Decentralized supply chain coordination through auction markets: dynamic lot-sizing in distribution networks

As supply chains become bigger and dynamically structured involving multiple organizations with different interests, it is impossible for a single organization to control a whole supply chain. So, decentralization of decision rights is an inevitable facet of managing modern supply chains. However, controlling in a decentralized mode can fail without appropriate coordination mechanisms. When the agents of a supply chain are not willing to cooperate in terms of information sharing, the whole supply chain can exhibit expensive inefficiencies such as the bullwhip effect. In this paper, we design a trustworthy decentralized coordination mechanism for dynamic lot-sizing in distribution networks, as an effort to motivate information sharing. We design multiple auctions and each auction coordinates the plans of a supplier and its customers by trading the right of managing the supplier's inventory plan. The coordination mechanism makes a reasonable profit and the profit is divided in an agreeable way. Also, the profits are actual because of the capability of supporting a truth-telling environment. Therefore, the designed coordination mechanism is trustworthy in that it guarantees the right benefits to all the agents in return for information sharing.     

A coordination theoretic model for three level supply chains using contracts

Typically, supply chain members are dependent on each other to manage various resources and information. The conflicting objectives and lack of coordination between supply chain members may often cause uncertainties in supply and demand. The basic elements of coordination theory like interdependency, coherency and mutuality may help in effective flow of information and material between the dependent supply chain members. Supply chain contract can be an effective coordination mechanism to motivate all the members to be a part of the entire supply chain. There are different types of supply chain contracts such as buy back and quantity flexibility contracts. Supply chain performance may be substantially improved by properly designing the contracts to share risks and rewards. The objective of this paper is to explore the applicability of coordination elements through an analytical model in three-level (Manufacturer-distributor-retailer) serial supply chains using contracts. The model evaluates the impact of supply chain contracts on various performance measures. The impact of some contract may be on some specific performance measure only, which helps managers to choose the type of contract if there is an objective of improving certain performance measure before hand. In three-level supply chains, the contracts are designed at two distinct interfaces: Manufacturer-distributor and distributor-retailer. The model demonstrates the complexity in evaluating the decision variables of three level supply chains. The proposed model is a novel approach to apply coordination theory at various levels of supply chain. The model also presents how the coordination elements are related to each other in various coordination cases.     

Coordinating supply chain decisions: an optimization model

Coordinating information and material flows are key to effective supply chain management. The complexity of interactions in and the uncertainties surrounding supply chains make such coordination difficult. However, coordination can be realized by optimizing the flows in supply chains with analytical approaches. A mixed integer programming model is presented to support the tactical decisions of ordering, producing and transporting under various conditions of information availability at the loci of decision making. The model is applied to a modified version of MIT's well known Beer Distribution Game. The performance of the modeling approach is contrasted with the results of human decision making under identical conditions and underlines the enormous potential for performance improvement analytical decision support can provide. Several methodological aspects for coping with the difficulties of solving rather large mixed integer models are presented and it is shown that they can contribute significantly in dealing with the inherent computational problems.     

A dynamic system model for proactive control of dynamic events in full-load states of manufacturing chains

Risk management is a major concern in supply chains that have high levels of uncertainty in product demand, manufacturing process or part supply. The uncertainties frequently manifest as dynamic events that pose a threat to interrupting supply chain operation. Depending on the nature and severity of uncertainty, the impact of dynamic events can be distinguished into three categories: deviation, disruption, and disaster. Many studies in literature addressed modelling of deviation events. In this paper, a dynamic system model of supply chains is described which can be applied to managing disruptive events in full-load states of manufacturing chains. An example of disruptive events is given which arises from demand shocks in distribution channel. The procedure to construct full-load production functions of complex manufacturing nodes with internal queuing delay is described. Analytic optimal solution is derived for the dynamic model. Given an unordinary event of demand shock, this model can be used to determine if demand shock can be absorbed by a manufacturing chain and the level of contingent resources that must be synchronously activated in multiple nodes of the chain. This model can be used to reduce what could have been a disruptive event into a deviation event, thus enhancing risk management.     

