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Entrepreneurship and Sustainability Issues Open access
Journal Impact FactorTM (2025) 1.5 Q3
Journal Citation IndicatorTM (2025) 0.25 Q4
Received: 2025-01-11  |  Accepted: 2025-04-14  |  Published: 2025-06-30

Title

Information technology / artificial intelligence use and labor productivity in firms


Abstract

This study aims to develop conceptual frameworks and propose an appropriate research methodology for analyzing the relationship between information technology (IT) and artificial intelligence (AI) use and labor productivity in firms, particularly within the context of Latvian ones. Drawing from a comprehensive literature review, it identifies key theoretical models, including the Technology Acceptance Model, Diffusion of Innovations, Resource-Based View, and Socio-Technical Systems Theory, as foundational for understanding IT/AI use in firms and its effects on productivity. The study also proposes a hybrid research methodology combining quantitative causal inference techniques (such as panel data regressions, difference-in-differences, instrumental variable regressions, and Stochastic Frontier Analysis) with qualitative approaches (including case studies, expert interviews, and content analysis) to capture both the measurable impacts and organizational dynamics of IT/AI use. Furthermore, it outlines how advanced tools like machine learning models and Bayesian networks can model complex interdependencies. The conceptual framework integrates theoretical insights with empirical indicators from Latvian official statistics, illustrating how IT/AI contributes to productivity via automation, augmentation, and labor reallocation. The study concludes by identifying limitations (such as its conceptual focus and country-specific scope) and recommends future empirical studies that apply the proposed framework across sectors and regions using firm-level data to validate and expand upon its findings.


Keywords

information technology (IT), Artificial Intelligence (AI), enterprises, labor productivity, conceptual framework, correlation vs. causality, research methodology


JEL classifications

O33 , D24 , L23 , J24 , C81


URI

http://jssidoi.org/jesi/article/1311


DOI


Pages

232-250


Funding

The article has been developed and funded within the Daugavpils University’s (Latvia) research project “Using Information Technology and Artificial Intelligence to Increase Labor Productivity in Enterprises of Latvian Regions”, Nr. 14-95/2025/4.

This is an open access issue and all published articles are licensed under a
Creative Commons Attribution 4.0 International License

Authors

Čižo, Edmunds
Daugavpils University, Daugavpils, Latvia https://du.lv
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Komarova, Vera
Daugavpils University, Daugavpils, Latvia https://du.lv
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Kokarēviča, Anita
Riga Stradins University, Riga, Latvia https://www.rsu.lv
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Kudiņš, Jānis
Daugavpils University, Daugavpils, Latvia https://du.lv
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Ruža, Oksana
Daugavpils University, Daugavpils, Latvia https://du.lv
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Fedorova, Elena
Daugavpils University, Daugavpils, Latvia https://du.lv
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Journal title

Entrepreneurship and Sustainability Issues

Volume

12


Number

4


Issue date

June 2025


Issue DOI


ISSN

ISSN 2345-0282 (online)


Publisher

VšĮ Entrepreneurship and Sustainability Center, Vilnius, Lithuania

Cited

Google Scholar

Article views & downloads

HTML views: 1950  |  PDF downloads: 2186

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