Improving the E-Store Business Model for Satisfying Customers' Needs Using a Hybrid MCDM Combined DANP with Grey Relational Model

Abstract

The current paper aims to qualitatively and quantitatively measure and evaluate e-store index criteria used to achieve the aspired levels for satisfying customers' needs. Such research should help e-store managers understand customers' feelings and requirements for improving the e-store business. Therefore, in the current approach, we use a hybrid MCDM model to address the dependent relational problems among the criteria. Specifically, we combine DANP (DEMATEL-based ANP) and grey relation analysis (GRA) methods to calculate the relative importance weights and relation of the criteria between interdependence and feedback. We also propose a strategy to improve the criteria gap for closing to the aspired levels of human life and convenient service. As such, this research can provide e-store managers with an understanding of how to improve business models in order to achieve consumers' needs and promote more repurchases and enable them to devise the best marketing strategies to provide the most effective and efficient service for their customers.