Benefits of working capital sharing in supply chains

Supply chain finance and working capital management are important avenues to reduce supply chain costs. Small suppliers may not have sufficient working capital to finance their operations and efficiently supply their customers. We develop a model that captures the fundamental aspects of financial and operational planning in a two-stage supply chain, with both strong and weak members. A strong member can negotiate for more favorable financing rates, more advantageous payment terms, and shorter lead times than a weaker member. We investigate two working capital allocation scenarios. In the dedicated working capital allocation scenario, the members of the supply chain each have their own working capital. In the joint working capital allocation scenario, the members of the supply chain have a joint pool of working capital. Our results demonstrate significant benefits when the members of the supply chain share the working capital. We also show that extending payment delays to a supplier upstream results in higher overall supply chain costs.     

Bilateral information sharing in two supply chains with complementary products

Information sharing has been regarded as a major way to promote collaboration or to optimize overall supply chain performance. Most of the literature has focused on unilateral information sharing in a supply chain with single or substitutable products. This paper investigates bilateral information sharing in two supply chains with complementary products, and formulates four decision models based on different information sharing patterns. Our results show that (i) information sharing always benefits the manufacturer, and benefits the retailer and the whole supply chain under certain conditions; (ii) information sharing increases/decreases the positive effect of the retailer’s/manufacturer’s forecast on the optimal pricing strategies in its own supply chain; however, its impact depends on the parameter conditions in the other complementary supply chain.     

Optimal production and rationing decisions in supply chains with information sharing

This paper considers a two-echelon capacitated supply chain with two non-identical retailers and information sharing. We characterize the optimal inventory policies. We also study the benefits of the optimal stock rationing policy over the first come first served (FCFS) and the modified echelon-stock rationing (MESR) policies.     

A new revenue sharing mechanism for coordinating multi-echelon supply chains

A new type of revenue sharing (RS) contract mechanism for multi-echelon supply chains between the most downstream entity and all upstream entities is proposed. The new RS contract is analyzed in the linear supply chain setting facing stochastic demand. Advantages over mechanisms with RS contracts between all pairs of adjacent entities are discussed and demonstrated.     

Risk management and coordination in service supply chains: information,logistics and outsourcing

A service supply chain, which is a system formed by a network of suppliers, service designers, service providers and other service partners, aims to transfer available scarce resources into services and deliver them to satisfy customer needs. It is a known fact that service supply chain management is playing a more and more important role in modern economies. However, the unique features of service supply chains also create new challenges that call for proper management of the respective operations. In particular, how to coordinate a service supply chain with risk considerations is a critical issue. In this paper, we concisely examine coordination and risk management challenges in service supply chain systems. We also introduce the technical papers featured in the special issue.     

Strategic information sharing in a supply chain

We consider a two-member supply chain that manufactures and sells newsboy-type products and comprises a downstream retailer and an upstream vendor. In this supply chain, the vendor is responsible for making stock-level decisions and holding the inventory, and the retailer is better informed about market demand. In each period, the retailer receives a signal about market demand before the actual demand is realized, and must decide whether to reveal the information to the vendor, at a cost, before the vendor starts production. We assume that any information that the retailer reveals is truthful. We model the situation as a Bayesian game, and find that, in equilibrium, whether the retailer reveals or withholds the information depends on two things—the cost of revealing the information and the nature of market demand signal that the retailer receives. If the cost of sharing the information is sufficiently large, then the retailer will withhold the information from the vendor regardless of the type of signal that is received. If the cost of sharing the information is small, then the retailer will reveal the information to the vendor if a high demand is signaled, but will withhold it from the vendor if a low demand is signaled. In general, reducing the cost of sharing information and increasing the profit margin of either the retailer or the vendor (or reducing the cost of the vendor or retailer) will facilitate information sharing.     

A multi-layer demand-responsive logistics control methodology for alleviating the bullwhip effect of supply chains

This paper presents a multi-layer demand-responsive logistics control strategy for alleviating, effectively and efficiently, the bullwhip effect of a supply chain. Utilizing stochastic optimal control methodology, the proposed method estimates the time-varying demand-oriented logistics system states, which originate directly and indirectly downstream to the targeted member of a supply chain, and associate these estimated demands with estimates of different time-varying weights under the goal of systematically optimizing the logistical performance of chain members. In addition, an experimental design is conducted where the proposed method is evaluated with the two specified criteria. Numerical results indicate that the proposed method permits alleviating, to a great extent, the bullwhip effect in comparison with the existing logistics management strategies. Furthermore, the methodology presented in this study is expected to help address issues regarding the uncertainty and complexity of the distortion of demand-related information existing broadly among supply chain members for an efficient supply chain coordination.     

