A dynamic grey target evaluation method with multiple reference points for new R&D institution performance

Abstract

As a new business form of innovation and development, new R&D institutions are characterized by their focus on regional and industrial major technical needs, diversified investment subjects, diversified construction models, and marketization of operation mechanism. Their performance evaluation faces new problems and challenges. This paper proposes a new dynamic grey target evaluation model of R&D institutions’ performance in regard to four evaluation indexes, three reference points, and four stages. Aiming at resolving the multi-attribute dynamic decision problem with the attribute value being an interval grey number and the decision-maker’s weight information unknown, we propose the use of the close degree of grey incidence method to determine the index weight. Our approach revolves around three reference points: peers, development, and expectations. Value matrices of the three reference points are expressed according to the Cumulative Prospect Theory, which also determines the distance from the center of the grey target. Based on the Orness measure, we establish a multi-stage weight optimization model to calculate the stage weight and the comprehensive cumulative prospect value of each agency. Finally, we verify the validity and practicability of our method with the use of parameter sensitivity analysis, a comparison with other methods, and a case study.