Supply Risk Mitigation Research Articles

Leaching of exhausted LNCM cathode batteries in ascorbic acid lixiviant: a green recycling approach, reaction kinetics and process mechanism

AbstractBACKGROUNDCritical metals (lithium, cobalt and nickel) used in Li‐ion batteries have been estimated to face a supply crunch by the end of 2020 due to their limited natural reserves and complex metallurgy. A green recycling approach to treat the exhausted batteries may potentially mitigate supply risks of metals and environmental burden of metal toxicity.RESULTSThe maiden application of bio‐producible/degradable ascorbic acid for the leaching of LiNi xCo yMn zO2 (LNCM) cathode batteries was investigated while performing parametric variations. Inhibited leaching at high temperature and long contact time showed the adversity caused by the possible decomposition of ascorbic acid. The low leaching of cobalt as a function of acid concentration indicated the hindrance in dissolution of Co(III) compound. A quantitative leaching of metals (≥96%) could be achieved under the following optimal conditions: agitation speed, 500 rpm; acid concentration, 2.0 mol L−1; temperature, 75 °C; time, 90 min; and pulp density, 6%. The apparent activation energy of metals was calculated to be more than 40 kJ mol−1.CONCLUSIONAscorbic acid could potentially dissolve the cathode material without introducing any additional reducing agent into the system. The leaching kinetics fitted with an empirical model {−ln(1 − x)}2 versus t could reveal that the overall dissolution process follows a chemically controlled mechanism. The present study leads towards sustainable metallurgy using a biodegradable reagent instead of applying harsh and hazardous mineral acids. © 2020 Society of Chemical Industry

Supply Risk Mitigation in a Decentralized Supply Chain: Price Postponement or Payment Postponement?

In a multi-stage model of a bilateral supply chain, we study two postponement strategies that the downstream retailer may deploy to mitigate the supply yield risk originated from the upstream production process. The retailer could either postpone the procurement payment until after the yield is realized and pay only for the delivered amount, or postpone the pricing decision to better utilize the available supply, or do both. Due to the decentralized setting, the timing of the payment and pricing will have a ripple effect and generate system-wide implications on the channel performance. Taking a game theoretic approach, we formulate a Stackelberg game and solve for the equilibrium in four scenarios respectively, in which the retailer uses different combination of the aforementioned postponement strategies. There are three main findings. First, when the production cost is low and the yield loss is highly likely, the retailer never strictly benefits from either postponement strategy; otherwise, the retailer is more likely to deploy payment, rather than price, postponement. Second, we uncover a situation where postponing price and payment are strategic complements for the retailer. That is, the use of one strategy may increase the benefit of using the other. Third, we identify conditions on the production cost and the random yield distribution, under which the postponement strategies can be Pareto optimal to the entire supply chain, making the firms' profits and the consumer surplus simultaneously higher. These results can be applied in many practical settings to provide guidance to effectively mitigate supply yield risk. Specifically, they may help a firm better design the procurement contract and properly use marketing instrument (pricing) to mitigate supply risk and increase profit.

Drop-Shipping and Backup-Sourcing Strategies Under the Risk of Supply Disruption

In recent years, an increasing number of e-retailers have adopted drop-shipping strategy to save logistics costs, and used backup-sourcing strategy to mitigate supply risks. However, the existing literature ignores the significant relationship between the two strategies. In this study, we develop a multi-stage game-theoretical model to investigate the optimal procurement decisions for an e-retailer who can activate both drop-shipping and backup-sourcing strategies. Specifically, our model considers the e-retailer sourcing some units of a product from a supplier to meet the random demand of online customers. The units of the product are held by the supplier, and then are directly shipped to the customers from the supplier side (i.e., drop-shipping strategy). However, there is disruption risk for the supplier; thus, after the randomness of the supplier is realized, the e-retailer can urgently order some units of the product from an expensive but perfectly reliable outside option (i.e., backup-sourcing strategy). We examine the optimal order decisions of the e-retailer and the optimal wholesale price decision of the supplier. Our study shows that for the retailer, the activation of both backup-sourcing and drop-shipping strategies increases its profit, and there is substitutability between the two strategies. For the supplier, the implementation of the drop-shipping (backup-sourcing) strategy increase (decreases) its profit, but the drop-shipping and backup-sourcing are complementary strategies. For the supply chain, when the logistics cost is low or high and the backup-sourcing cost is low, the backup-sourcing and drop-shipping are complementary strategies, whereas in other cases, they are substitutive strategies. Our study not only brings some academic contributions to supply chain management, but also provides significant management insights for the operational practice in terms of drop-shipping and backup-sourcing.

Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: a research note

Firms have learned how to strengthen the resilience of their global supply chains (SC) to confront disruptions triggered by severe disasters. However, a new instigator of SC disruption, quite unlike any seen in recent times, has now emerged – the COVID-19/SARS-CoV-2 virus. We model the ripple effect of an epidemic outbreak in global SCs considering the velocity of pandemic propagation, the duration of production, distribution and market disruption, and a demand decline. We analyse pandemic supply risk mitigation measures and potential recovery paths. Implications for future research and global SC (re)-designs are also discussed.

Platinum Demand and Potential Bottlenecks in the Global Green Transition: A Dynamic Material Flow Analysis.

