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dc.contributor.authorPaul J. Hickey
dc.contributor.authorAbdolmajid Erfani
dc.contributor.authorQingbin Cui
dc.date.accessioned2022-12-27T20:39:55Z
dc.date.available2022-12-27T20:39:55Z
dc.date.issued2022/11/01
dc.identifier.other(ASCE)ME.1943-5479.0001087.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4287755
dc.description.abstractWill women and men follow distinctively different paths to achieve executive engineering leadership positions in the US architecture, engineering, and construction (AEC) industry? Using Engineering News Record’s (ENR’s) 2019 Top 400 list, this research analyzed LinkedIn profiles for over 2,800 executives to assess career differences between genders. Statistical comparisons of important features, highlighted by number of companies, titles, education, and network size, revealed a significant impact of gender on individual career paths. A key finding was that men ascend to leadership with a single firm throughout their career, outpacing women almost fourfold (37% to 10%). Applying random forest (RF) as an ensemble classifier, researchers successfully predicted profile gender with accuracy of 98.95% for training and 89.53% for testing samples. Collating and categorizing the activities and milestones of individual and collective executives offer insight regarding successful experiences, skills, and choices to reach leadership roles. This creates a roadmap for current and future early and midlevel professionals to model their own vocational journey and accelerate progression up the corporate ladder. From an industry perspective, firms deprive themselves and customers of the proven wide-ranging benefits of diversity.
dc.publisherASCE
dc.titleUse of LinkedIn Data and Machine Learning to Analyze Gender Differences in Construction Career Paths
dc.typeJournal Article
dc.journal.volume38
dc.journal.issue6
dc.journal.titleJournal of Management in Engineering
dc.identifier.doi10.1061/(ASCE)ME.1943-5479.0001087
dc.journal.fristpage04022060
dc.journal.lastpage04022060_13
dc.page13
dc.treeJournal of Management in Engineering:;2022:;Volume ( 038 ):;issue: 006
dc.contenttypeFulltext


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