Combining entropy weight and TOPSIS method for information system selection

Abstract

This study proposes a combined entropy weight and TOPSIS method for information system selection. In the present paper, information entropy is employed to derive the objective weights of the evaluation criteria, and a modified TOPSIS method is employed to rank a finite number of feasible alternatives in order of preference and then select a suitable information system that conforms to the decision maker’s ideal. An empirical study demonstrated the feasibility and practicability of the proposed method for real-world applications. The result shows that the approach is computationally simple and its underlying concept is rational and comprehensible, thus facilitating its implementation in a computer-based system.