Abstract
This is an open access article distributed under the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits unrestricted non-commerical use, distribution, and reproduction in any medium, provided the original work is properly cited.
Highlights
The formal theory of social network analysis encompasses centrality measures, and these are to be employed in this research that dwells on the mergers of weights to evaluate network topologies and make a prediction
In the supply chain management (SCM), the node-weights could be any of the volume of sales, cost of storage or turnover at a depot/store, while the edges will be the distance between each depot and a proposed distribution centre (DC)
The network coverage of an existing distribution centre (DC) located at Scotland was investigated and the retail outlets or shops are considered as nodes with the value of sales taken to be the weights on the nodes while distances between nodes are regarded as the weights on the edges
Summary
The formal theory of social network analysis encompasses centrality measures, and these are to be employed in this research that dwells on the mergers of weights (link-weights and node weights) to evaluate network topologies and make a prediction. The equation (1) below represents the weighted degree centrality with respect to the edges or links. The above argument is extended to the weighted centrality of the four measures, i.e. Degree, Closeness, Betweenness and the Eigenvector. Equation (6) below thereby represents the product of degree of a focal node and the average weight to these nodes as adjusted by the introduced tuning parameter. In the supply chain management (SCM), the node-weights could be any of the volume of sales, cost of storage or turnover at a depot/store, while the edges will be the distance between each depot and a proposed distribution centre (DC). WEIGHTED MARKING METHOD AND CLIQUE STRUCTURE/NODE-WEIGHT MODULATED CENTRALITY MEASURES APPLIED TO SUPPLY CHAIN MANAGEMENT
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