A framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry

According to the Hamburger effect, food products export industry sector, especially cooked chicken products export to Japan of Thai industry, effort has been spent in the supply chain management (SCM) of internal efficiency, solely aiming at competitiveness survival in terms of cost reduction, bette...

Full description

Saved in:
Bibliographic Details
Main Authors: Pongsak Holimchayachotikul, Nuanlaor Phanruangrong
Format: Book Series
Published: 2018
Subjects:
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84903847403&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/50733
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Chiang Mai University
id th-cmuir.6653943832-50733
record_format dspace
spelling th-cmuir.6653943832-507332018-09-04T04:44:51Z A framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry Pongsak Holimchayachotikul Nuanlaor Phanruangrong Computer Science According to the Hamburger effect, food products export industry sector, especially cooked chicken products export to Japan of Thai industry, effort has been spent in the supply chain management (SCM) of internal efficiency, solely aiming at competitiveness survival in terms of cost reduction, better quality. To meet the customer satisfaction, the company must work towards a right time and volume of demand delivery. Therefore, forecasting technique is the crucial element of SCM. The more understanding how their company use the right forecasting based on information sharing in their SCM context; the more reducing inventory and capacity planning cost increase their company competitiveness. Presently, most of companies, in this sector, do not have a right knowledge to implement the suitable forecasting system to sustain their business; furthermore, they only use top management judgment and some of economical data for forecasting decision making to production. Because the complex, stochastic, dynamic nature and multi-criteria of the logistics operations along the food products exporting to Japan of Thai industry supply chain, the existing time series forecasting approaches cannot provide the information to operate demand from upstream to downstream effectively. The objective of the paper is how to develop a conceptual framework for an innovative and simplified forecasting system implementation for this industry based on data mining including time series factors and causal factors. Then we discuss a methodology to determine appropriated implementation guideline. © Springer-Verlag Berlin Heidelberg 2010. 2018-09-04T04:44:51Z 2018-09-04T04:44:51Z 2010-01-01 Book Series 18675662 2-s2.0-84903847403 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84903847403&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/50733
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
spellingShingle Computer Science
Pongsak Holimchayachotikul
Nuanlaor Phanruangrong
A framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry
description According to the Hamburger effect, food products export industry sector, especially cooked chicken products export to Japan of Thai industry, effort has been spent in the supply chain management (SCM) of internal efficiency, solely aiming at competitiveness survival in terms of cost reduction, better quality. To meet the customer satisfaction, the company must work towards a right time and volume of demand delivery. Therefore, forecasting technique is the crucial element of SCM. The more understanding how their company use the right forecasting based on information sharing in their SCM context; the more reducing inventory and capacity planning cost increase their company competitiveness. Presently, most of companies, in this sector, do not have a right knowledge to implement the suitable forecasting system to sustain their business; furthermore, they only use top management judgment and some of economical data for forecasting decision making to production. Because the complex, stochastic, dynamic nature and multi-criteria of the logistics operations along the food products exporting to Japan of Thai industry supply chain, the existing time series forecasting approaches cannot provide the information to operate demand from upstream to downstream effectively. The objective of the paper is how to develop a conceptual framework for an innovative and simplified forecasting system implementation for this industry based on data mining including time series factors and causal factors. Then we discuss a methodology to determine appropriated implementation guideline. © Springer-Verlag Berlin Heidelberg 2010.
format Book Series
author Pongsak Holimchayachotikul
Nuanlaor Phanruangrong
author_facet Pongsak Holimchayachotikul
Nuanlaor Phanruangrong
author_sort Pongsak Holimchayachotikul
title A framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry
title_short A framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry
title_full A framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry
title_fullStr A framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry
title_full_unstemmed A framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry
title_sort framework for modeling efficient demand forecasting using data mining in supply chain of food products export industry
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84903847403&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/50733
_version_ 1681423643068858368