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    Modeling Sustainability Discourse in the Construction Industry: A Deep-Learning Approach

    Source: Journal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 004::page 04026026-1
    Author:
    Sadick, Abdul-Manan
    ,
    Hasan, Abid
    ,
    Ahiaga-Dagbui, Dominic Doe
    DOI: 10.1061/JCEMD4.COENG-16205
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThe construction industry generates 13% of global gross domestic product; however, it accounts for one-third of global greenhouse gas emissions, creating an urgent need to align industry practices with sustainable development goals (SDGs). This ...Practical ApplicationsThe construction industry plays a vital role in shaping our built environment. However, its activities can have significant social, economic, and environmental impacts. It is essential to align construction practices with the United ...
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      Modeling Sustainability Discourse in the Construction Industry: A Deep-Learning Approach

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314667
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    contributor authorSadick, Abdul-Manan
    contributor authorHasan, Abid
    contributor authorAhiaga-Dagbui, Dominic Doe
    date accessioned2026-08-20T21:34:15Z
    date available2026-08-20T21:34:15Z
    date copyright2026/02/05
    date issued2026
    identifier otherJCEMD4.COENG-16205.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314667
    description abstractAbstractThe construction industry generates 13% of global gross domestic product; however, it accounts for one-third of global greenhouse gas emissions, creating an urgent need to align industry practices with sustainable development goals (SDGs). This ...Practical ApplicationsThe construction industry plays a vital role in shaping our built environment. However, its activities can have significant social, economic, and environmental impacts. It is essential to align construction practices with the United ...
    publisherAmerican Society of Civil Engineers
    titleModeling Sustainability Discourse in the Construction Industry: A Deep-Learning Approach
    typeJournal Article
    journal volume152
    journal issue4
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/JCEMD4.COENG-16205
    journal fristpage04026026-1
    journal lastpage04026026-23
    page23
    treeJournal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 004
    contenttypeFulltext
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