Unreliable Supplier Research Articles

Approximate Order-Up-To Policies for Inventory Systems with Binomial Yield

This paper studies an inventory policy for a retailer who orders his products from a supplier whose deliveries only partially satisfy the quality require- ments. We model this situation by an infinite-horizon periodic-review model with binomial random yield and positive lead time. We propose an order- up-to policy based on approximating the inventory model with unreliable supplier by a model with a reliable supplier and suitably modified demand distribution. The performance of the order-up-to policy is verified by com- paring it with both the optimal policy and the safety stock policy proposed in Inderfurth & Vogelgesang (2013). Further, we extend our approximation to a dual-sourcing model with two suppliers: the first slow and unreliable, and the other fast and fully reliable. Compared to the dual-index order- up-to policy for the model with full information on the yield, the proposed approximation gives promising results.

How does pricing power affect a firm’s sourcing decisions from unreliable suppliers?

We study sourcing decisions of price-setting and price-taking firms with two unreliable suppliers, where a price-setting firm sets the retail price after the supply uncertainty is resolved and a price-taking firm takes the retail price as given. We investigate the impacts of market conditions, suppliers’ wholesale prices and their reliabilities on the optimal sourcing decisions of price-setting and price-taking firms, and examine how a firm’s pricing power affects these impacts. We define a supplier’s reliability in terms of the “size” or the “variability” of his random capacity using the concepts of stochastic dominance. We find that the supplier reliability affects the optimal sourcing decisions differently for price-setting and price-taking firms. Specifically, with a price-setting firm, a supplier can win a larger order by increasing his reliability, it is not always so with a price-taking firm.

Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.

Newsvendor problem with multiple unreliable suppliers

This paper focuses on supplier-related decisions in a newsvendor setting. We build upon the current literature by analysing the newsvendor problem with multiple unreliable and non-identical suppliers. We also incorporate both fixed ordering costs and capacity limits for supplier selection. We develop an exact algorithm to solve the problem optimally and a heuristic algorithm to solve the problem efficiently. Through structural properties of the optimal solution and a numerical study, we provide useful managerial implications regarding optimal sourcing strategies in complex supply chains. Previous literature concludes that with multiple unreliable (independent) suppliers, cost is the order qualifier and reliability is the order winner. We found that when fixed ordering costs and supply capacities exist, this insight no longer holds. We also examine the sensitivity of the sourcing decisions to supplier capacity levels, demand uncertainty, salvage value and shortage cost. Our results show that high levels of demand uncertainty lead firms to turn to a single-sourcing strategy whereas high salvage values and high shortage cost suggest multi-sourcing strategy.

A Markov decision process-based policy characterization approach for a stochastic inventory control problem with unreliable sourcing

Abstract We consider a single-product periodic-review inventory system for a retailer who has adopted a dual sourcing strategy to cope with potential supply process interruptions. Orders are placed to a perfectly reliable supplier and/or to a less reliable supplier that offers a better price. The success of an order placed to the unreliable supplier depends on his supply status that has a Markovian nature. The inventory control problem for this unreliable supply chain is modeled as a discrete-time Markov decision process (MDP) in order to find the optimal ordering decisions. Through numerical experimentation, the structure of the optimal ordering policy under several cost scenarios and different supplier reliability levels is determined. Four basic policy structures are found and are referred as case 1: order only from the unreliable supplier; case 2: order simultaneously from both suppliers or only from the unreliable supplier depending on the inventory level; case 3: order from one or the other but not both suppliers simultaneously; and case 4: order only from the reliable supplier. For all cases, ( s , S )-like policies characterize perfectly the optimal ordering decisions due to the existence of the fixed ordering cost. Further experimentation is done to study the effects of changes in several system parameters (cost parameters such as fixed ordering cost, unit purchasing cost, backorder cost as well as the supplier reliability level) on the ordering policy and cost of the system.

