Information quality is a concept that can be used to measure the information of probability distribution. Dempster-Shafer evidence theory can describe uncertain information more reasonably than probability theory. Therefore, it is a research hot spot to propose information quality applicable to evidence theory. Recently, Deng proposed the concept of information volume based on Deng entropy. It is worth noting that, compared with the Deng entropy, the information volume of the Deng entropy contains more information. Obviously, it may be more reasonable to use information volume of Deng entropy to represent uncertain information. Therefore, this article proposes a new information quality, which is based on the information volume of Deng entropy. In addition, when the basic probability (BPA) degenerates into a probability distribution, the proposed information quality is consistent with the information quality proposed by Ygare and Petry. Finally, several numerical examples illustrate the effectiveness of this new method.