Assessing the sustainability of industrial value chains in Europe: a mapping method proposal

Jabier Retegi et al.

Production & Manufacturing Research2025https://doi.org/10.1080/21693277.2024.2448010article
AJG 1
Weight
0.44

What the paper says

Establishing sustainability policies and business strategies involvesmapping environmental, economic, and social factors in an inte-grative way. In the academic literature, environmentally extendedinput-output tables have been employed to analyse the relation-ship between economic flows and their impacts on sustainability.These methodologies require advanced mathematical expertiseand do not easily provide a graphical representation to facilitatetheir interpretation. To fill this gap, this paper develops a uniqueapproach using Power Query that integrates economic, environ-mental, and employment data to create value chain maps. It alsoprovides examples of the insights gained by applying the methodto 12 European countries. The resulting 240 industrial value chainmaps represent 94.41% of the industrial emissions in the surveyedcountries. This novel and comprehensive methodology for map-ping and characterising industrial sustainability in European indus-trial value chains (including Scope 3 emissions) provides valuableknowledge for researchers, business representatives, and policy-makers to design effective sustainable strategies

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https://doi.org/https://doi.org/10.1080/21693277.2024.2448010

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@article{jabier2025,
  title        = {{Assessing the sustainability of industrial value chains in Europe: a mapping method proposal}},
  author       = {Jabier Retegi et al.},
  journal      = {Production & Manufacturing Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/21693277.2024.2448010},
}

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Assessing the sustainability of industrial value chains in Europe: a mapping method proposal

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Evidence weight

0.44

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

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
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.