Ordering policies for a dual sourcing supply chain with disruption risks

Purpose: The main purpose of this article is to explore the trade-off between ordering policies and disruption risks in a dual-sourcing network under specific (or not) service level constraints, assuming that both supply channels are susceptible to disruption risks. Design/methodology/approach: Stochastic newsvendor models are presented under both the unconstrained and fill rate constraint cases. The models can be applicable for different types of disruptions related among others to the supply of raw materials, the production process, and the distribution system, as well as security breaches and natural disasters. Findings: Through the model, we obtain some important managerial insights and evaluate the value of contingency strategies in managing uncertain supply chains. Originality/value: This paper attempts to combine explicitly disruption management with risk aversion issues for a two-stage supply chain with two unreliable suppliers.

Managing Risk of Supply Disruptions: Incentives for Capacity Restoration

A supplier facing the prospect of disruption has to decide whether or not to invest in restoration capability. With restoration capability, if disruption occurs, additional costly effort can be exerted to rebuild capacity, although its outcome is uncertain. We study how a firm (buyer) can use incentive mechanisms to motivate a supplier's investment in capacity restoration, and compare this approach with the traditional approach of diversifying part of the order to an expensive but reliable supplier. Under a Restoration Enhancement (RE) strategy, the buyer uses price and/or order quantity incentives to encourage the supplier's restoration investment decision. Two different cases are considered—when the incentive is committed to ex ante (prior to disruption) and when it is committed to ex post (after disruption). In contrast, under a Supplier Diversification (SD) strategy, the buyer splits orders between a reliable supplier and an unreliable supplier to hedge against the disruption risk. Here, the buyer does not provide any separate incentive to the unreliable supplier. Our analysis indicates that under the RE strategy, where the buyer offers incentives, both the buyer and the supplier (weakly) prefer the ex ante commitment over the ex post one. Furthermore, the RE strategy is preferred over the SD strategy when the unreliable supplier's restoration outcome is more predictable or when a high restoration outcome is more likely. However, the buyer's preference for the SD strategy increases as market demand increases.

Compensating for Dynamic Supply Disruptions with Backup Flexibility

To increase resilience in supply chains, we investigate the optimal design of flexibility in the backup system. We model the dynamics of disruptions as Markov chains, and consider a multi-product, multi-supplier supply chain under dynamic disruption risks. Using our model, we first show that a little flexibility in the backup system can go a long way in mitigating dynamic disruption risks. This raises an important and fundamental question in designing flexibility in the backup system: to achieve the benefits of full backup flexibility, which unreliable suppliers should be backed up? To answer this question, we connect the supply chain to various queueing and dam models by analyzing the dynamics of the inventory shortfall process. Using this connection, we show that backing up suppliers merely based on first moment considerations such as their average reliability or average product demand can be misleading. All else equal, it is better to back up suppliers with (1) longer but less frequent disruptions, and (2) lower demand uncertainty. In addition to such second moment effects, by employing the Renyi's Theorem, we demonstrate that when disruptions are relatively long (if they occur), backing up the suppliers for which the expected wasted backup capacity is minimum provides the best backup flexibility design. We also develop easy-to-compute and yet effective indices that (a) guide the supply chain designer in deciding which suppliers to backup, and (b) provide insights into the role of various factors such as inventory holding and shortage costs, purchasing costs, suppliers reliabilities, and product demand distributions in designing backup flexibility.

Managing supplier delivery reliability risk under limited information: Foundations for a human-in-the-loop DSS

The potential impact of suppliers' delivery reliability issues in many industries requires a proper decision support system (DSS) that allows decision makers to analyze and reduce the delay's detrimental effects. Despite the relevance of the topic, companies are often confronted with the lack of historical, quantitative data and knowledge about a supplier's performance (i.e., when selecting a new supplier). In this paper, we address the problem of the scarcity of quantitative data by considering and extending the human-in-the-loop DSS concept, which accounts for an expert's knowledge and experience. In our concept, a human expert is involved in making and revising data provided by a computational model, with the aim of supporting companies in making decisions when dealing with unreliable suppliers, in order to minimize the costs related to external discontinuities. To deal with scant quantitative data, we developed a distribution-free model. Our findings positively support the distribution-free approach as an effective tool to be used when only a limited and perhaps unstructured base of data is available. The presented computational model aims at creating a solid foundation for developing a comprehensive human-in-the-loop decision support system.

