Towards Sustainable Digital Transformation in Industrial Enterprises with a Focus on the Czech Republic

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F26%3A0198582" target="_blank" >RIV/00216305:26510/26:0198582 - isvavai.cz</a>

Výsledek na webu

<a href="https://jssidoi.org/jesi/uploads/articles/50/Bures_Towards_Sustainable_Digital_Transformation_in_Industrial_Enterprises_with_a_Focus_on_the_Czech_Republic.pdf" target="_blank" >https://jssidoi.org/jesi/uploads/articles/50/Bures_Towards_Sustainable_Digital_Transformation_in_Industrial_Enterprises_with_a_Focus_on_the_Czech_Republic.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.9770/j2336895982" target="_blank" >10.9770/j2336895982</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Towards Sustainable Digital Transformation in Industrial Enterprises with a Focus on the Czech Republic

Popis výsledku v původním jazyce

This article presents a comprehensive review of current trends, barriers, and opportunities in sustainable digital transformation within the manufacturing sector, with an emphasis on Central and Eastern Europe. Drawing on a systematic analysis of 85 peer-reviewed studies published between 2020 and 2025, the review identifies the main factors influencing the successful adoption of information systems (IS) and artificial intelligence (AI) in industrial enterprises. The results highlight that the most significant long-term performance and sustainability gains are achieved when technological innovation is combined with the development of digital skills, open organizational culture, and strategic approaches to environmental management. The review further outlines persistent barriers – including human, organizational, and technological challenges – as well as the lack of locally tailored frameworks and empirical evidence for Central and Eastern Europe. By synthesizing these findings, the article provides practical guidance and conceptual clarity for both practitioners and researchers aiming to support effective and sustainable digital transformation in manufacturing.

Název v anglickém jazyce

Towards Sustainable Digital Transformation in Industrial Enterprises with a Focus on the Czech Republic

Popis výsledku anglicky

This article presents a comprehensive review of current trends, barriers, and opportunities in sustainable digital transformation within the manufacturing sector, with an emphasis on Central and Eastern Europe. Drawing on a systematic analysis of 85 peer-reviewed studies published between 2020 and 2025, the review identifies the main factors influencing the successful adoption of information systems (IS) and artificial intelligence (AI) in industrial enterprises. The results highlight that the most significant long-term performance and sustainability gains are achieved when technological innovation is combined with the development of digital skills, open organizational culture, and strategic approaches to environmental management. The review further outlines persistent barriers – including human, organizational, and technological challenges – as well as the lack of locally tailored frameworks and empirical evidence for Central and Eastern Europe. By synthesizing these findings, the article provides practical guidance and conceptual clarity for both practitioners and researchers aiming to support effective and sustainable digital transformation in manufacturing.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

50204 - Business and management

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Entrepreneurship and Sustainability Issues

ISSN

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e-ISSN

2345-0282

Svazek periodika

—

Číslo periodika v rámci svazku

13

Stát vydavatele periodika

LT - Litevská republika

Počet stran výsledku

11

Strana od-do

95-105

Kód UT WoS článku

001645786200005

EID výsledku v databázi Scopus

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