METHOD FOR PROJECT RANKING BY QUANTITATIVE AND QUALITATIVE CRITERIA

Abstract

Determining the efficiency and priority of R&D projects has always been topical and important. It has been widely considered by numerous home and foreign researchers. However, the problem of project evaluation by preference in a multidimensional space of heterogeneous criteria has not been adequately addressed yet. The main goal of this paper is to present a method of project ranking by quantitative and qualitative criteria based on a consistent criteria scaling algorithm and to demonstrate its applicability. The consistent scaling algorithm (CSA) is a variant of the familiar algorithms of joint criteria scaling. As distinct from an independent scaling algorithm (ISA), which is used in the construction of an additive integral value function (IVF) in normalized form, the CSA is used in the construction of a canonical IVF. These algorithms are based on methods of multi-attribute utility theory, which use the operation of trading off one quality index against another. The classical CSA and ISA have a resolution equal to one, but they operate with qualitative criteria alone, thus considerably narrowing their field of application. To resolve this problem, the tradeoff operation of replacement in the CSA was modified, and a special procedure was proposed for joint scaling of heterogeneous criteria. Based thereon, stage-by-stage procedures were developed to construct local value functions both for qualitative and for quantitative criteria. As a result, the following problems were solved. A method was proposed to verify the preferential independence of qualitative criteria. By modifying the CSA, the problem of incomparability of heterogeneous criteria was overcome. An additive model of a canonical IVF was constructed for heterogeneous criteria, and several methods to verify the IVF for adequacy were proposed, including a constructive verification, which allows one to formally identify inadequate models. A method was developed to rank alternatives in a space of quantitative and qualitative criteria with a maximum resolution. This work used methods of decision-making theory, multi-attribute utility theory, and verbal analysis of solutions. The obtained results may be used in evaluating the efficiency of innovative technologies, in project competitions, and in R&D program formation, thus improving project management quality and allowing one to justify project advisability.

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