{"id":{"repo_id":"nus","oai_identifier":"oai:scholarbank.nus.edu.sg:10635/153982"},"canonical_url":"https://search.dev.ndltd.org/etd/nus/oai:scholarbank.nus.edu.sg:10635/153982","repository":{"repo_id":"nus","name":"National University of Singapore","base_url":"https://scholarbank.nus.edu.sg/oai/request"},"display":{"title":"ANALYZING CONNECTION PATTERNS IN A TRANSHIPMENT PORT","abstract":"The port of Singapore is world™s busiest port in terms of total shipping tonnage and is also the world™s busiest transhipment port. This research aims to use the data from the connections between the shipping liners at the port of Singapore to obtain certain key indicators, which will allow for strategic planning of port operations. In particular, the use of social network analysis is tried and employed to obtain macro indicators, which will aid in decision support. Social network analysis is an emerging key analytical technique in analyzing informal networks. The analysis differs from traditional network theory in the heavier emphasis on the relations between the actors in a network as compared to their intrinsic attributes. This technique was found to be a suitable candidate for trial due to transhipment between shipping liners bearing a strong resemblance to social networks. The relationships can be strong or weak depending on the amount of volume flow between two shipping lines. The research has resulted in the development of an application, which makes use of a social network concept of œcoreness to determine which shipping liners are more important in a social context compared to others as well as various other indicators which allow for comparison over time.","abstract_html":"The port of Singapore is world™s busiest port in terms of total shipping tonnage and is also the world™s busiest transhipment port. This research aims to use the data from the connections between the shipping liners at the port of Singapore to obtain certain key indicators, which will allow for strategic planning of port operations. In particular, the use of social network analysis is tried and employed to obtain macro indicators, which will aid in decision support. Social network analysis is an emerging key analytical technique in analyzing informal networks. The analysis differs from traditional network theory in the heavier emphasis on the relations between the actors in a network as compared to their intrinsic attributes. This technique was found to be a suitable candidate for trial due to transhipment between shipping liners bearing a strong resemblance to social networks. The relationships can be strong or weak depending on the amount of volume flow between two shipping lines. The research has resulted in the development of an application, which makes use of a social network concept of œcoreness to determine which shipping liners are more important in a social context compared to others as well as various other indicators which allow for comparison over time.","abstract_has_math":false,"creators":["LIM LUI CHENG"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-24T03:32:30Z","subjects":["Transhipment pattens","social networks analysis"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["LIM LUI CHENG"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2008"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://scholarbank.nus.edu.sg/handle/10635/153982"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Transhipment pattens","social networks analysis"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://scholarbank.nus.edu.sg/bitstreams/9c4476e8-577b-4f99-8019-557642087c9c/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The port of Singapore is world™s busiest port in terms of total shipping tonnage and is also the world™s busiest transhipment port. This research aims to use the data from the connections between the shipping liners at the port of Singapore to obtain certain key indicators, which will allow for strategic planning of port operations. In particular, the use of social network analysis is tried and employed to obtain macro indicators, which will aid in decision support. Social network analysis is an emerging key analytical technique in analyzing informal networks. The analysis differs from traditional network theory in the heavier emphasis on the relations between the actors in a network as compared to their intrinsic attributes. This technique was found to be a suitable candidate for trial due to transhipment between shipping liners bearing a strong resemblance to social networks. The relationships can be strong or weak depending on the amount of volume flow between two shipping lines. 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In particular, the use of social network analysis is tried and employed to obtain macro indicators, which will aid in decision support. Social network analysis is an emerging key analytical technique in analyzing informal networks. The analysis differs from traditional network theory in the heavier emphasis on the relations between the actors in a network as compared to their intrinsic attributes. This technique was found to be a suitable candidate for trial due to transhipment between shipping liners bearing a strong resemblance to social networks. The relationships can be strong or weak depending on the amount of volume flow between two shipping lines. 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