Occasions do arise when researchers and industrialists alike are faced with the decision of where to cite new structures (shops, stores, distribution centers etc) in order to benefit the consumers and the business entity as well. Such decisions might take the importance of vertices and/or edges of a network (e.g. Supply Chain Network) into consideration. In particular, the strength of the vertices and those of the edges play an important role in arriving at such decisions. In this paper, as against the most common and traditional measures of centralities, that is - Degree, Closeness, Betweenness and Eigen-Vector centralities, a new centrality measure, Top Eigen-Vector Weighted Centrality (TEVWC) which takes into consideration the clique structure of a network and the strengths attached to the vertices/edges of the network, was used to predict the location of a distribution center in a supply chain management. The accuracy of prediction on a sample dataset of supply chain network, using the TEVWC was found to be 94.6%, which is 10.6% higher than the result outcome from the method of Newtonian Gravitational Force when driving distances are considered, but with the earth distances the accuracy obtained is 99%.