Risk decision-making based on Mahalanobis-Taguchi system and grey cumulative prospect theory for enterprise information investment

Abstract

For the decision-making problem of enterprise information technology investment risk, based on existing research shortage, this paper proposes a risk decision-making method based on cloud model, Mahalanobis-Taguchi system and grey cumulative prospect theory with the consideration of the fuzziness of evaluating language and subjective risk attitude of decision makers. The method results in the ``quantitative to qualitative'' transformation of risk evaluation in information technology investment by cloud model and constructs interval numbers decision matrices according to the ``3En'' principle. An m-dimensional interval numbers decision vector is regarded as super cuboids in m-dimensional attributes space, using two-level orthogonal experiment to arrange points uniformly and dispersedly. The numbers of points are assured by testing numbers of two-level orthogonal arrays and these points compose of distribution points set to stand for decision-making project. In order to eliminate the influence of correlation among indices, Mahalanobis distance is used to calculate the distance from each investment program to ideal programs. Since the decision-maker's attitude can affect the decision result when the investment decision-making in practice, the paper defines the grey correlation coefficient and the prospect value function based on Mahalanobis distance, and calculates the comprehensive prospect value of each program and finds the optimal one. Finally, an example application proves that the method is a feasible and effective method of decision-making. Compared with other methods, the result is much more realistic and superior.