A study on decision-making of food supply chain based on big data
As more and more companies have captured and analyzed huge volumes of data to improve the performance of supply chain, this paper develops a big data harvest model that uses big data as inputs to make more informed production decisions in the food supply chain. By introducing a method of Bayesian ne...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Published: |
Springer
2017
|
| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/40465/ |
| _version_ | 1848796063740198912 |
|---|---|
| author | Ji, Guojun Hu, Limei Tan, Kim Hua |
| author_facet | Ji, Guojun Hu, Limei Tan, Kim Hua |
| author_sort | Ji, Guojun |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | As more and more companies have captured and analyzed huge volumes of data to improve the performance of supply chain, this paper develops a big data harvest model that uses big data as inputs to make more informed production decisions in the food supply chain. By introducing a method of Bayesian network, this paper integrates sample data and finds a cause-and-effect between data to predict market demand. Then the deduction graph model that translates products demand into processes and divides processes into tasks and assets is presented, and an example of how big data in the food supply chain can be combined with Bayesian network and deduction graph model to guide production decision. Our conclusions indicate that the analytical framework has vast potential for supporting support decision making by extracting value from big data. |
| first_indexed | 2025-11-14T19:42:02Z |
| format | Article |
| id | nottingham-40465 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:42:02Z |
| publishDate | 2017 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-404652020-05-04T18:41:15Z https://eprints.nottingham.ac.uk/40465/ A study on decision-making of food supply chain based on big data Ji, Guojun Hu, Limei Tan, Kim Hua As more and more companies have captured and analyzed huge volumes of data to improve the performance of supply chain, this paper develops a big data harvest model that uses big data as inputs to make more informed production decisions in the food supply chain. By introducing a method of Bayesian network, this paper integrates sample data and finds a cause-and-effect between data to predict market demand. Then the deduction graph model that translates products demand into processes and divides processes into tasks and assets is presented, and an example of how big data in the food supply chain can be combined with Bayesian network and deduction graph model to guide production decision. Our conclusions indicate that the analytical framework has vast potential for supporting support decision making by extracting value from big data. Springer 2017-04-07 Article PeerReviewed Ji, Guojun, Hu, Limei and Tan, Kim Hua (2017) A study on decision-making of food supply chain based on big data. Journal of Systems Science and Systems Engineering, 26 (2). pp. 183-198. ISSN 1861-9576 Big data Bayesian network deduction graph model food supply chain http://link.springer.com/article/10.1007%2Fs11518-016-5320-6 doi:10.1007/s11518-016-5320-6 doi:10.1007/s11518-016-5320-6 |
| spellingShingle | Big data Bayesian network deduction graph model food supply chain Ji, Guojun Hu, Limei Tan, Kim Hua A study on decision-making of food supply chain based on big data |
| title | A study on decision-making of food supply chain based on big data |
| title_full | A study on decision-making of food supply chain based on big data |
| title_fullStr | A study on decision-making of food supply chain based on big data |
| title_full_unstemmed | A study on decision-making of food supply chain based on big data |
| title_short | A study on decision-making of food supply chain based on big data |
| title_sort | study on decision-making of food supply chain based on big data |
| topic | Big data Bayesian network deduction graph model food supply chain |
| url | https://eprints.nottingham.ac.uk/40465/ https://eprints.nottingham.ac.uk/40465/ https://eprints.nottingham.ac.uk/40465/ |