Decentralised decision-making with information sharing vs. centralised decision-making in supply chains

In recent years, implementing coordination mechanisms in decentralised supply chains to reduce the well-known negative effects of decentralisation, such as the ‘bullwhip effect’, has become a considerable challenge. Furthermore, with the dramatic developments in information and communication technologies, real-time information sharing has become increasingly easier to implement. In this work, we study a mono-product divergent supply chain composed of a supplier, a warehouse, retailers and customers in the context of decentralised and centralised decisions. The main objective of this study is to compare a decentralised supply chain combined with different scenarios of simultaneous upstream and downstream information sharing vs. a centralised supply chain. A mathematical model is developed to compare the logistics costs in the two decision contexts. The experimental results clearly show that the simultaneous sharing of customer demand and supplier-warehouse lead time information in a decentralised supply chain yields nearly equivalent logistics costs as the centralised supply chain context. However, the main beneficiary of the sharing is the warehouse, which receives approximately two-thirds of the benefit. Thus, incentives and revenue sharing contracts should be implemented to motivate and balance the benefits between supply chain partners.     

An entropy-based approach for measuring complexity in supply chains

Today's supply chains are more complex than ever due to globalisation and its effects, especially on logistics activities. Therefore, understanding and managing complexity in supply chains are very popular topics nowadays. Measures for complexity in supply chains contribute to their manageability and controllability. This paper describes an approach to the measurement of complexity in supply chains based on Shannon's information entropy. The new proposed approach gives a formal approach that is able to measure and analyse the supply chain complexity. The main contribution of this study is to extend two formulas (structural and operational complexity) building on Shannon's entropy measure to evaluate the complexity of a supply chain. The aim is to measure complexity associated with information and material flows in the chain. A numerical example is presented to demonstrate the approach.     

Supply chain design and cost analysis through simulation

This paper is grounded on a discrete-event simulation model, reproducing a fast moving consumer goods (FMCG) supply chain, and aims at quantitatively assessing the effects of different supply configurations on the resulting total supply chain costs and bullwhip effect. Specifically, 30 supply chain configurations are examined, stemming from the combination of several supply chain design parameters, namely number of echelons (from 3 to 5), re-order and inventory management policies (EOQ vs. EOI), demand information sharing (absence vs. presence of information sharing mechanisms), demand value (absence vs. presence of demand ‘peak’), responsiveness of supply chain players. For each configuration, the total logistics costs and the resulting demand variance amplification are computed. A subsequent statistical analysis is performed on 20 representative supply chain configurations, with the aim to identify significant single and combined effects of the above parameters on the results observed. From effects analysis, bullwhip effect and costs outcomes, 11 key results are derived, which provide useful insights and suggestions to optimise supply chain design.     

Game Theory Based Decision Coordination Strategy of Agricultural Logistics Service Information System

Under the background of “Internet plus” rapid development, the agricultural logistics industry should apply information technology to every link of the agricultural product logistics industry chain. By making full use of the decision making module of the agricultural logistics information system, we can realize the full sharing of information and data resources, which makes the decision-making scheme of the agricultural logistics information system more optimized. In real economic society, the uncertainty and mismatch between the customer’s logistics service demand and the logistics service capability that the logistics service function provider can provide, that is, when the two information are asymmetric, how to use the third-party contract to coordinate the income and profit distribution of the two, to make the information system decision making more reasonable? This paper mainly studies the coordination scheme of agricultural logistics information system decision making under uncertain output and demand information by introducing the spot market. A joint coordination strategy based on revenue sharing and penalty feedback contracts proposes decentralized decision making based on game theory. Experiments show that the flexible ordering strategy proposed in this paper can reduce the logistics service supply chain’s uncertainty and significantly improve the logistics service supply chain’s overall income level through coordination contracts.     

Fostering emergent resilience: the complex adaptive supply network of disaster relief

The frequency and intensity of disasters continue to increase. Following large-scale and catastrophic disasters, local organisations integrate with other responding organisations to form hastily disaster relief supply chain networks. Such supply networks are infrequently activated in a single location, generate unparalleled uncertainty, change quickly, and are driven by the urgency of saving lives and restoring livelihoods. Unfortunately, even where sound supply chain management practices are used, supply networks have encountered diverse levels of resilience and adequate disaster relief performance has remained elusive. In this paper, several unique characteristics that disaster relief efforts exhibit are examined as compared with demand-driven, steady-state supply chains. Important differences in the flows of resource, money, and information are identified. A complex adaptive supply network (CASN) lens is used to frame what existing literature has uncovered regarding disaster relief efforts, showing how relief organisations, their interactions, and their environmental context help determine the level of resilience that supply networks experience following disasters. This CASN characterisation is leveraged to help explain why traditional supply chain management practices lead to varied results in disaster relief. Finally, complexity science theory is drawn on to set forth eight testable propositions that may help to enhance supply network resilience.     

