A Purchasing Framework for B2B Pricing Decisions and Risk‐sharing in Supply Chains*

This paper presents a common modelling structure for (i) the implementation of operational policies by individual purchasing managers of risk‐sharing agreements among supply‐chain partners, and (ii) the integration of brick and click purchasing policies in a B2B. The problem of price uncertainty created within these two environments is modelled as a stochastic repetitive‐sales problem, applicable to any probability distribution. The model identifies sufficient conditions for regenerative ordering cycles, which allows for the use of the renewal reward theorem. The end result is a two‐price purchasing policy, which may substantially ease implementation problems across a global corporation's purchasing managers world‐wide and across B2B markets.     

Freezing the Master Production Schedule: Implications for Fill Rate*

Previous research examining alternative ways of dealing with schedule instability has shown that freezing a portion of the master production schedule (MPS) is a cost effective way to reduce instability. While it is often argued that MPS freezing limits the firm's ability to react to changing customer needs, the impact of freezing on customer service is not well understood. We examined the impact of freezing a specified portion of the MPS on the average fill rate under a wide variety of conditions using controlled simulation experiments. The results show that freezing can be implemented without causing a severe reduction in customer service.     

Replanning the Master Production Schedule for a Capacity-Constrained Job Shop

This research examines the use of both frozen and replanning intervals for planning the master production schedule (MPS) for a capacity-constrained job shop. The results show that forecast error, demand lumpiness, setup time, planned lead time, and order size have a greater impact on the mean total backlog, total inventory, and number of setups than the frozen and replanning intervals. The study also shows that a repetitive lot dispatching rule reduces the importance of lot sizing, and a combination of repetitive lot dispatching rule and single-period order size consistently produces the lowest mean total backlog and total inventory. The results also indicate that rescheduling the open orders every period produces a lower mean total backlog and total inventory when the forecast errors are large relative to the order sizes. This result suggests that the due date of an open order should be updated only when a significant portion of the order is actually needed on the new due date.     

Flow Coordination and Information Sharing in Supply Chains: Review,Implications, and Directions for Future Research

Advances in information technology, particularly in the e‐business arena, are enabling firms to rethink their supply chain strategies and explore new avenues for inter‐organizational cooperation. However, an incomplete understanding of the value of information sharing and physical flow coordination hinder these efforts. This research attempts to help fill these gaps by surveying prior research in the area, categorized in terms of information sharing and flow coordination. We conclude by highlighting gaps in the current body of knowledge and identifying promising areas for future research.     

Channel Strategies and Stocking Policies in Uncapacitated and Capacitated Supply Chains*

A supply chain consisting of a single supplier distributing two independent products through multiple retailers is analyzed in this paper. The supplier needs to incentivize its retailers to adopt stocking policies that are mutually advantageous and that result in the optimal level of market coverage. The focus is on determining the optimal stocking policies for retailers and the resulting distribution strategy given that the supplier has either unlimited or limited capacity. The results provide insights on the optimal distribution strategy and stocking policies for the supply chain. In general, the paper shows that it is optimal for the supplier to use an intensive distribution strategy (i.e., the products are stocked by all retailers). Selective or exclusive strategies are optimal only when retailers are risk averse, stocking synergies exist, and there are differences in demand or supply uncertainties across products. The analysis also shows that retailers hold larger stocks of a product which generates higher supplier margins but only when the supplier has unlimited capacity. If the supplier has limited capacity, then their margins have no effect on retailers' stocking decisions. Contrary to conventional wisdom, retailers hold larger stocks of a product that has less demand uncertainty as compared to one that has more demand uncertainty.     