Demand forecasting and sharing strategies to reduce fluctuations and the bullwhip effect in supply chains

Supply chain inventories are prone to fluctuations and instability. Known as the bullwhip effect, small variations in the end item demand create oscillations that amplify throughout the chain. By using system dynamics simulation, we investigate some of the structural sources of the bullwhip effect, and explore the effectiveness of information sharing to eliminate the undesirable fluctuations. Extensive simulation analysis is carried out on parameters of some standard ordering policies, as well as external demand and lead-time parameters. Simulation results show that (i) a major structural cause of the bullwhip effect is isolated demand forecasting performed at each echelon of the supply chain, and (ii) demand and forecast sharing strategies can significantly reduce the bullwhip effect, even though they cannot completely eliminate it. We specifically show how each policy is improved by demand and forecast sharing. Future research involves more advanced ordering and forecasting methods, modelling of other well-known sources of bullwhip, and more complex supply network structures.     

A heuristic for single-warehouse multiretailer supply chains with all-unit transportation cost discounts

In supply chain management research, transportation costs, if explicitly considered at all, are frequently assumed to be linear. These costs often have a more complex form, such as an all-unit discount structure – this piecewise cost function adds significant complexity when included in supply chain management problems and is therefore often ignored due to solution time or tractability concerns. We present and evaluate a new heuristic procedure which provides good solutions to problems involving all-unit discount cost functions while significantly reducing solution times. The general nature of this procedure does not require assumptions about the supply chain structure or policies, and is therefore applicable in a wide range of settings.     

Demand forecast sharing in a dual-channel supply chain

We assess the benefits of sharing demand forecast information in a manufacturer–retailer supply chain, consisting of a traditional retail channel and a direct channel. The demand is a linear function of price with a Gaussian primary demand (i.e., zero-price market potential). Both the manufacturer and the retailer set their price based on their forecast of the primary demand. In this setting, we investigate the value of sharing demand forecasts. We analyze the ‘make-to-order’ scenario, in which prices are set before and production takes place after the primary demand is known, and the ‘make-to-stock’ scenario, in which production takes place and prices are set before the primary demand is known. We also compare the supply chain performance with and without the direct channel under some assumptions (production cost is zero, and each demand function has the same slope of price). We find that the direct channel has a negative impact on the retailer’s performance, and, under some conditions, the manufacturer and the whole supply chain are better off. Our research extends and complements prior research that has investigated only the inventory and replenishment-related benefits of information sharing.     

Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty

In this paper, a mixed integer linear programming (MILP) formulation is developed for the design and planning of supply chains with reverse flows while considering simultaneously production, distribution and reverse logistics activities. It is also considered products’ demand uncertainty using a scenario tree approach. As main goal the model defines the maximization of the expected net present value and the results provide details on sizing and location of plants, warehouses and retailers, definition of processes to install, establishment of forward and reverse flows and inventory levels to attain. The model is applied to a representative European supply chain case study and its applicability is demonstrated.     

Bundling decisions in supply chains

Firms often sell products in bundles to extract consumer surplus. While most bundling decisions studied in the literature are geared to integrated firms, we examine a decentralized supply chain where the suppliers retain decision rights. Using a generic distribution of customers’ reservation price we establish equilibrium solutions for three different bundling scenarios in a supply chain, and generate interesting insights for distributions with specific forms. We find that (i) in supply chain bundling the retailer’s margin equals the margin of each independent supplier, and it equals the combined margin when the suppliers are in a coalition, (ii) when the suppliers form a coalition to bundle their products the bundling gain in the supply chain is higher and retail price is lower than when the retailer bundles the products, (iii) the supply chain has more to gain from bundling relative to an integrated firm, (iv) the first-best supply chain bundling remains viable over a larger set of parameter values than those in the case of the integrated firm, (v) supplier led bundling is preferable to separate sales over a wider range of parameter values than if the retailer led the bundling, and (vi) if the reservation prices are uniformly distributed bundling can be profitable when the variable costs are low and valuations of the products are not significantly different from one another. For normally distributed reservation prices, we show that the bundling set is larger and the bundling gain is higher than that for a uniform distribution.     

