We investigate the clustering properties of 45441 radio-quiet quasars (RQQs) and 3493 radio-loud quasars (RLQs) drawn from a joint use of the Sloan Digital Sky Survey (SDSS) and Faint Images of the Radio Sky at 20 cm (FIRST) surveys in the range 0.3 < z < 2.3. This large spectroscopic quasar sample allow us to investigate the clustering signal dependence on radio-loudness and black hole (BH) virial mass. We find that RLQs are clustered more strongly than RQQs in all the redshift bins considered. We find a real-space correlation length of r 0 = 6.59 +0.33 −0.24 h −1 Mpc and r 0 = 10.95 +1.22 −1.58 h −1 Mpc for RQQs and RLQs, respectively, for the full redshift range. This implies that RLQs are found in more massive host haloes than RQQs in our samples, with mean host halo masses of ∼ 4.9 × 10 13 h −1 M and ∼ 1.9 × 10 12 h −1 M , respectively. Comparison with clustering studies of different radio source samples indicates that this mass scale of 1 × 10 13 h −1 M is characteristic for the bright radio-population, which corresponds to the typical mass of galaxy groups and galaxy clusters. The similarity we find in correlation lengths and host halo masses for RLQs, radio galaxies and flat-spectrum radio quasars agrees with orientation-driven unification models. Additionally, the clustering signal shows a dependence on black hole (BH) mass, with the quasars powered by the most massive BHs clustering more strongly than quasars having less massive BHs. We suggest that the current virial BH mass estimates may be a valid BH proxies for studying quasar clustering. We compare our results to a previous theoretical model that assumes that quasar activity is driven by cold accretion via mergers of gas-rich galaxies. While the model can explain the bias and halo masses for RQQs, it cannot reproduce the higher bias and host halo masses for RLQs. We argue that other BH properties such as BH spin, environment, magnetic field configuration, and accretion physics must be considered to fully understand the origin of radio-emission in quasars and its relation to the higher clustering.