Supply-Side Story: Risks, Guarantees, Competition, and Information Asymmetry

The risk of supply disruption increases as firms seek to procure from cheaper, but unproven, suppliers. We model a supply chain consisting of a single buyer and two suppliers, both of which compete for the buyer's order and face risk of supply disruption. One supplier is comparatively more reliable but also more expensive, whereas the other one is less reliable but cheaper and faces higher risk of disruption. Moreover, the risk level of the unreliable supplier may be private information, and this lack of visibility increases the buyer's purchasing risk. In such settings, the unreliable supplier often provides a price and quantity (P&Q) guarantee to the buyer. Our objective is to study the underlying motivation for the guarantee offer and its effects on the competitive intensity and the performance of the chain partners. Our model also includes a spot market that can be utilized by any party to buy or to sell. The spot market price is random, partially depends on the available capacity of the two suppliers, and has a positive spread between buying and selling prices. We analytically characterize the equilibrium contracts for the two suppliers and the buyer's optimal procurement strategy. First, our analysis shows that P&Q guarantee allows the unreliable supplier to better compete against the more reliable one by providing supply assurance to the buyer. More importantly, when information asymmetry risk is high, use of a guarantee may enable the unreliable supplier to credibly signal her true risk, thereby improving visibility into the chain. This signal can also be used by the buyer to infer the expected spot market price. In spite of these benefits, a guarantee offer in an asymmetric setting may not always be desirable for the buyer. Rather, it can reduce competition between the suppliers, resulting in higher costs for the buyer. This paper was accepted by Martin Lariviere, operations management.

Management Insights

Management Insights

Supplier diversification under random yield

We consider the problem of a retailer that is served by multiple suppliers, where any given supplier, who leads to random yield in orders, is defined to be unreliable. We examine how random yield affects the outcome of supplier selection and the retailer's profit in two cases: independent random yields (IRY) and correlated random yields (CRY). For the IRY, we show that the wholesale price generally takes precedence over reliability in the retailer's supplier selection, that is, a given supplier will be selected only if all less-expensive suppliers are selected, regardless of the given supplier's reliability level. For the CRY, we show that the results may be totally different from results obtained in the IRY. That is, a given supplier is selected but not all less-expensive suppliers are selected. Moreover, we examine the impacts of yield uncertainty on the retailer's profit. We show that the retailer might be better off under unreliable suppliers than under completely reliable suppliers.

Russia's International Images and its Energy Policy. An Unreliable Supplier?

In recent years, the Russian authorities have invested significant effort into promoting a positive image of Russia as an energy supplier. Yet, Russia's behaviour sometimes seems to contradict the declared aim of improving this image. A particularly interesting case is the way the Russian authorities and Gazprom handled the dispute with Ukraine over gas prices in December 2008–January 2009, when the transit of Russian gas to a number of EU member states via Ukraine was seriously affected. This essay argues that in order to understand Russia's position during the crisis, one should take into account the impact of international images on Russian politics, in particular self-images and constructed images that the Russian authorities have been projecting in the West and in Russia itself.

Investigating the barriers of using just in time purchasing system for publically traded firms in Tehran stock exchange

Article history: Received October 8, 2011 Received in Revised form November, 18, 2011 Accepted 22 November 2011 Available online 25 November 2011 Just in time is one of the most important components of having efficient production plan. The primary objective of JIT is to reduce the amount of storage as much as possible to remove the cost of inventories and work-in-progress. However, the implementation of JIT is a tedious task especially in developing countries, where there are shortages for essential infrastructures and increase the risk of production in case of JIT adaptation. In this paper, we present a survey to detect important factors preventing JIT implementation in Iran. The proposed study designs a questionnaire for assessing important factors influencing JIT adaptation, which includes inflation, political sanction, unreliable suppliers, shortage of cash flow and weak organizational culture. The results of our survey confirm that shortage of cash flow is the most important factor, follows by economical sanction and inflation.

