Demand Disruptions Research Articles

Pricing Mechanism With Noncooperative Game and Revenue Sharing Contract in Electricity Market.

In this paper, a pricing mechanism is proposed for the electricity supply chain, which is consisting of one generation company (GC), multiple consumers, and competing utility companies (UCs). The UC participates in electricity supply chain management by a revenue sharing contract (RSC). In the electricity supply chain, the electricity real-time balance has an important role in the stable operation of the power system. Therefore, we introduce the demand response into the electricity supply chain to match supply with demand under forecast errors. Hence, we formulate a noncooperative game to characterize the interactions among the multiple competing UCs, which set the retail prices to maximize their profits. Besides, the UCs select their preferred contractual terms offered by the GC to maximize its profits and coordinate the electricity supply chain simultaneously. The existence and uniqueness of the Nash equilibrium (NE) are examined, and an iterative algorithm is developed to obtain the NE. Furthermore, we analyze the RSC that can coordinate the electricity supply chain and align the NE with the cooperative optimum under the RSC. Finally, numerical results demonstrate the superiority of the proposed model and the influence of market demand disruptions on the profits of the UCs, GC, and supply chain.

Examining price and service competition among retailers in a supply chain under potential demand disruption

Supply chain disruptions management has attracted significant attention among researchers and practitioners. The paper aims to examine the effect of potential market demand disruptions on price and service level for competing retailers. To investigate the effect of potential demand disruptions, we consider both a centralized and a decentralized supply chain structure. To analyze the decentralized supply chain, the Manufacturing Stackelberg (MS) game theoretical approach was undertaken. The analytical results were tested using several numerical analyses. It was shown that price and service level investment decisions are significantly influenced by demand disruptions to retail markets. For example, decentralized decision makers tend to lower wholesale and retail prices under potential demand disruptions, whereas a proactive retailer needs to increase service level with an increased level of possible disruptions. This research may aid managers to analyze disruptions prone market and to make appropriate decision for price and service level. The manufacturer or the retailers will also be able to better determine when to close a market based on the proposed analysis by considering anticipated disruptions. The benefits and usefulness of the proposed approach are explained through a real-life case adopted from a toy supply chain in Bangladesh.

Allocation flexibility for agribusiness supply chains under market demand disruption

This paper develops a multi-commodity multi-period optimisation model to analyse market demand disruption risk in agribusiness supply chains. It investigates the role of allocation flexibility and the effectiveness of multiple risk management strategies for achieving allocation flexibility. A robust optimisation formulation is used to obtain risk-averse solutions for an objective combining expected profit and risk. Numerical results are presented for a real-life case study of Zespri’s kiwifruit supply chain. The results show that allocation flexibility is effective for mitigating market demand disruption risk. Three proposed risk management strategies, namely diversified demand market, backup demand market and flexible rerouting, improve both expected profit and risk measures. While diversified demand market and backup demand market strategies are equally important for all decision-makers, flexible rerouting is especially significant for less risk-averse decision-makers.

Decision on risk-averse dual-channel supply chain under demand disruption

We studied dual-channel supply chains using centralized and decentralized decision-making models. We also conducted a comparative analysis of the decisions before and after demand disruption. The study shows that the amount of change in decision-making is a linear function of the amount of demand disruption, and it is independent of the risk-averse coefficient. The optimal sales volume decision of the disturbing supply chain is related to market share and demand disruption in the decentralized decision-making model. The optimal decision is only influenced by demand disruption in the centralized decision-making model. The stability of the sales volume of the two models is related to market share and demand disruption. The optimal system production of the two models shows robustness, but their stable internals are different.

Information sharing for competing supply chains with demand disruption

We investigate pricing decisions and information value in two competing supply chains, each consisting of one manufacturer and one retailer. Both retailers are engaged in Bertrand retail competition and are endowed with the private information on the disrupted demand. Three information sharing scenarios have been considered, i.e. , information sharing in both chains, information sharing in only one chain, and information sharing in neither chain. For each information scenario, there always exists robustness for each manufacturer’s production plan. That is, when the disrupted amount of the market demand is sufficiently small, the manufacturer’s production plan or the retailer’s order quantity will be unchanged. Meanwhile, we also study the information value by comparing these three information scenarios, and find that the information value not only works in one chain directly, but also does in the competing chain indirectly. Through comparative analysis, we find that the retailer is reluctant to share his private information on the disrupted demand with his partner because of the fear of information leakage. Meanwhile, the performance of the whole chain may become worse off if the information of disrupted demand is shared in this chain.

