This paper presents a study of the bounded confidence model applied to the complex networks. Two different cases were examined: opinion formation process in the Barabási–Albert network and corruption spreading in a hierarchical network. For both cases, the value of the bounded confidence parameter ε was assumed as a constant, or its value was dependent on the degree of a node in the network. To measure the opinion formation and corruption spreading processes, we introduced the order parameter related to the number of interfaces in the system. As a results of numerical simulations, the influence of the values of ε on the final opinions in the population, as well as, the influence of an initial source of corruption in the company structure on the corruption spreading process, were obtained and discussed.