Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning

Over the past few decades, the study of leadership theory has expanded across various disciplines, delving into the intricacies of human behavior and defining the roles of individuals within organizations. Its primary objective is to identify leaders who play significant roles in the communication f...

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Autores:: Xie, Yunbo
Meisel, Jose D.
Meisel, Carlos A.
Betancourt, Juan Jose
Yan, Jianqi
Bugiolacchi, Roberto

Tipo de recurso:: Article of investigation

Fecha de publicación:: 2024

Institución:: Universidad de Ibagué

Repositorio:: Repositorio Universidad de Ibagué

Idioma:: eng

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dc.title.eng.fl_str_mv	Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning
title	Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning
spellingShingle	Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning Redes Convolucionales de Grafos Inteligencia Artificial Explicable Aprendizaje Automático Automatizado Artificial intelligence Contrastive Learning Economic and social effects Federated learning Graph embeddings
title_short	Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning
title_full	Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning
title_fullStr	Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning
title_full_unstemmed	Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning
title_sort	Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning
dc.creator.fl_str_mv	Xie, Yunbo Meisel, Jose D. Meisel, Carlos A. Betancourt, Juan Jose Yan, Jianqi Bugiolacchi, Roberto
dc.contributor.author.none.fl_str_mv	Xie, Yunbo Meisel, Jose D. Meisel, Carlos A. Betancourt, Juan Jose Yan, Jianqi Bugiolacchi, Roberto
dc.subject.armarc.none.fl_str_mv	Redes Convolucionales de Grafos Inteligencia Artificial Explicable Aprendizaje Automático Automatizado
topic	Redes Convolucionales de Grafos Inteligencia Artificial Explicable Aprendizaje Automático Automatizado Artificial intelligence Contrastive Learning Economic and social effects Federated learning Graph embeddings
dc.subject.proposal.eng.fl_str_mv	Artificial intelligence Contrastive Learning Economic and social effects Federated learning Graph embeddings
description	Over the past few decades, the study of leadership theory has expanded across various disciplines, delving into the intricacies of human behavior and defining the roles of individuals within organizations. Its primary objective is to identify leaders who play significant roles in the communication flow. In addition, behavioral theory posits that leaders can be distinguished based on their daily conduct, while social network analysis provides valuable insights into behavioral patterns. Our study investigates five and six types of social networks frequently observed in different organizations. This study is conducted using datasets we collected from an IT company and public datasets collected from a manufacturing company for the thorough evaluation of prediction performance. We leverage PageRank and effective word embedding techniques to obtain novel features. State-of-the-art performance is obtained using various statistical machine learning methods, graph convolutional networks (GCN), automated machine learning (AutoML), and explainable artificial intelligence (XAI). More specifically, our approach can achieve state-of-the-art performance with an accuracy close to (Formula presented.) for leaders identification with data from projects of different types. This investigation contributes to the establishment of sustainable leadership practices by aiding organizations in retaining their leadership talent.
publishDate	2024
dc.date.issued.none.fl_str_mv	2024-10
dc.date.accessioned.none.fl_str_mv	2025-11-06T19:45:11Z
dc.date.available.none.fl_str_mv	2025-11-06T19:45:11Z
dc.type.none.fl_str_mv	Artículo de revista
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dc.type.content.none.fl_str_mv	Text
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dc.identifier.citation.none.fl_str_mv	Xie, Y.; Meisel, J.D.; Meisel, C.A.; Betancourt, J.J.; Yan, J.; Bugiolacchi, R. Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning. Appl. Sci. 2024, 14, 9461. https://doi.org/10.3390/ app14209461
dc.identifier.doi.none.fl_str_mv	https://doi.org/10.3390/ app14209461
dc.identifier.issn.none.fl_str_mv	20763417
dc.identifier.uri.none.fl_str_mv	https://hdl.handle.net/20.500.12313/5911
dc.identifier.url.none.fl_str_mv	https://www.mdpi.com/2076-3417/14/20/9461
identifier_str_mv	Xie, Y.; Meisel, J.D.; Meisel, C.A.; Betancourt, J.J.; Yan, J.; Bugiolacchi, R. Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning. Appl. Sci. 2024, 14, 9461. https://doi.org/10.3390/ app14209461 20763417
url	https://doi.org/10.3390/ app14209461 https://hdl.handle.net/20.500.12313/5911 https://www.mdpi.com/2076-3417/14/20/9461
dc.language.iso.none.fl_str_mv	eng
language	eng
dc.relation.citationissue.none.fl_str_mv	20
