| Title: | ESG and AI-driven governance transformation in the construction industry : a case-based analysis from Slovenia |
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| Authors: | ID Pavićević, Nora (Author)
ID Belak, Jernej (Author) |
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| Files: |  https://press.um.si/index.php/ump/sl/catalog/book/1126/chapter/1346
 RAZ_Pavicevic_Nora_2026.pdf (472,62 KB)
MD5: 23B45140D68D3BFAA14C5FB7C31B6CE4
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.16 - Independent Scientific Component Part or a Chapter in a Monograph |
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| Organization: | EPF - Faculty of Business and Economics
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| Abstract: | The construction industry is one of the most structurally complex and institutionally regulated sectors, characterized by project-based production, fragmented value chains, and strong exposure to regulatory frameworks. In recent years, this complexity has been intensified by the growing institutionalization of ESG principles and the accelerating diffusion of digital technologies, particularly artificial intelligence. While ESG increasingly functions as an integrated governance architecture shaping strategic decision-making and risk management, the construction sector remains among the least digitalized industries. Although AI-supported tools offer significant potential for performance monitoring, resource optimization, and transparency in reporting, technological adoption alone does not ensure organizational transformation. The presented chapter applies a qualitative case-based research approach focused on a Slovenian construction-sector context. The analysis combines document analysis, ESG governance assessment, and evaluation of AI-supported managerial practices in order to explore the relationship between sustainability transformation and digital governance capabilities. The findings indicate that AI-driven governance mechanisms can significantly support ESG integration, organizational adaptability, and long-term sustainability performance. The study contributes to the growing body of literature on ESG transformation by highlighting the strategic importance of AI-supported governance systems in traditionally conservative industries. |
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| Publication version: | Version of Record |
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| Publication date: | 04.07.2026 |
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| Year of publishing: | 2026 |
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| Number of pages: | Str. 1221-1251 |
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| PID: | 20.500.12556/DKUM-99048  |
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| UDC: | 658.114:004.8 |
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| COBISS.SI-ID: | 286184451 |
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| DOI: | 10.18690/um.epf.7.2026.61 |
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| Publication date in DKUM: | 28.07.2026 |
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| Views: | 205 |
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| Downloads: | 5 |
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| Metadata: |    |
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| Categories: | Misc.
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