Backup Supplier Research Articles

Resilience strategies in coping to disruptions of wheat supply chain caused by the Russia–Ukraine war crisis: case study from an emerging economy

PurposeThe Russia–Ukraine war has disrupted the wheat supply worldwide. Given that wheat is one of the most important agri-food products in the world, it is necessary to pay attention to the wheat supply chain during the global crises. The use of resilience strategies is one of the solutions to face the supply chain disruptions. In addition, there is a possibility of multiple crises occurring in global societies simultaneously.Design/methodology/approachIn this research, the resilience strategies of backup suppliers (BS) and inventory pre-prepositioning (IP) were discussed in order to cope with the wheat supply chain disruptions. Furthermore, the p-Robust Scenario-based Stochastic Programming (PRSSP) approach was used to optimize the wheat supply chain under conditions of disruptions from two perspectives, feasibility and optimality.FindingsAfter implementing the problem of a real case in Iran, the results showed that the use of resilience strategy reduced costs by 9.33%. It was also found that if resilience strategies were used, system's flexibility and decision-making power increased. Besides, the results indicated that if resilience strategies were used and another crisis like the COVID-19 pandemic occurred, supply chain costs would increase less than when resilience strategies were not used.Originality/valueIn this study, the design of the wheat supply chain was discussed according to the wheat supply disruptions due to the Russia–Ukraine war and its implementation on a real case. In the following, various resilience strategies were used to cope with the wheat supply chain disruptions. Finally, the effect of the COVID-19 pandemic on the wheat supply chain in the conditions of disruptions caused by the Russia–Ukraine war was investigated.

Coping with an unreliable supplier: An option contract with a backup supplier

AbstractThis study considers a channel with a retailer who satisfies demand by ordering from two suppliers: a low‐cost primary supplier whose production is subject to failure and an expensive reliable backup supplier. We develop a call option contract and evaluate the preference of each party through two negotiable scenarios: (i) the backup supplier only decides on option price and (ii) the backup supplier determines both option and exercise prices. We find that higher authority and flexibility of the backup supplier in making decisions in the second scenario results in a lower option price, yet more possibility of achieving channel coordination compared with the first scenario. While the backup supplier prefers the second scenario, the retailer would rather adopt the other one. The results also shed light on when/how the call option contract can be beneficial for each participant. Specifically, when the primary supplier is unable to supply the whole demand, the proposed option contract can be a win‐win Pareto‐improving profit‐sharing mechanism only if the likelihood of failure in the primary supplier's production is sufficiently low. Otherwise, the backup supplier may be a detrimental option for the retailer.

Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption

In order to mitigate the damage caused by natural disasters, appropriate relief supply planning is essential for humanitarian relief chains. This paper develops a resilient relief supply plan by formulating a novel integrated procurement-warehousing model under supply disruption via utilizing a portfolio of long-term contracts between a relief organization, multiple main and backup suppliers, and a third party who provides warehousing service. By using a portfolio of supply sources, a tailored two-stage scenario-based stochastic programming model is presented for determining an integrated relief procurement-warehousing plan. The plan includes (1) a number of multi-period quantity flexibility contracts with the main suppliers at pre-disaster, for prepositioning of relief supplies while ensuring to receive extra required amounts at post-disaster, (2) a number of dynamic option contracts with backup suppliers for decreasing the impacts of risks pertaining to the demand uncertainty and supply disruption at the main suppliers, and (3) a multi-period warehousing contract with a third party which allows the relief organization to adjust the required storage space in different periods to avoid extra cost pertaining to the storage space surplus/shortage. An effective differential evolution (DE) solution algorithm is also devised to solve the real scale instances efficiently. Applicability of the proposed model is illustrated by a real case study and useful managerial insights are extracted through conducting several sensitivity analyses.

Study on sustainable development of pharmaceutical health industry under ecological coordination.

Particularly in the post-pandemic period, where public health emergencies offer a greater risk of supply disruptions, the operational hazards of pharmaceutical supply chains are uncertain. One of the main concerns for businesses is how to handle the risk of supply disruption and take the necessary precautions to lower the chance of loss. Pharmaceutical raw material suppliers, pharmaceutical manufacturers and medical institutions constitute a complete three-tiered supply chain. On the basis of this, in Materials and methods part, a share contract based on buyback proceeds is created as a result, and a combination contract based on centralized decision-making and decentralized decision-making is employed to maximize the order volume of pharmaceutical supply chain participants. An out-of-stock cost pharmaceutical supply chain model is created, and a related solution is provided and measurable examples. In Results and discussion part, to confirm the accuracy of the model and algorithm, numerical examples are employed. Buyback prices and order volumes were subjected to sensitivity analysis, and discussion is had over how various parameters affect a model's performance. Due to supply disruptions, the study's findings show that there is "double sourcing" between upstream pharmaceutical raw materials and downstream major suppliers, necessitating the establishment of a supply chain with numerous standby suppliers. At the same time, modifying the contract parameters can improve the supply motivation of backup suppliers and guarantee the profitability of downstream medical institutions.

Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments

Supply chain (SC) resilience is imperative to cope with disruptions using some preparedness and recovery capabilities such as network redundancy (e.g., backup suppliers) and process flexibility (e.g., capacity agility). These capabilities frame an SC resilience portfolio. Both designing a resilient portfolio and recovering in case of a real disruption require investments. This paper presents a new mathematical model for designing an efficient resilience portfolio in a multi-echelon SC. Through computational and comparative analyses using a real-life case-study, we demonstrate that our model allows increasing resilience at minimal costs by determining an optimal combination of preparedness and recovery investments. Interestingly, the optimal solutions (i.e., efficient resilient SC designs) increase SC efficiency even in business-as-usual scenarios. This result contributes to the literature on transforming resilience from an expensive spend to a value-creation asset. We illustrate our approach using a real-life industrial example that allows for the identification of important relations between disruption duration/magnitude and efficiency of preparedness and recovery strategies. Based on computational, comparative, and case-study analyses, we deduce and generalize managerial implications at the network, supplier, and manufacturer levels. We take an extra step by extrapolating our major findings and generalized managerial implications toward the COVID-19 pandemic setting. The outcome of our research can be instructive for SC managers when deciding on investments in resilient redundancy allocation as a part of preparedness strategy and efficient recovery deployment.

Design of a robust closed-loop supply chain with backup suppliers under disruption scenarios

Design of a robust closed-loop supply chain with backup suppliers under disruption scenarios

Performance Assessment of Wheat Flour Suppliers Based on Balanced Scorecard (BSC)

Company Xis one of the companies in Indonesia that produces seasoned flour. This seasoned flour product uses the main raw material in the form of wheat flour. Company Xhas 3 suppliers of wheat flour raw materials used. In the process, there are problems with these suppliers in supplying wheat flour, including delays in the fulfillment of raw materials, the amount of raw materials sent does not match the demand, causing disruption to the production process, so Company Xneeds to evaluate suppliers of wheat flour to choose suppliers who the best that can be used so as not to interfere with the production process. In evaluating the performance of this supplier, the method used is the Balanced Scorecard in determining the criteria for supplier measurement indicators based on a financial perspective, a customer perspective, an internal business process perspective and a learning and growth perspective. This study aims to obtain the best supplier of wheat flour raw materials. Based on the results of the study, it shows that the best wheat flour supplier performance is the UPS supplier with a value of 148.09 meaning the company is satisfied with the UPS supplier performance because it is in the 80-160 value range so that it can be used as the main supplier in supplying wheatflour, then the ACL supplier. which gets a value of 151.37 which means that the company is also satisfied with the performance of the ACL supplier so that it can be used as a backup supplier

Sourcing decisions with uncertain time-dependent supply from an unreliable supplier

Recently, an increasing number of companies have encountered random production disruptions due to the COVID-19 pandemic. In this study, we investigate a two-stage supply chain in which a retailer can order products from a low-price (“cheap”) unreliable supplier (who may be subject to an uncertain production disruption and partially deliver the order) and an “expensive” reliable supplier at Stage 1 and a more “expensive” backup supplier at Stage 2. If the disruption happens, only the products that were produced before the disruption time can be obtained from the unreliable supplier. It is found that in the case with imperfect demand information updating, the unreliable supplier is always used while the reliable supplier can be abandoned. The time-dependent supply property of the unreliable supplier reduces the retailer's willingness of adopting the dual sourcing strategy at Stage 1, compared with the scenario with all-or-nothing supply. Different from the case with imperfect demand information updating, either the reliable or unreliable supplier can be abandoned in the case with perfect demand information updating. We derive the optimal ordering decisions and the conditions where single sourcing or dual sourcing is adopted at Stage 1. We conduct numerical experiments motivated by the sourcing problem of 3M Company in the US during the COVID-19 and observe that the unreliable supplier is more preferable when the demand uncertainty before or after the emergency order is higher. Interestingly, the retailer tends to order more from the unreliable supplier when the production disruption probability is larger in some cases.

