MCDM Method for Evaluating and Ranking the Online Shopping Websites Based on a Novel Distance Measure Under Intuitionistic Fuzzy Environment

This paper explores the concept of online shopping malls in terms of information technology as a multi-criteria decision-making (MCDM) challenge under an intuitionistic fuzzy environment. The intuitionistic fuzzy sets (IFSs) have a wider range of applications than fuzzy sets (FSs) due to their enhanced capability to handle information uncertainty. Despite the usefulness of IFSs, some of the existing measures for IFSs have been found to have shortcomings in handling the complexity of real-world applications. Some of these measures are inadequate and do not yield desirable results. Therefore, there is a need to develop new distance measures based on the Hausdorff metric that can overcome these limitations and provide more reliable and accurate results and also discuss their several mathematical properties. We compare suggested distance/similarity measures with existing measures and find that they are simpler, more intuitive, and better suited for most applications. Furthermore, we proposed an intuitionistic fuzzy linguistic MCDM method for the evaluation of Internet shopping malls. The enhancement of competitive advantage in Internet shopping malls is primarilapplied IFSs to pattern recognition, whiley attributed to factors such as information and e-service dimension, web creativity as well as online reputation. Amazon. in and Myntra. com is recognized as the top two pioneering internet shopping malls. This research introduces an intuitionistic fuzzy MCDM model aimed at aiding decision-makers and planners in evaluating and selecting digital shopping technology. A case study is also discussed for evaluating and ranking internet shopping websites. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.