Forecasting and Risk Analysis in Supply Chain Management
Application of econometric principles and techniques (VAR-MGARCH) to risk analytics and forecasting in operations management, healthcare, security and other verticals.
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Book chapter |
| Language: | English |
| Published: |
MIT Engineering Systems Division
2008
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/42899 |
| _version_ | 1826202155486281728 |
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| author | Hilmola, Olli-Pekka Graham, Donald Granger, Clive W. J. Datta, Shoumen |
| author2 | Massachusetts Institute of Technology. Auto-ID Laboratory |
| author_facet | Massachusetts Institute of Technology. Auto-ID Laboratory Hilmola, Olli-Pekka Graham, Donald Granger, Clive W. J. Datta, Shoumen |
| author_sort | Hilmola, Olli-Pekka |
| collection | MIT |
| description | Application of econometric principles and techniques (VAR-MGARCH) to risk analytics and forecasting in operations management, healthcare, security and other verticals. |
| first_indexed | 2024-09-23T12:03:23Z |
| format | Book chapter |
| id | mit-1721.1/42899 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2025-03-10T10:21:32Z |
| publishDate | 2008 |
| publisher | MIT Engineering Systems Division |
| record_format | dspace |
| spelling | mit-1721.1/428992025-02-28T18:29:45Z Forecasting and Risk Analysis in Supply Chain Management Confluence of Econometrics with Operations Management Hilmola, Olli-Pekka Graham, Donald Granger, Clive W. J. Datta, Shoumen Massachusetts Institute of Technology. Auto-ID Laboratory Forecasting, SCM, demand amplification, risk management, intelligent decision systems Application of econometric principles and techniques (VAR-MGARCH) to risk analytics and forecasting in operations management, healthcare, security and other verticals. Forecasting is an underestimated field of research in supply chain management. Recently advanced methods are coming into use. Initial results are encouraging, but often require changes in policies for collaboration and transparency. In this paper we explore advanced forecasting tools for decision support in supply chain scenarios and provide preliminary simulation results from their impact on demand amplification. It appears that advanced methods may be useful to predict oscillated demand but their performance is constrained by current structural and operating policies. Improvements to reduce demand amplification, for example, may decrease the risk of out of stock but increase operating cost or risk of excess inventory. MIT Forum for Supply Chain Innovation 2008-11-03T14:16:11Z 2008-11-03T14:16:11Z 2008-10 Book chapter http://hdl.handle.net/1721.1/42899 en MIT ESD Working Paper;esd-wp-2008-20 application/pdf MIT Engineering Systems Division |
| spellingShingle | Forecasting, SCM, demand amplification, risk management, intelligent decision systems Hilmola, Olli-Pekka Graham, Donald Granger, Clive W. J. Datta, Shoumen Forecasting and Risk Analysis in Supply Chain Management |
| title | Forecasting and Risk Analysis in Supply Chain Management |
| title_full | Forecasting and Risk Analysis in Supply Chain Management |
| title_fullStr | Forecasting and Risk Analysis in Supply Chain Management |
| title_full_unstemmed | Forecasting and Risk Analysis in Supply Chain Management |
| title_short | Forecasting and Risk Analysis in Supply Chain Management |
| title_sort | forecasting and risk analysis in supply chain management |
| topic | Forecasting, SCM, demand amplification, risk management, intelligent decision systems |
| url | http://hdl.handle.net/1721.1/42899 |
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