A game-theoretic approach for power pricing in a resilient supply chain considering a dual channel biorefining structure and the hybrid power plant

This study investigates power pricing decisions in a resilient supply chain, including the main biomass supplier, biorefinery, the hybrid power plant, and the backup supplier. The power plant's main fuel is considered biofuel derived from Jatropha Curcas L. (JCL). However, due to unavoidable uncertainties in biofuel supply links, the shortage in meeting demand is inevitable. Therefore, for increasing the supply chain's resiliency, the fossil fuel backup supplier is taken into account to make up the shortage with anticipated fossil fuel. Due to environmental concerns, the penalty cost is considered for excessive use of fossil fuel. The model is studied under two cases by considering a dual-channel biorefining. Different game-theoretic models are established for varied power configurations and interactions of supply chain members. It is observed from the numerical study that, depending on the fractional part of the power plant's requirements of biofuel and JCL supplied by the biorefinery (Case 1) and the main supplier (Case 2), respectively the performance of the supply chain increases in the presence of the backup supplier. Additionally, the sensitivity analysis shows that Case 1 is more profitable than Case 2 for chain members. Moreover, in contrast to the fossil fuel replacement coefficient, the greater the convertibility degree of the JCL, the larger the profits for the members.

Supplier Audit Information Sharing and Responsible Sourcing

We develop a game-theoretic model to study the incentive for competing manufacturers to share supplier audit information. Based on the audit information, each manufacturer decides whether to source from a common supplier who has uncertain responsibility violation risk or to switch to a backup supplier who has no responsibility violation risk but charges a higher price. When supplier responsibility violation occurs, some consumers boycott the manufacturers involved. Audit information allows a manufacturer to reduce the uncertainty about the risk of the common supplier. We show that audit information sharing may make the manufacturers’ sourcing strategies more or less differentiated. As a result, the information-sharing decision is not monotone in the model parameters. We fully characterize the manufacturers’ equilibrium audit information-sharing and sourcing decisions and establish conditions under which audit information sharing induces the manufacturers to adopt more or less responsible sourcing strategies. We also show that a manufacturer could be better off when the cost premium of sourcing from the backup supplier or the risk of the common supplier becomes higher or the audit information becomes less accurate. We consider several extensions of the base model and demonstrate that the main insights remain mostly valid.This paper was accepted by Charles Corbett, operations management.Funding: A. Y. Hawas supported by the Wei Lun Foundation. W. Shang was supported by the Research Grants Council of Hong Kong [GRF Project LU 13501415]. Y. Wang was supported by National Natural Science Foundation of China [Grant 71901209].Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4358 .

Pharmaceutical supply chain reliability and effects on drug shortages

Drug shortages occur frequently and are often caused by supply chain disruptions. For improvements to occur, it is necessary to be able to estimate the vulnerability of pharmaceutical supply chains. In this work, we present the first model of pharmaceutical supply chain reliability. We consider three key approaches that companies may use to improve reliability: configuration, risk of disruptions, and speed of recovery. Key metrics include expected drug shortages, average time-to-shortage, and average time-to-recovery. We parametrize the model using data from major drug shortage databases and a case example of a generic injectable oncology drug. With a lean supply chain configuration, we observe that expected shortages at status quo conditions are 10%. By either doubling the speed of recovery or halving the disruption rate, expected shortages could drop to 5%. The most influential single change would be to add a back-up supplier to a lean configuration, leading to expected shortages of 4%. We also consider profitability and present the breakeven prices for different configurations. The results from our analyses could lead to immediate policy impact, providing evidence of the benefits of redundancy and improving facility quality.

Designing a sustainable closed-loop supply chain network considering lateral resupply and backup suppliers using fuzzy inference system.

Sustainability is key factor for transforming traditional supply chain networks into modern ones. This study, for the first time, considers the impacts of the backup suppliers and lateral transshipment/resupply simultaneously on designing a Sustainable Closed-Loop Supply Chain Network (SCLSCN) to decrease the shortage that may occur during the transmission of produced goods in the network. In this manner, the fuzzy multi-objective mixed-integer linear programming model is proposed to design an efficient SCLSCN resiliently. Moreover, the concept of circular economy has been studied in this paper to reduce environmental effects. This study aims to optimize total and environmental costs, including energy consumption and pollution emissions, while increasing job opportunities. A demand uncertainty component is considered to represent reality more closely. Due to the importance of demand, this parameter is estimated using the Fuzzy Inference System (FIS) as an input into the proposed mathematical model. Then, the fuzzy robust optimization approach is applied in a fuzzy set’s environment. The model is tackled by a Multi-Choice Goal Programming Approach with Utility Function (MCGP-UF) to be solved in a timely manner, and the equivalent auxiliary crisp model is employed to convert the multi-objective function to a single objective. The proposed model is tested on the case study of the tire industry in terms of costs, environmental impacts, and social effects. The result confirmed that considering the concept of lateral resupply and backup supplier could considerably decrease the total costs and reduce shortages on the designed SCLSCN. Finally, sensitivity analysis on some crucial parameters is conducted, and future research directions are discussed.