Optimal ordering policies in a multi-sourcing supply chain with supply and demand disruptions-a CVaR approach

In this study, we propose a conditional value at risk (CVaR) model for supply chain disruptions planning of a multi-agent, multi-product supply chain subject to supply and demand disruptions. Our focus is on building and comparing ordering policies under CVaR and expected cost criteria. The proposed formulation is illustrated through some numerical instances. The results present that the CVaR model shows a considerable difference in response policies compared to the expected cost model. Ordering quantities in response to supply and demand disruption are lower in the CVaR model than the expected cost model. In many instances, it is also seen that ordering quantities in response to disruptions tend to become lower when a decision maker becomes more risk-averse. It is expected that the proposed CVaR model would outperform to optimise the supply chain of an organisation, in particular, for the purpose of reducing the risk of high cost.

Turn bad into good: Using transshipment-before-buyback for disruptions of stochastic demand

This paper presents a general characterization of demand disruption in the supply chain for stochastic consumer demand, which has an increasing generalized failure rate. A heuristic transshipment-before-buyback (TBB) contract is developed for the managers of both manufacturers and retailers to enable them to benefit from the demand disruption. A TBB contract is theoretically shown to be better than a classical pure buyback contract, which has the same buyback price as the TBB contract. Our results also show that, in the presence of a buyback promise, the transshipment price has no impact on the manufacturer's incentive to induce retailers to undertake transshipment. In addition, the manufacturer has an incentive to meet part of the transshipment cost when it is sufficiently large. This effect is greater when the manufacturer is loss averse.

Information Disclosure Model Under Supply Chain Competition with Asymmetric Demand Disruption

This paper develops the game models of two symmetric supply chains, each consisting of one manufacturer and one retailer, while both retailers compete in the market with a linear function. The disclosure mechanism is designed when the information of the disrupted demand is asymmetric between supply side and retail side. We first study the model with the full information as a benchmark to explore the effect of asymmetric information on the system. In the case, each manufacturer maximizes her profit while the downstream retailer only obtains the reservation profit. For the case of asymmetric information, each manufacturer can obtain the real information of the disrupted demand by using a menu of contract bundles. For each information structure, there are always robust regions for each manufacturer’s original trading quantity scheme. That is, when the disrupted amount of the demand is sufficiently small, the trading quantity will be unchanged. However, some special measures, e.g., the higher unit wholesale price, should be taken to prevent the retailer from deviating the trading quantity scheme. The high-disruption retailer gets the higher profit due to the information rent. Compared with a single supply chain, Cournot competition results in the less retail price and the lower performance for the whole system.

Market disruptions in supply chains: a review of operational models

AbstractMarket disruptions are unplanned and unanticipated events, which may further influence the flow of goods and materials within a supply chain. In view of the increasing significance of market disruptions in industries, in this paper, we review a selection of related papers that focus on market disruptions in the supply chain. We classify the literature into three aspects, namely, demand disruption, supply disruption, and supply chain disruption risk. We review the representative operational models in each aspect. We derive insights into the current state of knowledge in each area. We suggest three future research directions: (a) Can supply chain structure help reduce disruption risk? (b) How does information asymmetry influence the supply chain in the presence of disruption? (c) How does social welfare vary in the presence of disruption? In conclusion, this paper provides up‐to‐date information to both researchers and practitioners to better identify, manage, and control market disruptions.

