Using entropy and AHP-TOPSIS for comprehensive evaluation of internet shopping malls and solution optimality

Consumers are switching from offline to online to buy everything due to this reason nowadays internet shopping malls (ISMs) are setting up a very crucial role in the economy. For assessment and ranking are basically a critical work which could be exploitation of internet shopping malls information resources when consider in a scientific way, there are many methods for the evaluation and ranking of e-commerce sites. Taking into consideration traffic rank, inbound links, competition, speed, and keyword statistics, in literature multi criteria decision making (MCDM) methods are rarely used by the researchers to find the rank of internet shopping malls (ISMs) on the basis of primary/secondary data of these influencing factors. This study, therefore, is unique to narrow down the gap in literature by employing MCDM methods i.e. entropy and analytic hierarchy process (AHP) to collect the weight of influencing factors and technique for order preference by similarity to ideal (TOPSIS) to find the rank of internet shopping malls (ISMs). After finding out the rank of selected criteria, solution optimality needs to be done to find the average ideal solution matrix. Conclusion and managerial implications of the study are also discussed.