Moore's law will slow down in the next decades and potentially even stop due to unbridgeable physical challenges. In order to continue the trend of progressively increasing complex designs with ever-decreasing costs per transistor, the CMOS technology will have to be replaced by a new device technology. There are a multitude of these technologies known today. However, the identification of the most promising technologies is challenging due to two reasons. First, the successor technologies need to be assessed based on quantitative metrics (e.g., energy and speed) and qualitative metrics (e.g., reliability and CMOS compatibility). Second, most of the technologies are still in a very early stage, and only estimations on their characteristics are available. In this paper, we present a new methodology that enables a combined evaluation of qualitative and quantitative characteristics, and which can handle imprecise data in terms of uncertainty intervals. The methodology is applied to a data set taken from the International Technology Roadmap for Semiconductors.