Digital Technologies Research and Applications

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Insights into Digital Technologies Sustainability and the Economic Performance of Greek Enterprises

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https://doi.org/10.54963/dtra.v5i3.2244
Challoumis, C., Eriotis, N., & Vasiliou, D. (2026). Insights into Digital Technologies Sustainability and the Economic Performance of Greek Enterprises. Digital Technologies Research and Applications, 5(3), 56–88. https://doi.org/10.54963/dtra.v5i3.2244
Volume 5 Issue 3: September 2026 (In Progress)
Copyright (c) 2026 Constantinos Challoumis, Nikolaos Eriotis, Dimitrios Vasiliou
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Authors

  • Constantinos Challoumis

    Department of Accounting and Finance, Philips University, Nicosia 2090, Cyprus
    Department of Informatics and Computer Engineering, University of West Attica, 12243 Athens, Greece
    Department of Marketing and Communication, Athens University of Economics and Business, 10434 Athens, Greece
    Department of Business Administration, National and Kapodistrian University of Athens, 10559 Athens, Greece
  • Nikolaos Eriotis

    Department of Business Administration, National and Kapodistrian University of Athens, 10559 Athens, Greece
  • Dimitrios Vasiliou

    Department of Business Administration, National and Kapodistrian University of Athens, 10559 Athens, Greece

Received: 5 January 2026; Revised: 3 March 2026; Accepted: 18 March 2026; Published: 8 July 2026

This research examines how specific digital technologies—including artificial intelligence (AI) systems based on machine learning algorithms, data analytics platforms for real-time decision support, cloud computing infrastructures, Internet of Things (IoT) sensor network applications, and digital market platforms—affect the economic performance of Greek enterprises. Rather than treating digitalization as a homogeneous input, the analysis explicitly distinguishes between technology types and their application mechanisms within firms. Market-facing technologies (e-commerce systems and digital marketing platforms) operate primarily through demand expansion and market access, while production- and decision-oriented technologies (AI, machine learning-based analytics, IoT sensor networks, and cloud infrastructures) affect performance through process optimization, resource allocation efficiency, and organizational learning. Using a theory-driven and visualization-based analytical framework grounded in enterprise survey evidence, the study evaluates the association between individual and combined technology adoption and key performance indicators, including output growth, labor productivity, and total factor productivity (TFP). The results indicate that AI and data analytics systems enhance productivity through algorithmic optimization and data-driven decision processes, while IoT applications contribute via real-time monitoring, predictive maintenance, and input efficiency improvements. Cloud computing functions as a general-purpose enabling infrastructure, amplifying the productivity effects of other technologies. Enterprises adopting multiple complementary technologies exhibit significantly stronger performance outcomes than single-technology adopters, with multi-technology integration associated with TFP gains of approximately 15–20% in digitally mature firms. The findings highlight that digital transformation improves economic performance primarily through technology-specific application mechanisms and cross-technology complementarities, rather than through generic digital adoption alone.

Keywords:

Digital Technologies Digital Transformation Enterprise Performance Productivity Total Factor Productivity Economic Growth Greece Firm-Level Analysis

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