Inventory control in a two-echelon dual-channel supply chain with setup of production and delivery

This paper considers a two-echelon dual-channel supply chain model with setup of production and delivery and develops a new inventory control policy for the supply chain. Previously, a two-echelon supply chain model without setup of production and delivery is considered and a one-for-one inventory control policy is applied to the supply chain. In the inventory control policy, production is stopped when the warehouse inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. Moreover, delivery to the retailer is stopped when the store inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. The total cost that consists of inventory holding costs and lost sales cost is considered, and setup costs are not considered in the total cost. Once setup costs are introduced, the one-for-one inventory control policy is no longer appropriate. Then, this paper develops a new control policy for the two-echelon dual-channel supply chain with setup of production and delivery. As performance measure, the total cost that consists of inventory holding costs, lost sales cost, and production and delivery setup costs is considered, and the total cost calculated on the basis of Markov analysis demonstrates the effectiveness of the proposed control policy.     

Inter-temporal inventory competition and the effects of capacity constraints

This paper addresses an intertemporal inventory competition between a supplier (a provider, manufacturer) and a retailer engaged in a supply chain. The paper's focus is on the effect of capacity constraints on both parties when demands are seasonal. The paper provides a comparative study of two solution approaches, one is based on supply chain competition and the other is based on system wide optimization. Our results demonstrate that with dynamic inventory competition, the retailer reduces inventory costs by reducing the response period to higher demands while increasing the supply requests compared to the system-wide optimal approach. As a result, the supplier's inventory costs increase. An example illustrating these particular facets of the problem and its application is presented and discussed in light of the supplier and the retailer coordinating policies.     

Retailer policy, uncertainty reduction, and supply chain performance

We investigate how the retailer’s inventory policy affects the total cost of a serial supply chain. When the retailer uses the locally optimal (s,S) policy, there is randomness in order time and order quantity to the supplier whereas the supplier sees randomness only in order quantity for the suboptimal (R,T) policy and only in order time for another suboptimal (Q,r) policy. Using an extensive computational study, we find that the suboptimal policies perform better from the total supply chain perspective. The benefit of policy changes is magnified when the retailer costs are low, when the supplier costs are high, and when there is information sharing.     

A holistic network model for supply chain analysis

Supply chain researchers are experiencing a conceptual and analytical paradox. They are asked to move beyond dyadic analyses and investigate larger network effects with only a limited analytical toolkit. This research proposes the use of bilinear mixed-modeling to holistically analyze supply chain phenomena. Through this approach, researchers are able to account for multiple supply chain relationships, higher-order dependencies among member firms, and simultaneously evaluate covariates from buyer and seller perspectives. The model is validated through the lens of a pervasive supply chain problem commonly referred to as the bullwhip effect. A sample of firms from the US apparel industry in 2004 is analyzed and then the findings are confirmed using data from 2005. In addition to validating the model through the presence of the bullwhip effect, the bilinear model illuminates variables such as advertising, price deals, inventory turnover, and inventory backlogs that exacerbate or diminish inventory differences between firms in a supply chain. The results extend research on supply networks and supply efficiency to a more holistic level and show that higher-order dependencies are important drivers of supply chain phenomena.     

Ordering and pricing policies in a manufacturing and distribution supply chain for fashion products

In the paper, we develop a model of manufacturing and distribution supply chains that are operating to meet price-sensitive random demand for products with short life cycles such as fashion products. Two specific scenarios are considered. The manufacturer-controlled scenario is one where the distributor shares price-sensitive random demand with the manufacturer, and the manufacturer controls the supply chain stocking decisions and bears the risk of overstocking costs. The distributor-controlled scenario works in the opposite direction. Prevailing wisdom suggests that the manufacturer should control supply chain decisions (e.g., via vendor-managed inventory). Our results indicate that such an arrangement is against the interest of a distributor selling short life-cycle products. Furthermore, we find that the total supply chain profit is generally higher when the distributor controls the supply chain stocking decisions and bears the risk of overstocking costs.     

Streamlining inventory flows with time discounts to improve the profits of a decentralized supply chain

We consider a decentralized supply chain, whereby a supplier sells a product to a group of independent buyers, and develop a strategy for the supplier to offer an all-units price discount or cash rebate for orders that are synchronized with its replenishments. As synchronized orders can be met with inventory directly from receiving to shipping without warehousing, the proposed strategy streamlines system inventory flows to minimize inventory and, hence, the related costs. On the other hand, by increasing the replenishment interval of the supplier, the proposed strategy is able to induce buyers to order in large quantities and hence achieve the objectives of quantity discounts. We show that the proposed strategy can achieve nearly optimal (minimum) system cost, and is much more effective than the existing coordination strategies for decentralized supply chains in the literature.     