The influences of demand disruption on logistics service supply chain coordination: A comparison of three coordination modes

There are few studies on the influences of demand disruption on logistics service supply chain (LSSC) coordination in previous literature. Therefore, this paper will discuss an LSSC consisting of a logistics service integrator (LSI) and two functional logistics service providers (FLSPs) with demand disruption. LSI procures the same kind of logistics service capacity from these two FLSPs, sets a unified price and then sells to service market. The demand depends on retail price and service effort level. As different FLSPs may achieve different effort levels, which bring them different order quantities, there is competition on effort level between them. With all these conditions considered, three coordination modes (i.e. decentralized decision-making mode, supplier alliance decision-making mode and centralized decision-making mode) are established and compared. On this basis, demand disruption is taken into consideration and the corresponding decision changes are observed. Some interesting findings are obtained. For example, from the view of service effort level, supplier alliance decision-making mode makes FLSPs achieve lower effort level than decentralized decision-making mode does; from the view of decision robustness, when demand disruption occurs frequently, decisions made under supplier alliance decision-making mode changes less than those made under decentralized decision-making mode. At last, model application is deployed to verify the conclusions with a practical case of SND Logistics Company in China.

Coordination of supply chain with a dominant retailer under government price regulation by revenue sharing contracts

As the demands of some important products such as oil, gas, and agricultural commodities are disrupted, the government often regulates the retail price that includes impositions of a price ceiling and a price floor. In this paper, we analyze the coordination of a supply chain with a dominate retailer under the government price regulation policy by a revenue sharing contract after demand disruption. First, we characterize the optimal decisions of the supply chain under normal circumstance by the revenue sharing contract as a benchmark. Then, when the demand is disrupted, we redesign the contract to coordinate the supply chain and obtain the corresponding revenue sharing contract in different scenarios. Finally, we give some numerical examples to illustrate our theoretical results and explore the impacts of government price regulations on the coordination mechanism.

Collaborate or not? A system dynamics study on disruption recovery

Purpose – The purpose of this paper is to investigate different combinations of collaboration strategies to deal with different types of supply chain disruptions, find the best combination, and provide targeting suggestions for investments. Design/methodology/approach – A system dynamics simulation is applied to study a supply chain with three tiers: a producer, a logistics service provider (LSP), and a retailer. There are three types of disruptions to simulate: a producer capacity disruption, an LSP capacity disruption, and a demand disruption. As each tier has the option to choose whether or not to collaborate with the other two tiers, eight (2×2×2) scenarios are generated to represent different combinations of collaboration strategies. Findings – For a producer capacity disruption, both the producer and the LSP should collaborate by providing their surge capacities, while the retailer does not have to collaborate. For an LSP capacity disruption, the producer should not provide its surge capacity, while...

Disruption management in a two-period three-tier electronics supply chain

AbstractWe study strategies to manage demand disruptions in a three-tier electronics supply chain consisting of an Electronics Manufacturing Services provider, an Original Equipment Manufacturer (OEM), and a Retailer. We model price sensitivity of consumer demand with the two functions commonly used for this purpose, linear and exponential, and introduce disruptions in the demand function. We assume each supply chain member faces an increasing marginal unit cost function. Our decentralized supply chain setting is governed by a wholesale price contract. The OEM possesses greater bargaining power and therefore is the Stackelberg leader. A penalty cost incurred by the Retailer is introduced to capture the cost of deviation from the original plan. We find exact analytical solutions of the effectiveness of managing the disruption when the consumer demand function is linear, and we provide numerical examples as an illustration when the consumer demand function is either linear or exponential. We show that the o...

Informed Principal Model and Contract in Supply Chain with Demand Disruption Asymmetric Information

Because of the frequency and disastrous influence, the supply chain disruption has caused extensive concern both in the industry and in the academia. In a supply chain with one manufacturer and one retailer, the demand of the retailer is uncertain and meanwhile may suffer disruption with a probability. Taking the demand disruption probability as the retailer’s asymmetric information, an informed principal model with the retailer as the principal is explored to make the contract. The retailer can show its information to the manufacturer through the contract. It is found out that the high-risk retailer intends to pretend to be the low-risk one. So the separating contract is given through the low-information-intensity allocation, in which the order quantity and the transferring payment for the low-risk retailer distort upwards, but those of high-risk retailer do not distort. In order to reduce the signaling cost which the low-risk retailer pays, the interim efficient model is introduced, which ends up with the order quantity and transferring payment distorting upwards again but less than before. In the numerical examples, with two different mutation probabilities, the informed principal contracts show the application of the informed principal model in the supply chain with demand disruption.

