Identifying critical locations in road networks assists in reducing intermitting services and increases the quality of life. Complex networks applications are used in transportation networks to identify critical locations from a topological point of view. However, critical locations change when there are disruptions and people move towards a specific service inside its catchment area. In this paper, a modified betweenness centrality is used to identify critical locations when moving towards a single service. This index, the origin-destination betweenness centrality, is used to identify important locations in the baseline scenario on a case study from Kathmandu, Nepal. Furthermore, random disruptions with increasing magnitude are simulated to understand a networks’ behavior and to identify the changes in those critical locations under extreme conditions. The results showed that the origin-destination betweenness centrality is an effective index. Random disruption simulations can assist decision-makers in preparing recovery plans.