Newsvendor models with random supply capacity and backup sourcing

We consider newsvendor models with a primary supplier whose production is subject to random capacity. In order to hedge against this supply risk the retailer contracts with a reliable backup supplier to reserve capacity in advance, acquiring the option to use it after the delivery from the primary supplier and either before or after the demand realization. For both cases we identify the conditions under which the use of the backup supplier is beneficial and characterize the optimal order and reservation quantities. Furthermore, we examine how these optimal procurement quantities are affected by various model parameters.

Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study

This paper presents a multi-portfolio approach and scenario-based stochastic MIP (mixed integer programming) models for optimization of supply chain operations under ripple effect. The ripple effect is caused by regional pandemic disruption risks propagated from a single primary source region and triggering delayed regional disruptions of different durations in other regions. The propagated regional disruption risks are assumed to impact both primary and backup suppliers of parts, OEM (Original Equipment Manufacturer) assembly plants as well as market demand. As a result, simultaneous disruptions in supply, demand and logistics across the entire supply chain is observed. The mitigation and recovery decisions made to improve the supply chain resilience include pre-positioning of RMI (Risk Mitigation Inventory) of parts at OEM plants and ordering recovery supplies from backup suppliers of parts, located outside the primary source region. The decisions are spatiotemporally integrated. The pre-positioning of RMI implemented before a disruptive event is optimized simultaneously with the RMI usage and recovery supply portfolios for the backup suppliers in the aftermath periods. The recovery supplies of parts and production at OEM plants, are coordinated under random availability of suppliers and plants and random market demand. The resilient solutions for the resilient supply portfolios are compared with the non-resilient solutions with no recovery resources available. The findings indicate that the resilient measures commonly used to mitigate the impacts of region-specific disruptions can be successfully applied for mitigation the impacts of multi-regional pandemic disruptions and the ripple effect.

Selection of Alternative Suppliers Using Analytical Hierarchy Process dan Technique For Order Preference By Similarity To Ideal Solution

Garment industry is an industry that focuses on manufacture of clothing. Along with the times, development model and function clothing is increasingly varied. Company’s effort is determine best supplier. Based on observations in Central Java garment industry, it was found problems related to continuity of fabric supply from major suppliers. When demand soars, demand for cloth supply also increases. However, the availability of fabric supplies owned by main suppliers is not able to meet the needs of garment industry. Therefore, garment industry requires alternative backup suppliers who are able to meet the supply of fabric when the main supplier is inadequate. Supplier selection will be carried out using the Analytical Hierarchy Process (AHP) method in weighting and Technique for Others Preference by Similarity to Ideal Solution (TOPSIS) method in ranking priority order of suppliers. This supplier priority will be used as an alternative supplier that will meet the availability of fabric supply.

Product Flexibility Strategy Under Supply and Demand Risk

Problem definition: With heightened global uncertainty, supply chain managers are under increasing pressure to craft strategies that accommodate both supply and demand risks. Although product flexibility is a well-understood strategy to accommodate risk, there is no clear guidance on the optimal flexibility configuration of a supply network that comprises both unreliable primary suppliers and reliable backup suppliers. Academic/practical relevance: Existing literature examines the value of flexibility with primary and backup suppliers independently. For a risk-neutral firm, research shows that (a) incorporating flexibility in a primary supplier by replacing two dedicated ones (in absence of backup supply) is always beneficial and that (b) adding flexibility to a reliable backup supplier (in absence of product flexibility in primary suppliers) is always valuable. It is unclear, however, how flexibility should be incorporated into a supply network with both unreliable primary suppliers and reliable backup suppliers. This research studies whether flexibility should be incorporated in a primary supplier, a backup supplier, or both. Methodology: We develop a normative model to analyze when flexibility benefits and when it hurts. Results: Compared with a base case of no flexibility, we prove that incorporating flexibility in either primary or backup suppliers is always beneficial. However, incorporating flexibility in both primary and backup suppliers can be counterproductive because the supply chain performance can decline with saturated flexibility, even if flexibility is costless. A key reason is that the risk-aggregation effect of consolidating flexibility in an unreliable supplier becomes more salient when flexibility is already embedded in a backup supplier. Managerial implications: This research refines the existing understanding of flexibility by illustrating that flexibility is not always beneficial. When there is a choice, a firm should prioritize incorporating flexibility in a reliable backup supplier.

