Unravelling the Digital Sustainability Myth

Xiao Hu et al.

Journal of Organizational and End User Computing2026https://doi.org/10.4018/joeuc.398388article
AJG 1ABDC B
Weight
0.50

Abstract

The study provides novel empirical evidence from the GCC on how smart supply chains foster sustainable supply chain performance, emphasizing the role of green innovation and circular economy practices. Grounded in the resource-based view and circular economy theory, the authors analyze survey data from 312 multinational enterprises. Findings reveal that mere adoption of smart supply chain does not guarantee sustainable supply chain performance, underscoring the limits of smart supply chain in emerging markets. On the contrary, findings indicate that SSC promotes green innovation by enabling MNEs' visibility, predictive analytics, and collaboration, which in turn drives circular economy practices by enhancing firms' levels of eco-design, waste valorization, and closed-loop flows. Circular economy practices, being the most potent driver of sustainable supply chain performance, serve as the critical enabling mechanism that translates digitalization and innovation capacities into measurable sustainable supply chain performance.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.4018/joeuc.398388

Or copy a formatted citation

@article{xiao2026,
  title        = {{Unravelling the Digital Sustainability Myth}},
  author       = {Xiao Hu et al.},
  journal      = {Journal of Organizational and End User Computing},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.4018/joeuc.398388},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Unravelling the Digital Sustainability Myth

Flags are reviewed by the Arbiter methodology team within 5 business days.


Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.