Dynamic Analysis and Optimization of a Production Control System under Supply and Demand Uncertainties

This study investigates the dynamic performance and optimization of a typical discrete production control system under supply disruption and demand uncertainty. Two different types of uncertain demands, disrupted demand with a step change in demand and random demand, are considered. We find that, under demand disruption, the system’s dynamic performance indicators (the peak values of the order rate, production completion rate, and inventory) increase with the duration of supply disruption; however, they increase and decrease sequentially with the supply disruption start time. This change tendency differs from the finding that each kind of peak is independent of the supply disruption start time under no demand disruption. We also find that, under random demand, the dynamic performance indicators (Bullwhip and variance amplification of inventory relative to demand) increase with the disruption duration, but they have a decreasing tendency as demand variance increases. In order to design an adaptive system, we propose a genetic algorithm that minimizes the respective objective function on the system’s dynamic performance indicators via choosing appropriate system parameters. It is shown that the optimal parameter choices relate closely to the supply disruption start time and duration under disrupted demand and to the supply disruption duration under random demand.

Demand disruption and coordination of supply chain via effort and revenue sharing

This article explores the equilibrium behaviour of a basic supplier–retailer distribution channel under demand disruption via effort and revenue sharing contract. This differs from the traditional supply chain coordination model. Firstly, demand is simultaneously affected by retail price and nonprice marketing effort from manufacturers and retailers. Secondly, when the demand is disrupted, this article considers disruptions in the market scale and price sensitivity coefficient. Thirdly, the supply chain coordination model is proposed via effort and revenue sharing contract. In this way, the manufacturer reduces the wholesale price as an incentive for the retailer to share revenue. Finally, the total supply chain profit is greater with contract than no contract. This also constitutes another incentive for the players to follow the effort and revenue sharing contract.

Solar + storage: A holistic view

SUNVERGE CEO, Kenneth Munson, explains how using energy storage can build resilient utility business models, capture benefits across the energy supply chain and cope with demand disruption.

Coordinating a Dual-Channel Supply Chain Under Equal-price Mechanism When Demand Disruption Occurs

This paper studies a two-stage dual-channel supply chain composed of one manufacturer and one traditional retailer. The manufacturer has its own online channel when he sells its product to the offline retailer. There exists a Stackelberg game between the manufacturer and the traditional retailer, in which the manufacturer is the leader and the traditional retailer is the follower. The manufacturer sets the online retail price which is the same as the offline retail price. When the supply chain is in static (undisrupted) scenario, its Pareto improvement can be obtained and it can be coordinated by the two-part-tariff contract with one-time transfer payment. When disruptions make the market scale change, the supply chain performance such as the optimal retail price, the optimal production quantity and the optimal total supply chain profit under different demand disruptions in the centralized supply chain can be obtained. Then, we find that there exists certain robustness in the manufacturer’s production quantity. When the supply chain is decentralized, the supply chain coordination can be obtained by changing the wholesale price and one-time transfer payment according to different disruption levels. Finally, some numerical examples are presented to illustrate the results.

Resilience of multi-hospitals network based on the collaborative scheduling

Disasters always cause tremendous injuries and medical resources demands in a short period, while improving resilience of hospital network can help to quickly recover from disruptions. Based on biological cell elasticity theory, this paper assimilates the hospital network to the cellular tissue. And we define an indicator of multi-hospitals network resilience that quantifies the ability of hospital network to react to the medical resources demand disruptions due to natural or human-caused disaster. And a collaborative scheduling model of resources in the network is put forward as the reactive strategy to improve the resilience of the hospitals network against disasters. Finally, numerical examples are given to illustrate the resilience concept and assess the effectiveness of the collaborative scheduling.

Robustness Comparison of Three Dual-channel Supply Chain Structures under Demand Disruptions

Comprehensive comparisons of optimal pricing and ordering policies in different supply chain (SC) structures under demand disruptions still lacks. Three two-echelon dual-channel SC structures with different cooperation modes are raised first. And the decision robustness of them under demand disruptions are compared and sequenced. Results show that a partially vertically integrated SC structure has the best robustness, whereas the centralized SC structure, which is considered to be the most profitable, has the worst robustness.