Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study

Background: Supply Chain partners often find themselves in rather helpless positions, unable to improve their firm’s performance and profitability because their partners although willing to share production information do not fully collaborate in tackling customer order variations as they don’t seem...

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Autores principales:	Balaji Janamanchi, James R. Burns
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2016
Materias:	supply chain performance metrics cpfr optimization systems dynamics simulation modeling Business HF5001-6182 Management. Industrial management HD28-70
Acceso en línea:	https://doaj.org/article/ccef2a92e8f54bb8b6430db134a1c539
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spelling	oai:doaj.org-article:ccef2a92e8f54bb8b6430db134a1c5392021-12-02T14:07:31ZPerformance metric optimization advocates CPFR in supply chains: A system dynamics model based study2331-197510.1080/23311975.2016.1139440https://doaj.org/article/ccef2a92e8f54bb8b6430db134a1c5392016-12-01T00:00:00Zhttp://dx.doi.org/10.1080/23311975.2016.1139440https://doaj.org/toc/2331-1975Background: Supply Chain partners often find themselves in rather helpless positions, unable to improve their firm’s performance and profitability because their partners although willing to share production information do not fully collaborate in tackling customer order variations as they don’t seem to appreciate the benefits of such collaboration. Methods: We use a two-player (supplier-manufacturer) System Dynamics model to study the dynamics to assess the impact and usefulness of supply chain partner collaboration on the supply chain performance measures. Results: Simulation results of supply chain metrics under varied customer order patterns viz., basecase, random normal, random uniform, random upwardtrend, and random downwardtrend under (a) basecase, (b) independent optimization by manufacturer, and (c) collaborative optimization by manufacturer and supplier, are obtained to contrast them to develop useful insights. Conclusions: Focus on obtaining improved inventory turns with optimization techniques provides some viable options to managers and makes a strong case for increased collaborative planning forecasting and replenishment (CPFR) in supply chains. Despite the differences in the inventory management practices that it was contrasted with, CPFR has proven to be beneficial in a supply chain environment for all SC partners.Balaji JanamanchiJames R. BurnsTaylor & Francis Grouparticlesupply chain performance metricscpfroptimizationsystems dynamicssimulation modelingBusinessHF5001-6182Management. Industrial managementHD28-70ENCogent Business & Management, Vol 3, Iss 1 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	supply chain performance metrics cpfr optimization systems dynamics simulation modeling Business HF5001-6182 Management. Industrial management HD28-70
spellingShingle	supply chain performance metrics cpfr optimization systems dynamics simulation modeling Business HF5001-6182 Management. Industrial management HD28-70 Balaji Janamanchi James R. Burns Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study
description	Background: Supply Chain partners often find themselves in rather helpless positions, unable to improve their firm’s performance and profitability because their partners although willing to share production information do not fully collaborate in tackling customer order variations as they don’t seem to appreciate the benefits of such collaboration. Methods: We use a two-player (supplier-manufacturer) System Dynamics model to study the dynamics to assess the impact and usefulness of supply chain partner collaboration on the supply chain performance measures. Results: Simulation results of supply chain metrics under varied customer order patterns viz., basecase, random normal, random uniform, random upwardtrend, and random downwardtrend under (a) basecase, (b) independent optimization by manufacturer, and (c) collaborative optimization by manufacturer and supplier, are obtained to contrast them to develop useful insights. Conclusions: Focus on obtaining improved inventory turns with optimization techniques provides some viable options to managers and makes a strong case for increased collaborative planning forecasting and replenishment (CPFR) in supply chains. Despite the differences in the inventory management practices that it was contrasted with, CPFR has proven to be beneficial in a supply chain environment for all SC partners.
format	article
author	Balaji Janamanchi James R. Burns
author_facet	Balaji Janamanchi James R. Burns
author_sort	Balaji Janamanchi
title	Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study
title_short	Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study
title_full	Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study
title_fullStr	Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study
title_full_unstemmed	Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study
title_sort	performance metric optimization advocates cpfr in supply chains: a system dynamics model based study
publisher	Taylor & Francis Group
publishDate	2016
url	https://doaj.org/article/ccef2a92e8f54bb8b6430db134a1c539
work_keys_str_mv	AT balajijanamanchi performancemetricoptimizationadvocatescpfrinsupplychainsasystemdynamicsmodelbasedstudy AT jamesrburns performancemetricoptimizationadvocatescpfrinsupplychainsasystemdynamicsmodelbasedstudy
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Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study

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