Three essays on people analytics using big data and artificial intelligence빅데이터와 인공지능 기반한 피플 애널리틱스에 관한 연구

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dc.contributor.advisorCho, Daegon-
dc.contributor.advisor조대곤-
dc.contributor.authorJeon, Chihong-
dc.date.accessioned2023-06-21T19:33:05Z-
dc.date.available2023-06-21T19:33:05Z-
dc.date.issued2022-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=996542&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/307813-
dc.description학위논문(박사) - 한국과학기술원 : 경영공학부, 2022.2,[iv, 84 p. :]-
dc.description.abstractInterest in people analytics has been growing as people data sources expand, people data values increase, and more HR tech vendors offer analytics and reporting. This thesis aims to provide theoretical contributions and actionable implications by applying people analytics using big data and artificial intelligence to peer assessment, developmental feedback, and AI recruiting process. To do this, the first study examines how direct and transparent communications via the reply and the use of carbon copy (cc) measured by email big data analysis influences the perceptions in the context of peer assessment, respectively. The second study examines how specificity and quality of developmental feedback, measured by a range of state-of-the-art machine learning techniques, influence intended effort. The third study examines the difference in the predictive ability of two likeability scores on job interview performance: automated video interview likeability assessments developed based on labeled data by HR professionals and the current employees’ video interview likeability assessments based on asynchronous video interviews.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.titleThree essays on people analytics using big data and artificial intelligence-
dc.title.alternative빅데이터와 인공지능 기반한 피플 애널리틱스에 관한 연구-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :경영공학부,-
dc.contributor.alternativeauthor전치홍-
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MT-Theses_Ph.D.(박사논문)
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