This paper presents a sensitivity analysis of the hierarchical decomposition of networks in the context of seismic vulnerability of power systems. The sensitivity analysis is evaluated by varying the fragility curves and clustering algorithms on the vulnerability measure. For the fragility curves, four different curves are used. For sensitivity to clustering, four representative spectral clustering algorithms are used: SM, KVV, NJW, and Meila-Shi algorithms. The resulting vulnerability rankings are compared for a common case study (IEEE-118 test case) in terms of: correlation, identification of critical nodes, and identification of common clusters. The results show the robustness of the methodology with respect to variation of the fragility curves. On the other hand, the selection of the clustering algorithm is found to be a decisive parameter depending on application. If the application requires identification of critical elements a better performance is found.