Strategic cooperation in cost sharing games

We examine strategic cost sharing games with so-called arbitrary sharing based on various combinatorial optimization problems. These games have recently been popular in computer science to study cost sharing in the context of the Internet. We concentrate on the existence and computational complexity of strong equilibria (SE), in which no coalition can improve the cost of each of its members. Our main result reveals a connection to the core in coalitional cost sharing games studied in operations research. For set cover and facility location games this results in a tight characterization of the existence of SE using the integrality gap of suitable linear programming formulations. Furthermore, it allows to derive all existing results for SE in network design cost sharing games with arbitrary sharing via a unified approach. In addition, we show that in general there is no efficiency loss, i.e., the strong price of anarchy is always 1. Finally, we indicate how the LP-approach is useful for the computation of near-optimal and near-stable approximate SE.     

An analytical method for cost analysis in multi-stage supply chains: A stochastic network model approach

This paper studies the cost distribution characteristics in multi-stage supply chain networks. Based on the graphical evaluation and review technique, we propose a novel stochastic network mathematical model for cost distribution analysis in multi-stage supply chain networks. Further, to investigate the effects of cost components, including the procurement costs, inventory costs, shortage costs, production costs and transportation costs of supply chain members, on the total supply chain operation cost, we propose the concept of cost sensitivity and provide corresponding algorithms based on the proposed stochastic network model. Then the model is extended to analyze the cost performance of supply chain robustness under different order compensation ability scenarios and the corresponding algorithms are developed. Simulation experiment shows the effectiveness and flexibility of the proposed model, and also promotes a better understanding of the model approach and its managerial implications in cost management of supply chains.     

Cost analysis in global supply chains

This paper aims to explore effect of supply chain members’ costs change on participants of the network. On one perspective, it explores when there is a cost change to a firm, how other firms are affected and who bear(s) the most effect. On the other perspective, it investigates how an individual firm’s performance is affected by the other members in its network and whose cost change would impose a most significant effect on its profit.     

Managing raw material in supply chains

In this paper, we explore how firms can manage their raw material sourcing better by developing appropriate sourcing relationships with their raw material suppliers. We detail three empirical case studies of firms explaining their different raw material sourcing strategies: (a) firms can adopt a hands-off approach to raw material management, (b) firms can supply raw material directly to their suppliers, and this may be beneficial for some agents in the supply chain, and (c) firms can bring their component suppliers together, and the resulting cooperation between suppliers can be beneficial for supply chain. We then analytically model the three raw material scenarios encountered in our empirical work, examine the resulting profits along the supply chain, and extend the results to a competitive buyer scenario. Overall, our results show that active management of raw material sourcing can add value to supply chains.     

Profit allocation games in supply chains

The paper considers a supply chain where a number of agents are connected in some network relationship. Game theory is a very powerful framework for studying decision making problems, involving a group of agents in a supply chain. Allocation games examine the allocation of value among agents connected by a network. The ongoing actions in the supply chain are a mix of cooperative and non-cooperative behavior of the participants. The paper proposes a two-stage procedure for profit allocation based on combination of non-cooperative and cooperative game approaches. In the first stage, retailers meet customer price-dependent stochastic demand and seek to maximize total profit from the sale. Retailers are trying to align goals with producers on a contract basis and share the total profit with them. In the second stage, the cooperating producers allocate individual profits.     

Paths and consistency in additive cost sharing

We provide a direct proof of a representation theorem for additive cost sharing methods as sums of path methods. Also, by directly considering the paths that generate some common additive cost sharing methods (Aumann-Shapley, Shapley Shubik, and Serial Cost) we show that they are consistent. These results follow directly from a simple sufficient condition for consistency: being generated by an associative path. We also introduce a new axiom, dummy consistency, which is quite mild. Using this, we also show that the Aumann-Shapley and Serial Cost methods are the unique (additive) consistent extension of their restriction on all two agent problems, while the Shapley-Shubik method has multiple consistent extensions but a unique anonymous scale invariant one.I would like to thank Rich Mclean for many detailed comments and suggestions, Ori Haimanko for pointing out an error in an earlier version of this paper, Hervé Moulin, Yves Sprumont, Yuntong Wang for helpful comments and an anonymous referee for many useful comments. This paper contains results from two previous working papers: Paths in Additive Cost Sharing and Weak and Strong Consistency in Additive Cost Sharing.Received: November 2001/Revised: January 2004