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Collaborative supply chain: Insights from simulation
被引:9
作者
:
Manoj Hudnurkar
论文数:
0
引用数:
0
h-index:
0
机构:
Symbiosis Centre for Management and Human Resource Development (SCMHRD), Plot No. 15, Rajiv Gandhi Infotech Park, Hinjewadi
Manoj Hudnurkar
Urvashi Rathod
论文数:
0
引用数:
0
h-index:
0
机构:
Symbiosis Centre for Management and Human Resource Development (SCMHRD), Plot No. 15, Rajiv Gandhi Infotech Park, Hinjewadi
Urvashi Rathod
机构
:
[1]
Symbiosis Centre for Management and Human Resource Development (SCMHRD), Plot No. 15, Rajiv Gandhi Infotech Park, Hinjewadi
[2]
Symbiosis Centre for Information Technology (SCIT), Plot 15, Rajiv Gandhi InfoTech Park, Phase-I, Hinjawadi
来源
:
International Journal of System Assurance Engineering and Management
|
2012年
/ 3卷
/ 2期
关键词
:
Collaborative planning forecasting and replenishment (CPFR);
Collaborative supply chain;
Vendor Managed Inventory (VMI);
D O I
:
10.1007/s13198-012-0114-9
中图分类号
:
学科分类号
:
摘要
:
Supply Chain problem caused by the variability in demand is referred to as Bullwhip or Forrester effect. It attributes to increased inventory, poor customer service level and increase in overall supply chain cost. These adversities have been handled reasonably well by Information Technology enabled collaborative supply chains. Two prominent collaborative techniques, namely, Vendor Managed Inventory (VMI) and Collaborative Planning, Forecasting and Replenishment (CPFR) are considered effective in this regard. Despite perceived effectiveness of CPFR, the expected widespread adoption is still missing. An experimental research using beer game has been conducted to study the difference in the performance of traditional supply chain, VMI based Supply Chain and CPFR based Supply Chain in an industrial setting. Results affirms the ability of collaborative supply chain to reduce inventory and total cost of supply chain and achieve high service levels with almost nil backorders One more interesting observation about the human tendency of ignoring scientific tools for averting risks has been noticed. Authors observe that the emphasis on the use of business intelligence for forecasting will facilitate widespread adoption of CPFR. © 2012 The Society for Reliability Engineering.
引用
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页码:122 / 144
页数:22
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