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    Social Network Analysis Approach for Improved Transportation Planning

    Source: Journal of Infrastructure Systems:;2017:;Volume ( 023 ):;issue: 002
    Author:
    Islam H. El-adaway
    ,
    Ibrahim S. Abotaleb
    ,
    Eric Vechan
    DOI: 10.1061/(ASCE)IS.1943-555X.0000331
    Publisher: American Society of Civil Engineers
    Abstract: Social network analysis (SNA) is a well-established methodology for investigating networks through the use of mathematical formulations abstracted from graph theory. It has been successfully used in social sciences to evaluate how individuals and institutions are affected by societal or professional networks, and it has been applied to some civil and construction engineering applications where a network’s main actors are people or organizations controlled by people. Current transportation analysis tools are expensive and time consuming, and require rigorous data for reliable results. Accordingly, a quick and inexpensive methodology to preliminarily analyze traffic networks is beneficial to better direct more detailed transportation analyses. Because of its ability to grasp the full complexity and connectivity of networks in a timely and cost effective manner, SNA can fulfill this requirement. Mathematically speaking, social networks are very close to transportation networks because they share fundamental characteristics. This paper uses SNA to analyze transportation networks and consequently corroborate its effectiveness as a complementary tool for improved transportation planning. To this end, the authors adopted a four-step interrelated research methodology: (1) investigating the connection between the language and concepts of SNA and those of transportation systems; (2) using different SNA centrality measures in the transportation context; (3) using SNA in two case studies in Mississippi; and (4) analyzing the results of the case studies and drawing conclusions. The SNA approach was able to easily and quickly determine the most critical intersections in the investigated transportation networks. These results were in alignment with Mississippi Department of Transportation (MDOT 2014) traffic studies. Using SNA, the research also demonstrated that the performance of central intersections drives the overall performance of the area roadway network. Accordingly, SNA is believed to be an effective and innovative tool in transportation analysis. Using it as an initial analysis step to identify critical areas will assist decision makers in better focusing their more detailed analyses using validated traditional methods in such areas only compared with the entire network. This will significantly decrease the invested resources in transportation planning and will create a more integrated and holistic perspective for evaluating transportation networks.
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      Social Network Analysis Approach for Improved Transportation Planning

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4238494
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    contributor authorIslam H. El-adaway
    contributor authorIbrahim S. Abotaleb
    contributor authorEric Vechan
    date accessioned2017-12-16T09:05:54Z
    date available2017-12-16T09:05:54Z
    date issued2017
    identifier other%28ASCE%29IS.1943-555X.0000331.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4238494
    description abstractSocial network analysis (SNA) is a well-established methodology for investigating networks through the use of mathematical formulations abstracted from graph theory. It has been successfully used in social sciences to evaluate how individuals and institutions are affected by societal or professional networks, and it has been applied to some civil and construction engineering applications where a network’s main actors are people or organizations controlled by people. Current transportation analysis tools are expensive and time consuming, and require rigorous data for reliable results. Accordingly, a quick and inexpensive methodology to preliminarily analyze traffic networks is beneficial to better direct more detailed transportation analyses. Because of its ability to grasp the full complexity and connectivity of networks in a timely and cost effective manner, SNA can fulfill this requirement. Mathematically speaking, social networks are very close to transportation networks because they share fundamental characteristics. This paper uses SNA to analyze transportation networks and consequently corroborate its effectiveness as a complementary tool for improved transportation planning. To this end, the authors adopted a four-step interrelated research methodology: (1) investigating the connection between the language and concepts of SNA and those of transportation systems; (2) using different SNA centrality measures in the transportation context; (3) using SNA in two case studies in Mississippi; and (4) analyzing the results of the case studies and drawing conclusions. The SNA approach was able to easily and quickly determine the most critical intersections in the investigated transportation networks. These results were in alignment with Mississippi Department of Transportation (MDOT 2014) traffic studies. Using SNA, the research also demonstrated that the performance of central intersections drives the overall performance of the area roadway network. Accordingly, SNA is believed to be an effective and innovative tool in transportation analysis. Using it as an initial analysis step to identify critical areas will assist decision makers in better focusing their more detailed analyses using validated traditional methods in such areas only compared with the entire network. This will significantly decrease the invested resources in transportation planning and will create a more integrated and holistic perspective for evaluating transportation networks.
    publisherAmerican Society of Civil Engineers
    titleSocial Network Analysis Approach for Improved Transportation Planning
    typeJournal Paper
    journal volume23
    journal issue2
    journal titleJournal of Infrastructure Systems
    identifier doi10.1061/(ASCE)IS.1943-555X.0000331
    treeJournal of Infrastructure Systems:;2017:;Volume ( 023 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian