Real-time Demand Forecasting
Real-Time Demand Forecasting is a demand sensing method that continuously assimilates high-frequency, near-instantaneous data streams to dynamically update demand predictions at minimal latency, distinguishing it from traditional forecasting by its emphasis on immediacy, responsiveness, and operational integration in supply chain decision-making.
137
Publications
7.7K
Citations
426
Authors
225
Institutions
Publications per year
2017–2026
69
Parents
137
1–5 of 137
426
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225
Massachusetts Institute of Technology
Cambridge, United States
4 h-index
7 publications
321 citations

University of Exeter
Exeter, United Kingdom
4 h-index
5 publications
437 citations
Lancaster University
Lancaster, United Kingdom
4 h-index
7 publications
820 citations
University of Ferrara
Ferrara, Italy
4 h-index
9 publications
662 citations

Southeast University
Nanjing, China
3 h-index
3 publications
113 citations
Tsinghua University
Beijing, China
3 h-index
7 publications
507 citations

Bangladesh University of Engineering and Technology
Dhaka, Bangladesh
2 h-index
4 publications
134 citations

Istanbul Technical University
Istanbul, Türkiye
2 h-index
2 publications
295 citations
1–8 of 225
12 publications · 786 citations
12
h-index
7 publications · 484 citations
7
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4 publications · 352 citations
4
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4 publications · 105 citations
4
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4 publications · 200 citations
4
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1–5