Simulation Analysis of a Manufacturing Supply Chain*

A supply chain is a series of manufacturing plants that transform raw material into finished product. A pipeline within a supply chain refers to the stream of information, material, components, and assemblies that are associated with a particular product. It is typical for manufacturing plants to put considerable effort to optimize the performance of a horizontal slice of a supply chain (such as coordination among parts that share a common resource). The need to optimize the performance of the vertical slice (the supply chain connecting raw material to finished product) by controlling the transmission of schedule instability and the resulting inventory fluctuation is often overlooked. A schedule is stable if actual production requirements for a given period do not change from the forecast production requirements. Stable production schedules are important when managing supply chains as they help control inventory fluctuation and inventory accumulation. Failure to control schedule instability results in high average inventory levels in the system. In this paper a simulation analysis of supply chain instability and inventory is conducted, and it is shown how supply chains can be analyzed for continuous improvement opportunities using simulation. The focus is on a stamping pipeline in an automobile supply chain based on operating data from General Motors (GM). It is shown that the techniques used in this paper are a useful tool for supply chain analysis.     

Role of Random Capacity Risk and the Retailer in Decentralized Supply Chains with Competing Suppliers

This research considers a supply chain under the following conditions: (i) two heterogeneous suppliers are in competition, (ii) supply capacity is random and pricing is endogenous, (iii) consumer demand, with and without an intermediate retailer, is price dependent. Specifically, we examine how uncertainty in supply capacity affects optimal ordering and pricing decisions, supplier and retailer profits, and the incentives to reduce such uncertainty. When two suppliers sell through a monopolistic retailer, supply uncertainty not only affects the retailer's diversification strategy for replenishment, but also changes the suppliers’ wholesale price competition and the incentive for reducing capacity uncertainty. In this dual‐sourcing model, we show that the benefit of reducing capacity uncertainty depends on the cost heterogeneity between the suppliers. In addition, we show that a supplier does not necessarily benefit from capacity variability reduction. We contrast this incentive misalignment with findings from the single‐supplier case and a supplier‐duopoly case where both suppliers sell directly to market without the monopolistic retailer. In the latter single‐supplier and duopoly cases, we prove that the unreliable supplier always benefits from reducing capacity variability. These results highlight the role of the retailer's diversification strategy in distorting a supplier's incentive for reducing capacity uncertainty under supplier price competition.     

绿色供应链管理的集成特性和体系结构

绿色供应链管理是一种现代企业的可持续发展模式。本文论述了绿色供应链管理的概念,分析了绿色供应链管理的集成特性,并建立了绿色供应链管理的体系结构。     

Leveraging Supply Chain Integration through Planning Comprehensiveness: An Organizational Information Processing Theory Perspective

This study extends prior research on supply chain planning and integration by examining the underlying capabilities by which firms exploit the information they gain from integration activities. We use organizational information processing theory (OIPT) to develop hypotheses that identify the comprehensiveness of an organization's supply chain planning capabilities as an important mediator in the relationship between its supply chain integration activities and its operational performance. Further, our interpretation of OIPT suggests that an organization's usage of technology‐enabled supply chain management systems (SCMS) moderates these effects. Using survey data from 445 global firms, we estimate the corresponding moderated‐mediation structural model. The results indicate that usage of SCMS enables organizations to better utilize the information they gain from external integration efforts (relationships with customers and suppliers), thus improving the comprehensiveness of their supply chain planning capabilities. In contrast, the use of SCMS appears to be a partial substitute for internal integration as a driver of planning comprehensiveness. Most importantly, the results suggest that planning comprehensiveness is a significant generative means by which integration and technology investments produce superior operational performance. These findings provide a richer and more theoretically grounded explanation of relationships between supply chain integration, supply chain planning, and operational performance.     

A Comparative Analysis of Master Production Scheduling Techniques for Assemble-To-Order Products

This paper studies the master production scheduling (MPS) activity of manufacturing firms that produce assemble-to-order (ATO) products. It describes four techniques for master scheduling ATO products: end-product bills, modular bills, super bills, and percentage bills. These procedures are compared in terms of the percentage of customer orders delivered late, the mean tardiness of customer order deliveries, and the total cost of inventory using simulation analysis. The results indicate that the performance of an MPS technique is affected by the level of uncertainty of the end products' demands and the degree of component commonality in the product structure. In particular, modular bills produce the highest customer service level and super bills produce the lowest total inventory cost under most operating conditions. The conclusions also suggest that the choice of a particular MPS technique is often a compromise between the benefits of improved MPS performance and the costs of implementing and executing the MPS system.     

