Demand information sharing in supply chains: the impact of lead-time and inventory to backorder cost ratio

2013 ◽  
Vol 12 (3) ◽  
pp. 215
Author(s):  
Ghada A. Deghedi ◽  
Yasser M. Ibrahim
Keyword(s):  
Supply Chains ◽  
Information Sharing ◽  
Lead Time ◽  
Cost Ratio ◽  
Demand Information ◽  
The Impact

Value of Lead Time and Demand Information Sharing in Supply Chains

2013 ◽  
pp. 317-339
Author(s):  
Ali Mehrabi ◽  
Thierry Moyaux ◽  
Armand Baboli
Keyword(s):  
Supply Chains ◽  
Information Sharing ◽  
Lead Time ◽  
Demand Information

scholarly journals Lead Times – Their Behavior and the Impact on Planning and Control in Supply Chains

2017 ◽  
Vol 8 (2) ◽  
pp. 30-40 ◽  
Author(s):  
Peter Nielsen ◽  
Zbigniew Michna ◽  
Brian Bruhn Sørensen ◽  
Ngoc Do Anh Dung
Keyword(s):  
Supply Chains ◽  
Lead Time ◽  
Large Impact ◽  
Lead Times ◽  
Stochastic Nature ◽  
Planning And Control ◽  
And Control ◽  
The Impact ◽  
Independent And Identically Distributed

AbstractLead times and their nature have received limited interest in literature despite their large impact on the performance and the management of supply chains. This paper presents a method and a case implementation of the same, to establish the behavior of real lead times in supply chains. The paper explores the behavior of lead times and illustrates how in one particular case they can and should be considered to be independent and identically distributed (i.i.d.). The conclusion is also that the stochastic nature of the lead times contributes more to lead time demand variance than demand variance.

scholarly journals Simulation Research on Information-Sharing Value of Two-Level Supply Chain

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaheng Zhang ◽  
Zekai Lin ◽  
Lin Xiao
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
Information Sharing ◽  
Chain Model ◽  
Simulation Research ◽  
Incentive Effect ◽  
Actual Evaluation ◽  
Demand Information ◽  
And Performance ◽  
The Impact

In the two-stage supply chain model, the incentive effect to the supplier’s sharing of demand information and performance evaluation and the effect of various parameters on the incentive effect of the supply chain are studied through a multiagent simulation model constructed for the purpose. It is found that the incentive coefficient of demand information-sharing degree, the number of selected suppliers, the order allocation coefficient, and the order proportion are positively related to the incentive effect of demand information sharing. So, the greater the demand information sharing is, the greater the impact of these parameters on the incentive effect is. Based on the demand information sharing, the supplier performance evaluation rules are shared, and when the actual evaluation rules are inconsistent with the supplier’s expectations, the incentive effect is further enhanced. Other parameters do not affect the incentive effect of demand information sharing and performance evaluation rule sharing.

Investigating the impact of inventory inaccuracy on the bullwhip effect in RFID-enabled supply chains using colored petri nets

2019 ◽  
Vol 14 (2) ◽  
pp. 360-384 ◽  
Author(s):  
Maria Drakaki ◽  
Panagiotis Tzionas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Petri Nets ◽  
Information Sharing ◽  
Bullwhip Effect ◽  
Colored Petri Nets ◽  
Content Type ◽  
Multi Stage ◽  
The Impact ◽  
Serial Supply Chains

PurposeInformation distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.Design/methodology/approachA simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.FindingsThe bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.Research limitations/implicationsInformation sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.Originality/valueColored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.

Mobile Consumer Scanning Technology: A Replacement for Interorganizational Information Systems for Demand Information Learning in Supply Chains?

2021 ◽  
Author(s):  
Ye Shi ◽  
Layth Alwan ◽  
Srinivasan Raghunathan ◽  
Yugang Yu ◽  
Xiaohang Yue
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Simulation Analysis ◽  
Mobile Apps ◽  
Interorganizational Information Systems ◽  
Real World Data ◽  
Extensive Simulation ◽  
Mobile Consumer ◽  
Demand Information ◽  
The Impact

Recently, firms in supply chains have begun to deploy popular mobile apps (e.g., WeChat) into their supply chain practices to improve demand visibility. These efforts rely on consumers to scan the products they purchase using these apps, which we refer to as consumer scanning technology (CST). CST can be an alternative to the conventional interorganizational information technology (IOIT) that relies on collaboration between supply chain firms. This paper develops a theoretical model to examine the value of CST to learn supply chain (demand) information and the impact of CST on IOIT. Using an extensive simulation analysis based on real-world data from a manufacturer that has implemented a CST program, we show that the value of CST to a manufacturer can be substantial and provide insights into how market conditions affect the value.

Supply Chain Competition with Information Sharing

2011 ◽  
Vol 486 ◽  
pp. 309-312
Author(s):  
Rong Yao He ◽  
Zhong Kai Xiong ◽  
Yu Xiong
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Information Sharing ◽  
Optimal Pricing ◽  
Market Demand ◽  
Pricing Policy ◽  
Supply Chain Competition ◽  
Demand Information ◽  
Total Profit

Given the case of two competing supply chains each consisting of one manufacturer and one retailer, we explore whether the retailers should share the market demand information they know with their manufacturers when the manufacturers do not know the same specific demand information. We also determine the optimal pricing policy and total profit for the retailers when each chain either shares or does not share market demand information. We find that sharing information is always more profitable for both retailer and supply chain.

scholarly journals Demand Sharing Inaccuracies in Supply Chains: A Simulation Study

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Salvatore Cannella ◽  
Roberto Dominguez ◽  
Jose M. Framinan ◽  
Manfredi Bruccoleri
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Negative Impact ◽  
Positive Impact ◽  
Bullwhip Effect ◽  
Sources Of Information ◽  
Short Delay ◽  
Demand Information ◽  
Demand Variability ◽  
The Impact

We investigate two main sources of information inaccuracies (i.e., errors and delays) in demand information sharing along the supply chain (SC). Firstly, we perform a systematic literature review on inaccuracy in demand information sharing and its impact on supply chain dynamics. Secondly, we model several SC settings using system dynamics and assess the impact of such information inaccuracies on SC performance. More specifically, we study the impact of four factors (i.e., demand error, demand delay, demand variability, and average lead times) using three SC dynamic performance indicators (i.e., bullwhip effect, inventory variability, and average inventory). The results suggest that demand error has a negative impact on SC performance, which is exacerbated by the magnitude of the error and by low demand variability scenarios. In contrast, demand delay produces a nonlinear behavior in the supply chain response (i.e., a short delay may have a negative impact and a long delay may have a positive impact), being influenced by the supply chain configuration.

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