Determination of the optimal degree of information sharing in a two-echelon supply chain

Information sharing is beneficial for supply chains, but often has marginally decreasing impacts on profit due to the costly expense of collecting more detailed information. This study aims to determine the optimal degree of information sharing with consideration of the trade-off between the cost of collecting information and the benefits gained by utilising it to enhance the profit of a two-echelon supply chain. Based on the analytical results, the profit that the supplier gains from information sharing can stem from the decrease in inventory cost after having more accurate information about demand. Furthermore, the impacts that the cost of collecting information has on the optimal degree of information sharing are investigated, and the results show that the optimal degree of information sharing is positively correlated to the correlation of successive market demand, that is, when the demand for successive periods is more correlated, information sharing becomes more valuable, and hence the optimal degree of information sharing increases.     

供应链信息不确定性对生产计划的影响及改善方法研究

分析了供应链上信息不确定性的主要根源,从需求与供应两个角度分析供应链信息不确定性对生产计划的影响;探讨如何通过信息共享、弱化信息不确定性等提高生产计划动态响应性的技术方法．     

Coordination of dual-channel supply chains under demand disruptions management decisions

This paper examines optimal decisions and coordination models for a dual-channel supply chain when the two end competition market demands are simultaneously disrupted. Firstly, we developed the pricing and production decisions models without demand disruptions and propose a revenue sharing contract to coordinate the dual-channel supply chain where the manufacturer is a Stackelberg leader and the retailer is a follower. We derived the conditions under which the maximum profit can be achieved in detailed. We compared the profits under normal case and disrupted case and quantified the information value of knowing demand disruptions. We proposed an improved revenue sharing contract to coordinate the dual-channel supply chain with demand disruptions. The results indicate that the adjusting prices and production quantity are the optimal decisions whether the demand disruptions case or normal case. We also find that the original revenue sharing contract is a special case of improved revenue sharing contract and the market scale change, channel substitutability and deviation cost affected the improved revenue sharing contract under demand disruptions. Finally, we further conduct numerical experiments to show how the demand disruption affects the decisions.     

A multi-agent model for the reasoning of uncertainty information in supply chains

In order to simulate the real world effectively, this paper proposes a multi-agent model that integrates a price negotiation support system based on the use of intelligent agents capable of processing information uncertainty. The certainty factor is integrated in expert systems to support the decision of agents. In the model, each agent is integrated with an expert system to deal with the uncertainty information. A real example of supply chains is chosen to show the validity of the proposed multi-agent model. Virtual companies can use the uncertainty information to support decisions. Multiple experiments are conducted to work on the coordination of the supply chain. The selling and purchasing prices in the supply chain are proposed in the experimental results. These prices are similar with the data in a real supply chain and are the optimal price strategy for the supply chain. The model was programmed using Jess and Swarm, which was run on Windows XP. The multi-agent model in the paper is beneficial to the reasoning of uncertainty information in multi-agent systems.     

Involvement in emergency supply chain for disaster management: a cognitive dissonance perspective

An integrated process, interlinked operation and interoperable communication network amongst operating agencies are critical for developing an effective disaster management supply chain. The traditional managerial problems observed across disaster management operations are: non-cooperation among members, disrupted chain of commands, misuse of relief items, lack of information sharing, mistrust and lack of coordination. This study aims to understand the issues affiliated with negative attitude towards disaster management operations using theory of cognitive dissonance. A qualitative investigation was undertaken across 64 districts in Bangladesh. Five constructs were examined for their influences on attitude and behavioural intention of members participating in government emergency supply chain for disaster management. The results indicate that administrative conflict, political biasness and professional growth have significant effects on attitude. Impact of insecurity is non-significant on attitude. This research offers substantial theoretical contribution to the cognitive dissonance theory in the context of disaster management supply chain.     

