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Optimizing Sustainability in Food Supply Chains Through Strategic Digital Twins Enablers: A Gray Influence Analysis Approach (GINA)

Madhuri Chouhan & Rajendra Sahu

NMIMS Management Review2025https://doi.org/10.1177/09711023251400099article
ABDC C
Weight
0.50

What the paper says

The digitalization of the food supply chain (FSC) is reshaping food production, potentially increasing productivity and reducing food waste. However, it is still being determined whether implementing digital twin technologies in FSC can also prevent or reduce food loss and waste. This research work identified and analyzed the enablers of digital twins in implementing FSC. Very few studies have analyzed the role of digitalization in FSC, and no study was found in the open literature that has analyzed the enablers of the digital FSC to prevent food waste. This investigation employed a novel gray influence analysis (GINA) methodology for the analysis of causal relationships between factors. Using the GINA method, responses may be aggregated cumulatively without information loss. Consequently, the primary advantage of the GINA method is its capacity to execute a causal analysis model while accommodating a vast amount of data. The study has identified 17 enablers that can improve the sustainability of the FSC through the implementation of digital twin technology. After analysis, enablers visibility (ENB5) and collaboration (ENB16) received the first and second positions based on the total influence score. The digitalization of the FSC promotes better collaboration between stakeholders, enhances traceability and visibility, encourages high-quality products, and reduces food waste. This research study is helpful for the researchers, practitioners, and managers working in the field of digitalization of FSC.

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https://doi.org/https://doi.org/10.1177/09711023251400099

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@article{madhuri2025,
  title        = {{Optimizing Sustainability in Food Supply Chains Through Strategic Digital Twins Enablers: A Gray Influence Analysis Approach (GINA)}},
  author       = {Madhuri Chouhan & Rajendra Sahu},
  journal      = {NMIMS Management Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/09711023251400099},
}

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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.