OPTIMAL PROCUREMENT STRATEGY UNDER SUPPLY RISK

With the rapid expansion of global business, newer suppliers with cheaper but possibly unreliable technologies have entered the marketplace to win orders from buyer firms by beating the price of their perfectly reliable (but expensive) competitors. We model the procurement problem as a Nash game where the buyer has to allocate its purchases between an expensive but reliable supplier, and a cheaper but unreliable supplier. The suppliers specify prices for different proportions of the order awarded to them. Our analysis shows that, when perfect information is available about the reliability level of the unreliable supplier, the Nash equilibrium is a sole-sourcing allocation and that the supplier selection decision depends on the reliability and cost differentials between the two suppliers. In addition, we model the case when the buyer and the reliable supplier have limited information about the reliability of the unreliable supplier. Even in such an asymmetric scenario, the buyer's equilibrium allocation is a sole-sourcing outcome, but depending on system conditions either a separating or a pooling equilibrium is possible. An interesting insight into the effect of information asymmetry is that it can result in higher or lower profits/costs for the channel partners (compared to the perfect information case). As such, the buyer may even benefit from information asymmetry regarding unreliable supplier due to its impact on the degree of competition between the two suppliers.

Sourcing from suppliers with random yield for price-dependent demand

We study a multi-period inventory planning problem. In each period, the firm under consideration can source from two possibly unreliable suppliers for a price-dependent demand. Our analysis suggests that the optimal procurement policy is neither a simple reorder-point policy nor a complex one without any structure, as previous studies suggest. Instead, we prove the existence of a reorder point for each supplier. No order is placed to that supplier for any inventory level above the reorder point and a positive order is issued to that supplier for almost every inventory level below the reorder point. We characterize conditions under which the optimal policy reveals monotone response to changes in the inventory level. Furthermore, two special cases of our model are examined in detail to demonstrate how our analysis generalizes a number of well-known results in the literature.

Deriving the cost function of an integrated dyadic supply chain with uncertainty in the supply

This paper considers a dyadic supply chain with an uncertain supplier. Both the retailer and the supplier use continuous review policy. The supplier is randomly available for supplying the retailer. The retailer faces Poisson demands. In this system, lead time is a random variable consists of a constant transportation time plus a random delay occurs due to availability of stock at the supplier. In this paper, for the first time in the literature, we consider both the integrity and the uncertainty in the above supply chain. The main distinguishing characteristic of this paper, in comparison with the existing literature, is considering simultaneously two main concepts, namely the integration and unreliable supplier, through modelling the problem. We derive a good approximation for the total cost function of described system, using weighted mean costs of the one-for-one ordering policy. Finally, using simulation studies, we show that absolute errors are significantly ignorable.

Contributors

Contributors

In This Issue

In This Issue

Sharing demand and supply risk in a supply chain

This article studies two contract mechanisms to share demand and supply risk in a decentralized supply chain. In an option contract, the buyer reserves capacity with a supplier who guarantees delivery up to this limit. This insulates the buyer from any disruption risk, but the supplier faces both demand and supply risk. The second mechanism, the firm order contract, represents a conventional dyadic channel relationship where the buyer places a firm order and the supplier builds capacity but does not guarantee delivery if any disruption occurs. It is shown that the buyer's preference for using the different risk-sharing mechanisms switches back and forth (as the probability of disruption increases). Consequently, a supplier with a higher disruption risk may make higher expected profits compared to one with lower risk. In addition, the buyer may benefit from a higher wholesale price since it provides incentive for the supplier to participate without requiring the buyer to use higher order quantities. Two operational mitigation strategies that can be used by the buyer to hedge against the disruption risk are considered: the use of an alternate reliable supplier during a shortage and use of a direct subsidy for the supplier to improve reliability. It is found that the value of the reliable supplier depends on the type of contract with the unreliable supplier: interestingly, it is in the option contract—where supply is guaranteed—that the buyer almost always uses the reliable supplier as well. Also, it is found that offering a subsidy for reliability improvement acts as a strategic alternative to placing large pre-orders as a way to improve supplier operations.