Benefits of backup sourcing for components in assembly systems under supply uncertainty

We consider an assembly system for a final product consisting of multiple components. The assembler orders each component from its primary supplier, and one of the components is subject to supply uncertainty in which the actual available quantity for assembly is only equal to a random fraction of the order quantity. After this actual available quantity is realized but before assembly for meeting final demand, the assembler can procure additional components from some backup suppliers. We derive the optimal ordering policy under this backup sourcing strategy and analyze the benefits of using backup suppliers in mitigating the adverse effect of supply uncertainty in component procurement from the primary suppliers. Our result shows that the availability of backup supplier for the component with supply uncertainty can provide very substantial benefits to the assembler, especially when the unit cost of this component from the primary supplier is high relative to the extra unit component cost from the backup supplier for high-margin products under an operating environment of high supply uncertainty and low demand uncertainty. We further show that the availability of backup suppliers for the other components with no supply uncertainty can provide additional significant benefits to the assembler when extra unit component cost of backup supplier for the unreliable component supplier is high for low-margin products with high demand uncertainty.

A resilient supply chain network for an online retailer: a three-phase robust framework and a case study

This paper proposes a three-phase robust approach to the problem of designing a supply chain in an e-tailing environment considering the resilience strategies such as fortification, backup suppliers, and transshipment. First, the scores of potential suppliers are obtained using several resilience criteria. Then, a scenario-based stochastic network design model is proposed which considers operational (demand and transfer cost) and disruption (a natural disaster) risks. Finally, an order transfer problem is solved. The results prove the effectiveness of the framework for a case study. A preferred Pareto optimal solution of the robust optimization model is selected such that its cost is only 0.15% worse than its neighbour while its score of suppliers is 2.46% greater than the mentioned point. In addition, the results of the sensitivity analysis show that although the suppliers with higher scores costs more, they have a smaller cost range.

Simulation-based assessment of supply chain resilience with consideration of recovery strategies in the COVID-19 pandemic context

In the wake of the COVID-19 pandemic, many firms lacked a strategy to cope with disruptions and maintain resiliency. In this study, we develop a measurement method to evaluate the impact of resilience strategies in a multi-stage supply chain (SC) in the presence of a pandemic. For the first time, we propose a method to deduce quantitative resilience assessment from simulation. We implement two resilience strategies, i.e., prepositioning extra-inventory and a backup supplier, and then we simulate its impact on SC resilience and financial performance. The simulation results indicate that the extra inventory leads to a higher resilience than a backup supplier but costs more for the given contextual setting. Finally, we examine the demand fulfillment and observe that the extra-inventory strategy allows for a higher service level, confirming our resilience simulations. We discuss the managerial implications of these findings on the descriptive and predictive analysis levels. Decision-makers can utilize our model and findings to develop a response plan in the occurrence of a pandemic or any long-duration high magnitude disruption. Also, scholars and managers can use our proposed method to measure SC resiliency from simulation in any disruption.

Integrating lean, resilient, and sustainable practices in supply chain network: mathematical modelling and the AUGMECON2 approach

Nowadays, organisations try to find a proper method to increase their competitiveness. Lean, resilient, and sustainable are top-hole managerial practices in supply chain management. This paper tries to study the effects of integrating lean, resilient, and sustainable practices in the supply chain network (SCN). To this end, a new multi-objective mixed-integer programming is developed in such a way that lean manufacturing is implemented in a resilient-sustainable SCN. The objective functions try to maximise job opportunities and minimise costs, environmental effects, and delivery time. Resilience has been taken into account to tackle the lack of raw materials during disruptions by implementing multiple sourcing in the model. Besides, to devote more attention to sustainable practices, backup suppliers have been prioritised based on sustainability criteria. The academics were enquired to rate sustainability criteria for selecting a backup supplier. Finally, a fuzzy TOPSIS method was used to rank the backup suppliers based on sustainability criteria. The improved version of augmented ϵ-constraint (AUGMECON2) was applied to cope with multi-objectivity of the problem. The results indicated a synergistic effect among leanness, resilience, and sustainability in the supply chain. Also, it turned out that sustainable backup supplier selection boosts the synergistic effect among these three concepts.