity measures for the single valued neutrosophic hypersoft sets is applied to get the best website on the bases of given criteria. Shopping websites are evaluated at three levels-below average, average and good. The attributes used to evaluate the websites are offers and deals made by the e-commerce sites to present and potential customers, qualitative assessment of the offered products and services, delivery timelines, payment safety and security concerns. Safety of personal data is the attribute which is judged as the most important factor in evaluation of shopping websites