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<p>This study examines the strategic integration of digitalization, Industry 4.0 technologies, and sustainability within an industrial context. Drawing on an in-depth single-case study of a multinational manufacturing firm, we investigate how digital tools such as artificial intelligence (AI), big data analytics (BDA), the Internet of Things (IoT), and hybrid infrastructures both enable and constrain sustainability objectives. The findings reveal practical mechanisms for operationalizing sustainability, including data-driven decision-making, IoT-enabled traceability, and circular design integration, while also highlighting tensions such as fragmented data systems, the environmental footprint of digital infrastructures, and ethical challenges associated with AI use. The study further identifies competency gaps and organizational barriers influencing Industry 4.0 adoption, underscoring the importance of continuous learning and stakeholder engagement. Theoretically, the research extends the “digitainability” framework by demonstrating how contextual factors, governance mechanisms, and organizational learning shape the interplay between digitalization and sustainability. Practically, the study provides actionable recommendations for managers and policymakers to promote responsible, circular, and energy-efficient digital transformation.</p>

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Strategic Integration Of Digitalization, Industry 4.0 And Sustainability: Enablers, Constraints, And Organizational Capabilities In A Multinational Company

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月23日

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  • Ville-Veikko Piispanen,
  • Panu Hentunen

摘要

This study examines the strategic integration of digitalization, Industry 4.0 technologies, and sustainability within an industrial context. Drawing on an in-depth single-case study of a multinational manufacturing firm, we investigate how digital tools such as artificial intelligence (AI), big data analytics (BDA), the Internet of Things (IoT), and hybrid infrastructures both enable and constrain sustainability objectives. The findings reveal practical mechanisms for operationalizing sustainability, including data-driven decision-making, IoT-enabled traceability, and circular design integration, while also highlighting tensions such as fragmented data systems, the environmental footprint of digital infrastructures, and ethical challenges associated with AI use. The study further identifies competency gaps and organizational barriers influencing Industry 4.0 adoption, underscoring the importance of continuous learning and stakeholder engagement. Theoretically, the research extends the “digitainability” framework by demonstrating how contextual factors, governance mechanisms, and organizational learning shape the interplay between digitalization and sustainability. Practically, the study provides actionable recommendations for managers and policymakers to promote responsible, circular, and energy-efficient digital transformation.