突发事件且非对称信息下的供应链回购契约模型

考虑由一个制造商和一个零售商组成的供应链,在随机市场需求下,分析了回购契约对供应链的协调作用;探讨了突发事件导致市场需求和零售商边际成本同时变化且变化后的零售商边际成本是不对称信息时回购契约对供应链的协调作用,研究表明：基准的回购契约对突发事件下的供应链不再发挥协调作用,为此,给出了供应链应对突发事件的最优应对策略,并调整了原来的回购契约使其具有抗突发事件性。用一个算例对比加以说明。      

环境绩效视角下的闭环供应链定价和协调

从供应链利润和环境绩效视角分别对集中式和分散式闭环供应链进行建模分析,得出2种不同视角下的最优定价和协调策略。结果表明,供应链基准利润提高,环境绩效变差;2种视角下,零售价和单位回收价格之间的关系是一致的;以环境绩效最大化为目标的供应链可以达到相比于以利润最大化为目标的供应链较好的环境绩效,但由于零售价较高,供应链所获得的利润减少;同一收益共享契约在不同参数设置下可以协调2种视角下的供应链。     

供应链中信息资源共享的行为学分析

供应链中各阶段之间的合作往往由于非技术原因产生失调.JH窗是研究人与人之间沟通的图形化模型.通过改进JH窗,将信息共享行为描述为一个JH窗中区域变化过程,分析了合作中技术和管理两个因素之间的关系.用JH窗描述了合作行为对信息资源共享的影响与合作行为改进的方向.指出信息共享不仅是技术问题,管理因素是技术应用成败的关键.只有在一个诚信和开放的环境中,合作的参与者才能开放自身的信息,并通过良性的反馈减小自身盲区,提高对环境的信任,从而开放更多的信息以达到一个良性的循环.     

A clustering algorithm for supplier base management

Supplier base management is an important strategy for managing global, customer driven supply chains. Successful supplier base management can effectively handle supply side exceptions, which may have significant business implications. Currently, there is a trend to reduce the size of the supplier base which makes the coordination and interaction among suppliers more effective, less costly and time consuming. The goal of this research is to present a clustering algorithm, named min-min-roughness (MMR) to cluster suppliers into smaller, more manageable groups with similar characteristics. Due to the fact that supplier data are mainly categorical in nature, MMR, based on rough set theory (RST) is developed for categorical data clustering which is also capable of handling the uncertainty during the clustering process. One potential benefit of applying MMR to supplier base management is that more realistic benchmarking can be obtained and the fulfilment operation can be sped up by reducing the number of variables impacting the operations. In addition, the characteristics of each smaller group of suppliers can be summarised and exploited to handle supply side disruptions.     

Vendor-managed inventory: a review based on dimensions

Vendor-managed inventory (VMI) represents the methodology through which the upstream stage of a supply chain (vendor) takes responsibility for managing the inventories at the downstream stage (customer) based on previously agreed limits. VMI is another method by which supply chains can be managed, and, owing to centralised decision-making and constant information sharing, the benefits are much higher than in traditional supply chain case. However, there exists a lack of research that identifies the dimensions of VMI, benefits of VMI, methods, and levels used in the VMI environment. The focus of this paper is to explore the existing literature on VMI, to categorise it according to the criteria evaluated, and to present a systematic review. In this study, we have classified the review into three categories such as dimension-based, methodology-based, and level-based. From the thorough literature review, we have identified six dimensions of VMI: namely, inventory, transportation, manufacturing, general benefits, coordination/collaboration, and information sharing. In addition, there are, three methodological classifications: modelling, simulation, and case studies. Finally, we will consider the level-based classification. Based on the review, several recommendations that improve the performance of VMI are presented.     

Emerging trends in large-scale supply chain management

The present evolution of production systems and markets is forcing producers, distributors and vendors to integrate their operations into large-scale networks of different services for managing materials and products, information and capitals, i.e. into a 'supply chain'. 'Integration' seems to be the new paradigm in organizing business lines, and 'supply chain management' seems to be the related organization approach that can help in managing interactions among concurrent firms as well as markets. However, supply chains are really complex systems, and their management is a really complex task in which the cooperation of several intelligent agents together and their finalization to common industrial goals need methods and procedures that are still either to be developed or, at the least, to be widely validated. The actual goal for an effective supply chain management is to obtain a good integration of all intelligent agents, such as to make each local strategy as cooperative as possible. This paper will analyse the basic concepts of supply chain management, with the aim of presenting a set of design criteria that could drive a designer in organizing more efficient management systems.