Bridging digital and sustainable supply chains: insights from a podcast analysis Article

Seuring, Stefan, Neuberger, Jannik, Qazi, Sharfah Ahmad et al. (2026). Bridging digital and sustainable supply chains: insights from a podcast analysis . International Journal of Physical Distribution and Logistics Management, 1-27. 10.1108/ijpdlm-05-2025-0256

cited authors

  • Seuring, Stefan; Neuberger, Jannik; Qazi, Sharfah Ahmad; Schilling, Lara; Patrucco, Andrea S

authors

abstract

  • Purpose The growing complexity of global supply chains and mounting sustainability pressures have increased interest in digital technologies (DTs) as enablers of sustainable supply chain management (SSCM). While conceptual research has outlined the potential of DTs, empirical evidence on how they are applied in practice to achieve economic, environmental and social sustainability outcomes remains limited. Design/methodology/approach This study analyzes 52 episodes of the “sustainable supply chain” podcast, featuring interviews with industry experts. A qualitative content analysis, combining keyword-based and manual coding with contingency analysis, is used to identify how four DTs − artificial intelligence (AI), Internet of Things (IoT), blockchain technology (BT) and cloud services (CS) − enable SSCM practices and related sustainability outcomes. A short practitioner resonance survey was added as a supplementary validation step. Findings The results show that DTs contribute to sustainability primarily through specific SSCM practices, especially sustainable risk management, collaboration and proactivity. AI supports predictive analytics, digital twins and decision-making to enable proactive, sustainable risk management. Blockchain strengthens compliance and accountability through secure traceability. IoT enables end-to-end visibility, automated tracking, and lifecycle monitoring, while cloud services facilitate real-time data sharing and collaboration. Across the cases discussed, DT-enabled SSCM practices are associated with improvements on all three sustainability dimensions, with social outcomes emerging as a central outcome in the contingency analysis. Research limitations/implications The podcast data is publicly available and primarily presents positive examples of DT use, limiting the analysis of unintended or negative consequences. The study therefore complements, but does not replace, more critical examinations of the “dark side” of digitalization and points to open questions regarding trade-offs and rebound effects. Practical implications The study offers actionable insights for supply chain managers on aligning digital transformation with sustainability outcomes. It emphasizes the importance of embedding data and systems capabilities, clarifies the distinct roles of AI, IoT, BT and cloud services, and embeds these technologies within well-defined SSCM practices to improve outcomes across the triple bottom line. Social implications The findings suggest that DT-enabled SSCM practices can support social outcomes by improving visibility, ensuring safer work allocation and strengthening monitoring of labor-related risks. Because the podcast material primarily presents positive accounts, these social implications warrant further research across settings involving workers, suppliers and other affected stakeholders. Originality/value The study extends existing DT-SSCM frameworks by empirically mapping how distinct DTs support specific SSCM practices and sustainability outcomes, using podcast interviews as a novel secondary qualitative data source. It also highlights the role of social sustainability in DT-enabled SSCM and identifies practice-level levers that can inform both research and managerial action.

publication date

  • July 30, 2026

webpage

published in

Digital Object Identifier (DOI)

publisher

  • Emerald

start page

  • 1

end page

  • 27