Interorganizational Collaborative Forecasting and Replenishment Systems and Supply Chain Implications

Collaborative Forecasting and Replenishment (CFAR) is a new interorganizational system that enables retailers and manufacturers to forecast demand and schedule production jointly. The capabilities of CFAR exceed those of the traditional EDI because CFAR allows exchange of complex decision support models and manufacturer/retailer strategies. The proponents of CFAR claim that the fastest way for retailers and manufacturers to slash inventory costs and product shortages is by coordinating their decisions. The impact of CFAR on the supply chain using a model consisting of a manufacturer selling its product through two independent identical retailers is analyzed. The model assumes that the manufacturer doesn't face capacity constraints, the demand is stationary, and retailer prices are constant over time; the shortages are backordered at the manufacturer and retailers to isolate the effects of information sharing in CFAR. The most significant findings relate to the increase in the cost incurred by the nonparticipant in CFAR, the increase in the manufacturer's cost of serving the nonparticipant if the participant can obtain delivery guarantees in return for demand information sharing, and the incentives of the players to move towards universal retailer participation in CFAR. The findings are explained using the risk structure faced by the players in the supply chain. The managerial implications of the impact of CFAR on the supply chain structure are also discussed.     

e‐Integration in the Supply Chain: Barriers and Performance*

Current opinion holds that Internet‐based supply chain integration with upstream suppliers and downstream customers (called “e‐integration” in this paper) is superior to traditional ways of doing business. This proposition remains untested, however, and similarly we know little about what are the upstream, internal, and downstream barriers to implementing e‐integration. This paper empirically addressed these questions using data from a large single nation study, and found (1) a positive link between e‐integration and performance, and (2) that internal barriers impeded e‐integration more than either upstream supplier barriers or downstream customer barriers. Findings from this study contribute to our theoretical understanding of implementing change in contemporary supply chains, and have important implications for manufacturers interested in improving their supply chain's performance using the Internet.     

基于两层供应链的JIT策略和VMI策略的对比研究

JIT策略和VMI策略是基于供应链的两种先进库存管理方法。本文以两层供应链的JIT策略和VMI策略为例,通过数学模型和具体算例,比较分析了两种策略下买方和卖方运作方式的不同之处。本文研究发现,在外部需求变化时,相对于JIT策略而言,在VMI策略下卖方送货批量将变大、买方的成本将变小、卖方的成本将变大、供应链整体的成本将变小。而在卖方生产启动成本变化时,相对于JIT策略而言,在VMI策略下如果卖方生产启动成本相对较小时,卖方送货批量将变大、如果卖方生产启动成本相对较大时,卖方送货批量将变小、买方的成本将变小、卖方的成本将变大、供应链整体的成本将变小。本文研究分析表明,从供应链整体的角度来看,VMI策略是优于JIT策略的。     

The Impact of Forecast Errors on Early Order Commitment in a Supply Chain*

Supply chain partnership involves mutual commitments among participating firms. One example is early order commitment, wherein a retailer commits to purchase a fixed‐order quantity and delivery time from a supplier before the real need takes place. This paper explores the value of practicing early order commitment in the supply chain. We investigate the complex interactions between early order commitment and forecast errors by simulating a supply chain with one capacitated supplier and multiple retailers under demand uncertainty. We found that practicing early order commitment can generate significant savings in the supply chain, but the benefits are only valid within a range of order commitment periods. Different components of forecast errors have different cost implications to the supplier and the retailers. The presence of trend in the demand increases the total supply chain cost, but makes early order commitment more appealing. The more retailers sharing the same supplier, the more valuable for the supply chain to practice early order commitment. Except in cases where little capacity cushion is available, our findings are relatively consistent in the environments where cost structure, number of retailers, capacity utilization, and capacity policy are varied.     

