Managing the bullwhip effect in multi-echelon supply chains

This editorial article presents the bullwhip effect which is one of the major problems faced by supply chain management. The bullwhip effect represents the demand variability amplification as demand information travels upstream in the supply chain. The bullwhip effect research has been attempting to prove its existence, identify its causes, quantify its magnitude and propose mitigation and avoidance solutions. Previous research has relied on different modeling approaches to quantify the bullwhip effect and to investigate the proposed mitigation/avoidance solutions. Extensive research has shown that smoothing replenishment rules and collaboration in supply chain are the most powerful approaches to counteract the bullwhip effect. The objective of this article is to highlight the bullwhip effect avoidance approaches with providing some interesting directions for future research

Overview and classification of coordination contracts within forward and reverse supply chains

Among coordination mechanisms, contracts are valuable tools used in both theory and practice to coordinate various supply chains. The focus of this paper is to present an overview of contracts and a classification of coordination contracts and contracting literature in the form of classification schemes. The two criteria used for contract classification, as resulted from contracting literature, are transfer payment contractual incentives and inventory risk sharing. The overview classification of the existing literature has as criteria the level of detail used in designing the coordination models with applicability on the forward and reverse supply chains.Coordination contracts; forward supply chain; reverse supply chain

Information Sharing for improved Supply Chain Collaboration – Simulation Analysis

Collaboration among consumer good’s manufacturer and retailers is vital in order to elevate their performance. Such mutual cooperation’s, focusing beyond day to day business and transforming from a contract-based relationship to a value-based relationship is well received in the industries. Further coupling of information sharing with the collaboration is valued as an effective forward step. The advent of technologies naturally supports information sharing across the supply chain. Satisfying consumers demand is the main goal of any supply chain, so studying supply chain behaviour with demand as a shared information, makes it more beneficial. This thesis analyses demand information sharing in a two-stage supply chain. Three different collaboration scenarios (None, Partial and Full) are simulated using Discrete Event Simulation and their impact on supply chain costs analyzed. Arena software is used to simulate the inventory control scenarios. The test simulation results show that the total system costs decrease with the increase in the level of information sharing. There is 7% cost improvement when the information is partially shared and 43% improvement when the information is fully shared in comparison with the no information sharing scenario. The proposed work can assist decision makers in design and planning of information sharing scenarios between various supply chain partners to gain competitive advantage

Modeling Overstock

Two main problems have been emerging in supply chain management: the increasing pressure to reduce working capital and the growing variety of products. Most of the popular indicators have been developed based on a controlled environment. A new indicator is now proposed, based on the uncertainty of the demand, the flexibility of the supply chains, the evolution of the products lifecycle and the fulfillment of a required service level. The model to support the indicator will be developed within the real options approach.overstock, stock management, real options

Editorial - Evolving Trends in Supply Chain Management: Complexity, New Technologies, and Innovative Methodological Approaches

Ministerio de Ciencia e Innovación DPI201680750

Investigating the impact of networking capability on firm innovation performance:using the resource-action-performance framework

The author's final peer reviewed version can be found by following the URI link. The Publisher's final version can be found by following the DOI link.Purpose The experience of successful firms has proven that one of the most important ways to promote co-learning and create successful networked innovations is the proper application of inter-organizational knowledge mechanisms. This study aims to use a resource-action-performance framework to open the black box on the relationship between networking capability and innovation performance. The research population embraces companies in the Iranian automotive industry. Design/methodology/approach Due to the latent nature of the variables studied, the required data are collected through a web-based cross-sectional survey. First, the content validity of the measurement tool is evaluated by experts. Then, a pre-test is conducted to assess the reliability of the measurement tool. All data are gathered by the Iranian Vehicle Manufacturers Association (IVMA) and Iranian Auto Parts Manufacturers Association (IAPMA) samples. The power analysis method and G*Power software are used to determine the sample size. Moreover, SmartPLS 3 and IBM SPSS 25 software are used for data analysis of the conceptual model and relating hypotheses. Findings The results of this study indicated that the relationships between networking capability, inter-organizational knowledge mechanisms and inter-organizational learning result in a self-reinforcing loop, with a marked impact on firm innovation performance. Originality/value Since there is little understanding of the interdependencies of networking capability, inter-organizational knowledge mechanisms, co-learning and their effect on firm innovation performance, most previous research studies have focused on only one or two of the above-mentioned variables. Thus, their cumulative effect has not examined yet. Looking at inter-organizational relationships from a network perspective and knowledge-based view (KBV), and to consider the simultaneous effect of knowledge mechanisms and learning as intermediary actions alongside, to consider the performance effect of the capability-building process, are the main advantages of this research

