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Title:Artificial-intelligence-supported reduction of employees’ workload to increase the company’s performance in today’s VUCA environment
Authors:ID Rožman, Maja (Author)
ID Oreški, Dijana (Author)
ID Tominc, Polona (Author)
Files:.pdf Rozman-2023-Artificial-Intelligence-Supported.pdf (716,50 KB)
MD5: 4EB09D19324B5647ECB22F8F89EADA0E
 
URL https://doi.org/10.3390/su15065019
 
Language:English
Work type:Scientific work
Typology:1.01 - Original Scientific Article
Organization:EPF - Faculty of Business and Economics
Abstract:This paper aims to develop a multidimensional model of AI-supported employee workload reduction to increase company performance in today's VUCA environment. Multidimensional constructs of the model include several aspects of artificial intelligence related to human resource management: AI-supported organizational culture, AI-supported leadership, AI-supported appropriate training and development of employees, employees' perceived reduction of their workload by AI, employee engagement, and company's performance. The main survey involved 317 medium-sized and large Slovenian companies. Structural equation modeling was used to test the hypotheses. The results show that three multidimensional constructs (AI-supported organizational culture, AI-supported leadership, and AI-supported appropriate training and development of employees) have a statistically significant positive effect on employees' perceived reduction of their workload by AI. In addition, employees' perceived reduced workload by AI has a statistically significant positive effect on employee engagement. The results show that employee engagement has a statistically significant positive effect on company performance. The concept of engagement is based on the fact that the development and growth of the company cannot be achieved by increasing the number of employees or by adding capital; the added value comes primarily from increased productivity, which is a result of the innovative ability of employees and their work engagement, which improve the company's performance. The results will significantly contribute to creating new views in the field of artificial intelligence and adopting important decisions in creating working conditions for employees in today's rapidly changing work environment.
Keywords:artificial intelligence, leadership, employee engagement, company performance
Publication status:Published
Publication version:Version of Record
Submitted for review:15.02.2023
Article acceptance date:10.03.2023
Publication date:12.03.2023
Publisher:MDPI
Year of publishing:2023
Number of pages:Str. 1-21
Numbering:Letn. 15, št. 6, št. članka 5019
PID:20.500.12556/DKUM-86981-1d056245-bb09-d759-1483-01af174e21c4 New window
UDC:331.1
ISSN on article:2071-1050
COBISS.SI-ID:145075715 New window
DOI:10.3390/su15065019 New window
Publication date in DKUM:02.02.2024
Views:604
Downloads:291
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Sustainability
Shortened title:Sustainability
Publisher:MDPI
ISSN:2071-1050
COBISS.SI-ID:5324897 New window

Document is financed by a project

Funder:ARRS - Slovenian Research Agency
Project number:P5-0023
Name:Podjetništvo za inovativno družbo

Funder:HRZZ - Croatian Science Foundation
Project number:UIP-2020-02-6312
Name:SIMON: Intelligent system for automatic selection of machine learning algorithms in social sciences

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:12.03.2023

Secondary language

Language:Slovenian
Keywords:umetna inteligenca, vodenje, zavzetost zaposlenih, uspešnost podjetja


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