Solving the Economic Lot-Scheduling Problem Using the Method of Prime Subperiods

In recent years the reported successes of Japanese production systems, particularly the just-in-time approach to inventory control, has caused managers to focus more of their attention on efficient decision-making procedures for determining production schedules that minimize inventory costs. One such potential area of attention is the economic lot-scheduling problem (ELSP), which occurs in a variety of manufacturing environments where machining operations are prevalent. The economic lot-scheduling problem addresses the determination of lot sizes for N products with constant demand (and cycled through one machine with a given production rate) to minimize setup and inventory costs. The most successful solution approaches to the ELSP have been based on the concept of a basic period that is of sufficient length for the production of all items, even though each item might not be produced during each repetition of the basic period. This paper proposes a heuristic approach to the solution of the ELSP (referred to as the method of prime subperiods), which is an extension of the basic period approaches. The procedure is described and demonstrated via an example and then tested using a set of six example problems previously employed in the literature related to the ELSP. The results indicate as good or superior performance by the proposed method of prime subperiods.     

Setup Reduction in the Economic Production Quantity Model

We present an analysis of setup cost reduction using the economic production quantity model. The objectives of the paper are to draw conclusions by investigating several classes of setup reduction functions and to provide a general solution procedure. We examine the trade-offs between reduced inventories and increased capital investment and show that given any hypothetical setup cost reduction function, we can determine whether the total relevant cost can be reduced and how the reduction is achieved.     

The Effect of Lead Time Uncertainty on Safety Stocks

The pressure to reduce inventory investments in supply chains has increased as competition expands and product variety grows. Managers are looking for areas they can improve to reduce inventories without hurting the level of service provided. Two areas that managers focus on are the reduction of the replenishment lead time from suppliers and the variability of this lead time. The normal approximation of lead time demand distribution indicates that both actions reduce inventories for cycle service levels above 50%. The normal approximation also indicates that reducing lead time variability tends to have a greater impact than reducing lead times, especially when lead time variability is large. We build on the work of Eppen and Martin (1988) to show that the conclusions from the normal approximation are flawed, especially in the range of service levels where most companies operate. We show the existence of a service‐level threshold greater than 50% below which reorder points increase with a decrease in lead time variability. Thus, for a firm operating just below this threshold, reducing lead times decreases reorder points, whereas reducing lead time variability increases reorder points. For firms operating at these service levels, decreasing lead time is the right lever if they want to cut inventories, not reducing lead time variability.     

Order Promising and the Master Production Schedule*

Previous research on material requirements planning (MRP) systems has rarely considered the impact of the master production scheduling method used to promise customer orders and to allocate production capacity. Based on a simulation study of an MRP environment, we show that the correct selection of a master production schedule (MPS) method depends on the variance of end-item demand. In addition, we find evidence that the effectiveness of a particular MPS method can be enhanced by holding buffer inventory at the same level in the product structure as in the MPS.     

Supporting Quick Response Through Scheduling of Make-to-Stock Production/Inventory Systems*

Scheduling of traditional job shops in make-to-order systems has seen extensive research over the past three decades. In such systems, performance is often related to various job completion metrics such as average flow time, average lateness, etc. This paper examines a scheduling problem in a make-to-stock environment where individual job completion measures are irrelevant. In this case, customer orders are satisfied through on-hand inventory where customer service is more closely related to the manufacturer's ability to quickly satisfy demand. We consider the role of scheduling in reducing inventories and improving customer service in the context of a manufacturer who assembles several different products on a single assembly line. We develop scheduling rules for such a system and experimentally compare their performance to those typically used in such environments. Our results indicate that rules which consider the inventory position and demand forecast outperform traditional fixed cycle rules.     

Plots of Conditional Wait-Time Intervals Provide Better Information to Queueing System Arrivals

The management of queues is a very important aspect of service operations management. One way to enhance the queueing experience is to provide customers with the most informative and certain estimate of anticipated wait time. This paper develops such a measure—referred to as the conditional wait-time interval (CWTI)—for queueing systems with exponentially distributed service times. It is especially applicable at the operational level of an organization since it utilizes the most current information on the status of the system (number of customers in the queue at arrival). CWTI is also based on two risk factors that consider the chance a customer's actual wait time is outside of the estimated range. This paper also provides a graphical means to display multiple CWTIs.