dc.relation.citationvolume.none.fl_str_mv	14
dc.relation.ispartofjournal.none.fl_str_mv	Applied Sciences
dc.relation.references.none.fl_str_mv	Dinh, J.E.; Lord, R.G.; Gardner, W.L.; Meuser, J.D.; Liden, R.C.; Hu, J. Leadership theory and research in the new millennium: Current theoretical trends and changing perspectives. Leadersh. Q. 2014, 25, 36–62 Montalván, S.E.S.; Aguirre, I.P.V.; Sánchez, J.P.P.; Condolo, C.R.Q. Teorías de liderazgo contemporáneo: Análisis de la dinámica relacional. Oikos Rev. Esc. Adm. Econ. 2014, 18, 41–61 Retamozo, M. La teoría política del populismo: Usos y controversias en América Latina en la perspectiva posfundacional. Latinoam. Rev. Estud. Latinoam. 2017, 125–151. Conger, J.A.; Kanungo, R.N. Toward a behavioral theory of charismatic leadership in organizational settings. Acad. Manag. Rev. 1987, 12, 637–647. Chica, C.A.P.; Álvarez, J.C.E.; Zurita, I.N.; Clerque, S.E.M. El Marketing como estrategia de posicionamiento en empresas de servicios. Dominio Cienc. 2019, 5, 784–802. Quezada Torres, C.; Illesca Pretty, M.; Cabezas González, M. 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spelling	Xie, Yunbocc2319ea-7ec8-4d7a-8062-cbe11a79b620-1Meisel, Jose D.fb6ee7e4-d71a-4ad0-ada1-224714cb0696-1Meisel, Carlos A.b8f9ef40-615f-4056-8ff6-ef9a58e64002-1Betancourt, Juan Josecd38a9d5-fe13-4776-b50f-3690cc2b386b-1Yan, Jianqif54a205c-64a4-4978-b5aa-d1c06a8aa21d-1Bugiolacchi, Roberto95058079-325c-4eef-97a0-fb54f31b5bc1-12025-11-06T19:45:11Z2025-11-06T19:45:11Z2024-10Over the past few decades, the study of leadership theory has expanded across various disciplines, delving into the intricacies of human behavior and defining the roles of individuals within organizations. Its primary objective is to identify leaders who play significant roles in the communication flow. In addition, behavioral theory posits that leaders can be distinguished based on their daily conduct, while social network analysis provides valuable insights into behavioral patterns. Our study investigates five and six types of social networks frequently observed in different organizations. This study is conducted using datasets we collected from an IT company and public datasets collected from a manufacturing company for the thorough evaluation of prediction performance. We leverage PageRank and effective word embedding techniques to obtain novel features. State-of-the-art performance is obtained using various statistical machine learning methods, graph convolutional networks (GCN), automated machine learning (AutoML), and explainable artificial intelligence (XAI). More specifically, our approach can achieve state-of-the-art performance with an accuracy close to (Formula presented.) for leaders identification with data from projects of different types. This investigation contributes to the establishment of sustainable leadership practices by aiding organizations in retaining their leadership talent.application/pdfXie, Y.; Meisel, J.D.; Meisel, C.A.; Betancourt, J.J.; Yan, J.; Bugiolacchi, R. 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Intell. 2017, 40, 2935–2947.© 2024 by the authors.info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Atribución 4.0 Internacional (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/Redes Convolucionales de GrafosInteligencia Artificial ExplicableAprendizaje Automático AutomatizadoArtificial intelligenceContrastive LearningEconomic and social effectsFederated learningGraph embeddingsSpotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine LearningArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Textinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPublicationTEXTArtículos.pdf.txtArtículos.pdf.txtExtracted texttext/plain8137https://repositorio.unibague.edu.co/bitstreams/1c0b51e3-5536-4344-95db-d43979e6a32d/download7c8ae4e20c7a4dfea05f4ea364cdc1beMD53ORIGINALArtículos.pdfArtículos.pdfapplication/pdf166057https://repositorio.unibague.edu.co/bitstreams/43a0061d-e0aa-40f6-b7de-890aac22e773/download0e06868f48933e1a63b0a00ddd425a93MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-8134https://repositorio.unibague.edu.co/bitstreams/a886cfcb-b720-4662-a457-d3d8573c6543/download2fa3e590786b9c0f3ceba1b9656b7ac3MD51THUMBNAILArtículos.pdf.jpgArtículos.pdf.jpgIM Thumbnailimage/jpeg22516https://repositorio.unibague.edu.co/bitstreams/01887ac0-c081-4a73-a906-20b4e6aeff37/downloadba389a8f35732dbd55bee42509326669MD5420.500.12313/5911oai:repositorio.unibague.edu.co:20.500.12313/59112025-11-07 03:03:25.982https://creativecommons.org/licenses/by/4.0/© 2024 by the authors.https://repositorio.unibague.edu.coRepositorio Institucional Universidad de Ibaguébdigital@metabiblioteca.comQ3JlYXRpdmUgQ29tbW9ucyBBdHRyaWJ1dGlvbi1Ob25Db21tZXJjaWFsLU5vRGVyaXZhdGl2ZXMgNC4wIEludGVybmF0aW9uYWwgTGljZW5zZQ0KaHR0cHM6Ly9jcmVhdGl2ZWNvbW1vbnMub3JnL2xpY2Vuc2VzL2J5LW5jLW5kLzQuMC8=

Spotting Leaders in Organizations with Graph Convolutional Networks, Explainable Artificial Intelligence, and Automated Machine Learning

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