Optimal inventory control of empty containers in inland transportation system

In this paper, we deal with an inventory control problem of empty containers in an inland transportation system. In inland container transportation, freights (containers) are transported between terminal and the customer’s location by trucks, trains and barges. Empty containers are an important logistic resource and shipping companies try to operate and manage empty containers efficiently. Because of the trade imbalance between hub ports, empty containers should be periodically repositioned from surplus areas to shortage areas. However, it is not easy to exactly forecast the demand of empty containers, and we therefore need to build an efficient way to reposition the empty containers. In this paper, we consider a shortage area and propose an efficient inventory policy to control empty containers. We assume that demands per unit time are independent and identically distributed random variables. To satisfy the demand of empty containers, we reposition empty containers from other hubs based on the (s, S) inventory policy, and also consider the lease of empty containers with zero lead time. For the leased containers, we should return the number of empty containers leased to the leaser after the specified period. For a given policy, simulation is used to estimate the expected cost rate and we use the optimization tool, OptQuest^® in Arena to obtain the near optimal (s, S) policy in numerical examples.     

Inventory management with random supply and imperfect information: A hidden Markov model

In most of the papers on inventory models operating in a random environment, the state of the environment in each period is assumed to be fully observed with perfect information. However, this assumption is not realistic in most real-life situations and we provide a remedy in this paper by assuming that the environment is only partially observed with imperfect information. We accomplish this by analyzing two formulations of single-item models with periodic-review and random supply in a random environment. In the first one, supply is random due to random capacity of production and random availability of transportation. We show that state-dependent base-stock policy is optimal if the capacity and all costs are observed, while demand and availability are unobserved. In the second model, we consider a model with random availability only with fixed-ordering cost. We show that state-dependent (s,S) policy is optimal if the availability process is observable.     

Conceptual modelling for supply chain inventory visibility

Visibility becomes increasingly important for companies that seek to globalise their supply chains due to the increasing complexity involved. This paper contributes to the research on Supply Chain Visibility (SCV) from an inventory perspective with a focus on inventory visibility, which is a critical part of SCV. The characteristics of Inventory Visibility (IV), which are inherited from SCV, are conceptually analysed. A theoretical model in terms of atom, single, and compound visibility, is developed based on the characteristics identified. A method for objectively measuring IV is presented together with a case example to demonstrate its convenience and usefulness.     

Reducing the mean supply delay of spare parts using lateral transshipments policies

Lateral transshipment has been studied lately as a promising policy for increasing the performances of multi-echelon spare parts inventory system. By lateral transshipment spare parts can be moved from one location with excess inventory to another location, at the same echelon, in shortage, with the aim of reducing supply delays of spare parts. This paper will examine the relative effectiveness of two lateral shipments approaches in reducing the mean supply delay (MSD) of a non-repairable item, with respect to a classical policy of no lateral shipments. A simulation model of a two echelon supply network has been implemented and an experiment has been performed by varying different parameters of the supply network, such as the number of warehouses (locations at the lower echelon), the supply lead time from the central depot, the spare parts demand uncertainty, and the size variability of the warehouses. Results show appreciable reductions of MSD when lateral shipments are allowed with respect to the classical policy, in almost every network configuration.     

Using System Dynamics to assess the impact of RFID technology on retail operations

The application of item-level radio frequency identification (RFID) technology in retail supply chains creates cost savings and promises large potential benefits from revenue growth. However, the economic assessment of the impact on improved store operations, labor utilization, and increased sales is still not fully explored. We propose to use System Dynamics as a structural modeling and simulation approach to integrate conventional return on investment evaluations. Building on previous research about RFID technology in retail supply chains, we developed a model based on the case exploration of a leading Italian apparel retailer. Simulations show that RFID implementations are profitable whenever they contribute to increase sales, especially when a fashion retailer is focused on clerk-assisted sales strategies. Sales growth results from the dynamic and integrated impacts of RFID technology on better inventory control, faster inventory turnover, and longer time available for store personnel to assist consumers as an effect of more efficient backroom operations.     

Information sharing and profit allotment based on supply chain cooperation

To maximize customer value created by a supply chain system as a whole, one of the key issues in supply chain management is how to have profit and benefit properly shared between partners in an effective manner of the supply chain integration. In this regard, information sharing between partners plays a rather important role in business process and management integration of the supply chain. The paper focuses on analyzing the value created from information sharing by decreasing inventory level and on investigating the collaborative mechanism of providing incentive to retailer by upstream partner via sharing profit gained information sharing in the context of three-echelon supply chain system. The issue of dealing with the interest conflict between the supply chain as a whole and individual partners is addressed based on information sharing analysis by means of cooperative game approach, a graphic model with three-dimensions is developed to depict the possible cooperative solutions of profit allotment between partners, and a problem solving method addressing how the profit allotment between partners can effectively motivate the partners to be cooperative with each other is presented as well.     