An enhanced approximation mathematical model inventorying items in a multi-echelon system under a continuous review policy with probabilistic demand and lead-time

An inventory system attempts to balance between overstock and understock to reduce the total cost and achieve customer demand in a timely manner. The inventory system is like a hidden entity in a supply chain, where a large complete network synchronizes a series of interrelated processes for a manufacturer, in order to transform raw materials into final products and distribute them to customers. The optimality of inventory and allocation policies in a supply chain for a cement industry is still unknown for many types of multi-echelon inventory systems. In multi-echelon networks, complexity exists when the inventory issues appear in multiple tiers and whose performances are significantly affected by the demand and lead-time. Hence, the objective of this research is to develop an enhanced approximation mathematical model in a multi-echelon inventory system under a continuous review policy subject to probabilistic demand and lead-time. The probability distribution function of demand during lead-time is established by developing a new Simulation Model of Demand During Lead-Time (SMDDL) using simulation procedures. The model is able to forecast future demand and demand during lead-time. The obtained demand during lead-time is used to develop a Serial Multi-echelon Inventory (SMEI) model by deriving the inventory cost function to compute performance measures of the cement inventory system. Based on the performance measures, a modified distribution multi-echelon inventory (DMEI) model with the First Come First Serve (FCFS) rule (DMEI-FCFS) is derived to determine the best expected waiting time and expected number of retailers in the system based on a mean arrival rate and a mean service rate. This research established five new distribution functions for the demand during lead-time. The distribution functions improve the performance measures, which contribute in reducing the expected waiting time in the system. Overall, the approximation model provides accurate time span to overcome shortage of cement inventory, which in turn fulfil customer satisfaction

OVAP: A strategy to implement partial information sharing among supply chain retailers

This paper analyses the impact on supply chain performance of adopting different strategies to implement partial information sharing among heterogeneous retailers. Supply chains are modelled using a multi-agent systems approach. We find that the strategy adopted to construct the partial information sharing structure (i.e., the retailers who share information) has a significant impact on supply chain performance. We propose a practical strategy, named Order VAriance Prioritization (OVAP), which gives priority to the retailers with higher order variance. OVAP outperforms the worst (i.e. naive) implementation method by 27.2% and 7.8% with respect to the levels of bullwhip and average inventory.Ministerio de Ciencia e Innovación DPI201680750P

The impact of the supply chain structure on bullwhip effect

The aim of this paper is to study how the structural factors of supply chain networks, (i.e. the number of echelons, the number of nodes and the distribution of links) impact on its dynamics performance (i.e. bullwhip effect). To do so, we systematically model multiple structures according to a robust design of experiments and simulate such structures under two different market demand scenarios. The former emulates a stationary condition of the market, while the latter reproduce the extreme volatility and impetuous alteration of the market produced by the current economic recession. Results contribute to the scientific debate on supply chain dynamics by showing how the advocated number of echelons is not the only structural factor that exacerbates the bullwhip effect. In particular, under a sudden shock in market demand, the number of nodes and the divergence of the supply chain network affect the supply chain performance.Ministerio de Economía y Competitividad DPI2013-44461-P/DP