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Clique structure and node-weighted centrality measures to predict distribution centre location in the supply chain management
Much importance is attached to the weights on the edges in a network, but in actual fact what makes up a network is both the nodes and the edges linking up the network. It is therefore pertinent to investigate the effects and importance of the weights attributed unto the nodes in a network as well a...
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creator | Akanmu, Amidu A. G. Wang, Frank Z. Yamoah, Fred A. |
description | Much importance is attached to the weights on the edges in a network, but in actual fact what makes up a network is both the nodes and the edges linking up the network. It is therefore pertinent to investigate the effects and importance of the weights attributed unto the nodes in a network as well as the weights on the links of such networks as they both play important roles in determining the prominence or popularity of actors within any particular network. Principles of centrality measures were employed in the supply chain management to show that the weighted-ness of the edges/nodes together with the clique structure that emanates from it can be a pointer to centrality or otherwise of members of a group in the network of a distribution system. As expected, it was affirmed that the nodes belonging to the high clique members have a high percentage of being chosen/predicted as the most likely distribution centre. We examined the cliques of the weighted centrality matrix for the distributed system of a supply chain management network, and from the outcome we are able to predict a location of a new distribution centre in and around a particular area/region with an accuracy of more than 66%. In addition, the distinction between the notion of link-weightedness and node-weightedness were clarified. |
doi_str_mv | 10.1109/SAI.2014.6918178 |
format | conference_proceeding |
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G. ; Wang, Frank Z. ; Yamoah, Fred A.</creator><creatorcontrib>Akanmu, Amidu A. G. ; Wang, Frank Z. ; Yamoah, Fred A.</creatorcontrib><description>Much importance is attached to the weights on the edges in a network, but in actual fact what makes up a network is both the nodes and the edges linking up the network. It is therefore pertinent to investigate the effects and importance of the weights attributed unto the nodes in a network as well as the weights on the links of such networks as they both play important roles in determining the prominence or popularity of actors within any particular network. Principles of centrality measures were employed in the supply chain management to show that the weighted-ness of the edges/nodes together with the clique structure that emanates from it can be a pointer to centrality or otherwise of members of a group in the network of a distribution system. As expected, it was affirmed that the nodes belonging to the high clique members have a high percentage of being chosen/predicted as the most likely distribution centre. We examined the cliques of the weighted centrality matrix for the distributed system of a supply chain management network, and from the outcome we are able to predict a location of a new distribution centre in and around a particular area/region with an accuracy of more than 66%. 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G.</creatorcontrib><creatorcontrib>Wang, Frank Z.</creatorcontrib><creatorcontrib>Yamoah, Fred A.</creatorcontrib><title>Clique structure and node-weighted centrality measures to predict distribution centre location in the supply chain management</title><title>2014 Science and Information Conference</title><addtitle>SAI</addtitle><description>Much importance is attached to the weights on the edges in a network, but in actual fact what makes up a network is both the nodes and the edges linking up the network. It is therefore pertinent to investigate the effects and importance of the weights attributed unto the nodes in a network as well as the weights on the links of such networks as they both play important roles in determining the prominence or popularity of actors within any particular network. Principles of centrality measures were employed in the supply chain management to show that the weighted-ness of the edges/nodes together with the clique structure that emanates from it can be a pointer to centrality or otherwise of members of a group in the network of a distribution system. As expected, it was affirmed that the nodes belonging to the high clique members have a high percentage of being chosen/predicted as the most likely distribution centre. We examined the cliques of the weighted centrality matrix for the distributed system of a supply chain management network, and from the outcome we are able to predict a location of a new distribution centre in and around a particular area/region with an accuracy of more than 66%. In addition, the distinction between the notion of link-weightedness and node-weightedness were clarified.</description><subject>Accuracy</subject><subject>Centrality</subject><subject>Cities and towns</subject><subject>Clique</subject><subject>Conferences</subject><subject>Distribution centres</subject><subject>Educational institutions</subject><subject>Emission</subject><subject>Joining</subject><subject>Links</subject><subject>Management</subject><subject>Networks</subject><subject>Roads</subject><subject>Supply chain management</subject><subject>Supply chains</subject><subject>Tuning</subject><subject>Weight measurement</subject><isbn>0989319334</isbn><isbn>9780989319331</isbn><isbn>0989319318</isbn><isbn>9780989319317</isbn><isbn>0989319326</isbn><isbn>9780989319324</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2014</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpFkM1LxDAQxSMiqOveBS85eumaSbpNc1wWPxYWPKjnkibT3Uib1iZF9uD_bnAXhIHhDb_34A0ht8AWAEw9vK02C84gXxQKSpDlGblmqlQC0pTn_0Lkl2QewidjDKQUnOdX5Gfduq8JaYjjZOI0ItXeUt9bzL7R7fYRLTXo46hbFw-0Qx0SFGjs6TCidSZS65LZ1VN0vT-ySNve6D_tPI37FD8NQ3ugZq_TodNe77BL5A25aHQbcH7aM_Lx9Pi-fsm2r8-b9WqbOeAiZoWSdWNKUIw3VtYci1wt87qQIGyDwhpcmlyKQtQaBXI0ILAxKhdmCUqrQszI_TF3GPvUNsSqc8Fg22qP_RQqkExJkAUTCb07og4Rq2F0nR4P1emz4hdHZ2-4</recordid><startdate>20140801</startdate><enddate>20140801</enddate><creator>Akanmu, Amidu A. G.</creator><creator>Wang, Frank Z.</creator><creator>Yamoah, Fred A.</creator><general>The Science and Information (SAI) Organization</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope><scope>7SC</scope><scope>7SP</scope><scope>7TA</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20140801</creationdate><title>Clique structure and node-weighted centrality measures to predict distribution centre location in the supply chain management</title><author>Akanmu, Amidu A. G. ; Wang, Frank Z. ; Yamoah, Fred A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i123t-697bfc81902fd7b2e64954b6713dfe3dce5c47363bae3e2ec13efc943c519a963</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Accuracy</topic><topic>Centrality</topic><topic>Cities and towns</topic><topic>Clique</topic><topic>Conferences</topic><topic>Distribution centres</topic><topic>Educational institutions</topic><topic>Emission</topic><topic>Joining</topic><topic>Links</topic><topic>Management</topic><topic>Networks</topic><topic>Roads</topic><topic>Supply chain management</topic><topic>Supply chains</topic><topic>Tuning</topic><topic>Weight measurement</topic><toplevel>online_resources</toplevel><creatorcontrib>Akanmu, Amidu A. G.</creatorcontrib><creatorcontrib>Wang, Frank Z.</creatorcontrib><creatorcontrib>Yamoah, Fred A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Materials Business File</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Akanmu, Amidu A. 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It is therefore pertinent to investigate the effects and importance of the weights attributed unto the nodes in a network as well as the weights on the links of such networks as they both play important roles in determining the prominence or popularity of actors within any particular network. Principles of centrality measures were employed in the supply chain management to show that the weighted-ness of the edges/nodes together with the clique structure that emanates from it can be a pointer to centrality or otherwise of members of a group in the network of a distribution system. As expected, it was affirmed that the nodes belonging to the high clique members have a high percentage of being chosen/predicted as the most likely distribution centre. 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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Accuracy Centrality Cities and towns Clique Conferences Distribution centres Educational institutions Emission Joining Links Management Networks Roads Supply chain management Supply chains Tuning Weight measurement |
title | Clique structure and node-weighted centrality measures to predict distribution centre location in the supply chain management |
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