An inventory model with non-resuming randomly interruptible lead time

We assume that an unreliable supplier in a single-item stochastic inventory system alternates randomly between two possible states (i.e., available and unavailable), following a two-state continuous-time homogeneous Markov chain. For a compound Poisson stream of demands and Erlang lead times, our model considers the scenario where the processing of the outstanding order (if any) is interrupted at every supplier's transition epoch from the available to the unavailable state, and is restarted from the outset upon the supplier's regaining its available state. We derive the stationary distribution of the on-hand inventory under a continuous-review policy and provide some numerical results.     

Comparison of benefits of radio frequency identification: Implications for business strategic performance in the U.S. and Korean retailers

This study explores a model to compare the benefits of RFID technology on supply chain management by focusing on retail industry. A path model was estimated to examine structural relationships among technological infrastructure, RFID benefits, and business strategic performance in the U.S. (n = 70) and Korean samples (n = 87). Result showed that technological infrastructure was required to more improve inventory management, store operation and demand management, leading to business strategic performance. Especially, data system automation was perceived as a prerequisite for improving inventory management for both countries. Hardware/software application was significantly related to the RFID benefit of inventory management for U.S. retailers, whereas, it was related to the benefits of efficient store operation and demand management for Korean retailers. Business strategic performance was significantly determined by RFID benefit factors (e.g., inventory management and demand management) for U.S. retailers and Korean retailers. The managerial implication for business to business strategic performance in the U.S. and Korean retail industries was discussed from a retailer's perspective.     

Agents’ incentives under buy-back contracts in a two-stage supply chain

This paper investigates how the behavior of individual decision makers can affect the performance of a supply chain. We study a two-stage supplier–retailer system, using a buy-back contract. Each firm's actions are executed by an agent. The retailer's purchasing agent and the supplier's sales agent are compensated based on certain performance measures, and they act accordingly. We study the impacts of their behavior in both the supplier-as-leader and retailer-as-leader settings. We find that, unless their incentives are carefully constructed, the agents can strongly distort the system's behavior. Specifically, “channel stuffing” (packing the distribution channel with excess inventory) can occur in both settings. Only when the agents are compensated based on net profit do they act in accord with their firms’ objectives. These results may help explain some recent scandals.     

Optimization of a vendor managed inventory supply chain with guaranteed stability and robustness

In this work we address the steady state optimization of a supply chain model that belongs to the class of vendor managed inventory, automatic pipeline, inventory and order based production control systems (VMI-APIOBPCS). The supply chain is optimized with the so-called normal vector method, which has specifically been developed for the economic optimization of uncertain dynamical systems with constraints on dynamics. We demonstrate that the normal vector method provides robust optimal points of operation for a number of scenarios. Since the method strictly distinguishes economic optimality, which is treated as the optimization objective, from dynamical requirements, which are incorporate by appropriate constraints, it provides a measure for the cost of stability and robustness as a desired side-effect.     

A review of the extensions of a modified EOQ model for imperfect quality items

Imperfect items in the raw material and production stages of a supply chain directly impact the coordination of the product flow within a supply chain. In response to this concern, production and inventory lot sizing models, which incorporate imperfect items into their formulation have become an important and growing area of research. The contribution of Salameh and Jaber (2000) is one of the fundamental models on lot sizing when procured items are of imperfect quality. Over the past decade, there has been a noticeable amount of interest in the EOQ model for imperfect items that was set forth in Salameh and Jaber (2000). Several researchers have published adaptations and extensions of this original model that address supply chain coordination, quality improvement and yield management, and the impact of human error on production and inventory systems. In this paper, we summarize the current body of research that has extended the Salameh and Jaber (2000) EOQ model for imperfect items. Some possible future research directions are identified at the end of the paper.     

Introduction to design and analysis of production systems

In a two-party VMI channel, the vendor operates the basic stocking and delivery functions and makes inventory replenishment decisions while the retailer is responsible for customer acquisition and in-store services. This paper focuses on such retail channel and proposes an analytical model for the partners in supply channel to determine the inventory policy with the objective of optimizing system net profit. The model explicitly incorporates issues from both the vendor and the retailer in order to derive a policy for mutual benefits. To illustrate and obtain insights from the proposed solution procedure, we devise a set of numerical analyses based on various scenarios. Factors such as shelf-space-dependent demand, shelf-space capacity, demand pattern, logistics characteristics, and disparity between holding costs of the warehouse and the retail store are also investigated.     

Considering stochastic lead times in a manufacturing/remanufacturing system with deterministic demands and returns

In this paper we study a manufacturing/remanufacturing system with stochastic lead times and a constant demand. We base our approach on previous research in which we have developed models to describe an inventory system with stochastic lead times. In this paper, we first adopt this method to manufacturing/remanufacturing situations, where there are essentially two supply sources for replenishing serviceable inventory. We then provide a solution procedure when a cycle ordering policy is used. Secondly, we investigate the possibility to use a dual sourcing ordering policy in which each order is split between a manufacturing and a remanufacturing process. Finally, we compare the two ordering policies and illustrate how the lead-time patterns influence the economic consequences.