Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships

AbstractThe paper’s main aim is to analyze five constructs of organizational culture, AI-supported leadership, AI-supported appropriate training of employees, teams’ effective performance, and employee engagement, and their relationship through the prism of artificial intelligence on a sample of lar...

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Main Authors: Maja Rožman, Polona Tominc, Borut Milfelner
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Cogent Business & Management
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/23311975.2023.2248732
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author Maja Rožman
Polona Tominc
Borut Milfelner
author_facet Maja Rožman
Polona Tominc
Borut Milfelner
author_sort Maja Rožman
collection DOAJ
description AbstractThe paper’s main aim is to analyze five constructs of organizational culture, AI-supported leadership, AI-supported appropriate training of employees, teams’ effective performance, and employee engagement, and their relationship through the prism of artificial intelligence on a sample of large and medium-sized Slovenian companies. The second aim of the paper is to test the proposed model with two different statistical techniques in the scope of structural equation modeling (SEM) that enable us to assess linear (PLS-SEM) and non-linear relationships (CB-SEM) among the constructs. The empirical research included 437 medium-sized and large Slovenian companies. From each company, a CEO or owner participated in our research. The findings of the research with both techniques show that organizational culture had no impact on AI-supported appropriate training of employees and was not significant as well as that organizational culture had an impact on AI-supported leadership. The impact of AI-supported leadership on AI-supported appropriate training of employees were supported only for the PLS-SEM model. The impact of AI-supported leadership for employees on teams was positive. Contrary to that, the impact of AI-supported leadership for business solutions on teams was non-significant. In both cases, AI-supported appropriate training of employees’ impact on teams was strong and positive. Also, employee engagement impact on teams was positive and statistically significant with PLS-SEM and CB-SEM methods. The research yields important implications for companies seeking to integrate artificial intelligence effectively in their operations. It emphasizes the critical role of AI-supported leadership in driving positive outcomes, such as improved employee training and enhanced team effectiveness. Companies should focus on developing leaders who can leverage AI tools to foster a skilled and engaged workforce. By adopting data-driven decision-making processes and incorporating insights from structural equation modeling, organizations can develop effective AI integration strategies. These provide valuable guidance for enhancing human resource management practices and achieving successful AI adoption across companies. The findings contribute to the formation of new views in the field of artificial intelligence implementation in the companies and show companies a broader picture of which aspects of human resource management need to be improved.
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spelling doaj.art-fb0d3b19178043548d19791a76ac3f582024-03-12T08:30:26ZengTaylor & Francis GroupCogent Business & Management2331-19752023-12-0110210.1080/23311975.2023.2248732Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationshipsMaja Rožman0Polona Tominc1Borut Milfelner2Faculty of Economics and Business, University of Maribor, Maribor, SloveniaFaculty of Economics and Business, University of Maribor, Maribor, SloveniaFaculty of Economics and Business, University of Maribor, Maribor, SloveniaAbstractThe paper’s main aim is to analyze five constructs of organizational culture, AI-supported leadership, AI-supported appropriate training of employees, teams’ effective performance, and employee engagement, and their relationship through the prism of artificial intelligence on a sample of large and medium-sized Slovenian companies. The second aim of the paper is to test the proposed model with two different statistical techniques in the scope of structural equation modeling (SEM) that enable us to assess linear (PLS-SEM) and non-linear relationships (CB-SEM) among the constructs. The empirical research included 437 medium-sized and large Slovenian companies. From each company, a CEO or owner participated in our research. The findings of the research with both techniques show that organizational culture had no impact on AI-supported appropriate training of employees and was not significant as well as that organizational culture had an impact on AI-supported leadership. The impact of AI-supported leadership on AI-supported appropriate training of employees were supported only for the PLS-SEM model. The impact of AI-supported leadership for employees on teams was positive. Contrary to that, the impact of AI-supported leadership for business solutions on teams was non-significant. In both cases, AI-supported appropriate training of employees’ impact on teams was strong and positive. Also, employee engagement impact on teams was positive and statistically significant with PLS-SEM and CB-SEM methods. The research yields important implications for companies seeking to integrate artificial intelligence effectively in their operations. It emphasizes the critical role of AI-supported leadership in driving positive outcomes, such as improved employee training and enhanced team effectiveness. Companies should focus on developing leaders who can leverage AI tools to foster a skilled and engaged workforce. By adopting data-driven decision-making processes and incorporating insights from structural equation modeling, organizations can develop effective AI integration strategies. These provide valuable guidance for enhancing human resource management practices and achieving successful AI adoption across companies. The findings contribute to the formation of new views in the field of artificial intelligence implementation in the companies and show companies a broader picture of which aspects of human resource management need to be improved.https://www.tandfonline.com/doi/10.1080/23311975.2023.2248732leadershiporganizational cultureemployee engagementartificial intelligentC1C12
spellingShingle Maja Rožman
Polona Tominc
Borut Milfelner
Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships
Cogent Business & Management
leadership
organizational culture
employee engagement
artificial intelligent
C1
C12
title Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships
title_full Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships
title_fullStr Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships
title_full_unstemmed Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships
title_short Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships
title_sort maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees testing linear and non linear relationships
topic leadership
organizational culture
employee engagement
artificial intelligent
C1
C12
url https://www.tandfonline.com/doi/10.1080/23311975.2023.2248732
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AT polonatominc maximizingemployeeengagementthroughartificialintelligentorganizationalcultureinthecontextofleadershipandtrainingofemployeestestinglinearandnonlinearrelationships
AT borutmilfelner maximizingemployeeengagementthroughartificialintelligentorganizationalcultureinthecontextofleadershipandtrainingofemployeestestinglinearandnonlinearrelationships