Platinum, as a key catalytic material, is important for the global green transition due both to its current main use in autocatalysts and its increasing use in emerging and renewable energy technologies such as fuel cells and electrolyzers. In this study, we developed a dynamic material flow analysis model to characterize the global platinum cycle between 1975 and 2016 and to develop scenarios for future global platinum demand to 2050. Our results show that the autocatalyst and jewelry uses represent the most primary platinum use and possess the highest platinum stocks in use by 2016; however, when closed loop recycling is considered, the gross platinum demand from the glass industry would be the largest. Many socioeconomic (e.g., population and car ownership) and technological (e.g., engine and energy technologies) factors will affect the future demand for platinum in a global green transition. Our analysis concludes that, only in high demand scenarios and when fuel cell market penetration is high compared to the expected, the aggregate demand to 2050 will exceed the 2016 global platinum reserves. Improving the end of life collection and recycling rates would be important to address potential future supply risks due to geopolitical reasons. These demand scenarios and further mapping of the global platinum value chain can help inform government and industry policies on transportation and energy transition, platinum supply risk mitigation, and recycling capacity planning and technology development.

Building supply-side resilience – a behavioural view

PurposeTo build resilient supply chains, buyers should implement risk mitigation tactics. The purpose of this paper is to provide insights into the risky decision-making process that underlies buyers’ decisions to adopt supply risk mitigation tactics for creating supply-side resilience.Design/methodology/approachThe authors employ experimental scenarios to simulate supply disruptions of low and high likelihood. The authors then assess buyers’ decisions to adopt supply risk mitigation tactics in response to these scenarios.FindingsThe authors find that buyers’ perceptions of supply disruption likelihood are positively related to their adoption of buffer- and process-oriented risk mitigation tactics and preference for process-oriented risk mitigation tactics. Conversely, risk propensity negatively affects buyers’ adoption of buffer- and process-oriented mitigation tactics.Originality/valueBeyond risk perceptions, the authors consider how risk propensity also affects the risky decision-making process. Moreover, whereas previous studies often focus on a single mitigation tactic, the authors study buyers’ adoption of multiple buffer- and process-oriented risk mitigation tactics to create supply-side resilience.

Gibbs Energy Minimization Model for Solvent Extraction with Application to Rare-Earths Recovery.

The emergence of technologies in which rare-earth elements provide critical functionality has increased the demand for these materials, with important implications for supply security. Recycling provides an option for mitigating supply risk and for creating economic value from the resale of recovered materials. While solvent extraction is a proven technology for rare-earth recovery and separation, its application often requires extensive trial-and-error experimentation to estimate parameter values and determine experimental design configurations. We describe a modeling strategy based on Gibbs energy minimization that incorporates parameter estimation for required thermodynamic properties as well as process design for solvent extraction and illustrate its applicability to rare earths separation. Visualization analysis during parameter estimation revealed a linear relationship between the standard enthalpies of the extractant and respective organo-metal complexes, analogous to the additivity principle for predicting molar volumes of organic compounds. Establishing this relationship reduced the size of the parameter estimation problem and yielded good agreement between model predictions and reported equilibrium extraction data, validating the property estimates for the organic phase species. Design exploration and optimization results map the space of feasible solvent extraction column configurations and identify the set of optimal design parameter values that meet recovery and purity targets.

Potential Contribution of Secondary Materials to Overall Supply - The Example of the European Cobalt Cycle

Higher efficiency in raw material recycling is discussed as a key strategy to decrease the environmental impact of resource consumption and to improve materials’ availability in order to mitigate supply risks. However, particularly in the case of technology metals, demand is driven by specific emerging technologies from which recycling will not be possible before the end of their useful lifetimes. Hence, the availability of secondary materials is limited by the amount of obsolete products as well as their collection, separation and treatment during waste management and recycling. In this paper, we present the results of a dynamic material flow model for cobalt as a key raw material for lithium-ion batteries at an European level (EU28). This model aims at quantifying the current state of recycling and future recycling potentials from end-of-life (EoL) product flows. While it is expectable that obsolete large battery packs from (hybrid) electric vehicles will be efficiently collected in future, EoL Li-ion battery flows will remain dominated by smaller electronic equipment (smartphones, laptops etc.) in the coming years and the model results show a significant potential for improvements in collection and material recovery from EoL batteries in Europe. A major challenge will be the collection of smaller batteries and Waste Electrical and Electronic Equipment (WEEE) in general from which a significant share of total European cobalt demand could be recovered in the coming years.

Operational supply risk mitigation of SME and its impact on operational performance

PurposeThe purpose of this paper is to investigate how buyer–supplier social capital may help mitigate operational supply risk (OSR) of small- and medium-sized enterprises (SMEs). It empirically examines a framework that posits the direct and mediated impacts of three dimensions of buyer–supplier social capital – structural, relational and cognitive – and supplier integration on the OSR of SMEs and consequently their operational performance.Design/methodology/approachThis study uses data collected via a questionnaire from 485 manufacturing SMEs in Bangladesh for analysis using structural equation modeling.FindingsThe analysis reveals that all the three dimensions of buyer–supplier social capital can effectively reduce the OSR of SMEs, either directly or indirectly through supplier integration. The mediating role of supplier integration in the relationship between social capital and OSR is confirmed and the negative impact of OSR on operational performances of SMEs is verified.Research limitations/implicationsGeneralization of the findings needs to be prudent since the study gathered information only from manufacturing SMEs in Bangladesh on the buyer side of the buyer–supplier dyad.Practical implicationsFindings of this study can provide references for SME practitioners to formulate their OSR mitigation strategies for enhancing operational performance.Originality/valueThis study adds to the currently scarce literature on OSR of SMEs by combining antecedents and consequences of OSR in a single framework. It also extends the use of buyer–supplier social capital to risk mitigation research.

A Multi-Criteria Decision Analysis Approach to Facility Siting in a Wood-Based Depot-and-Biorefinery Supply Chain Model

As the lignocellulosic biofuels industry is still developing, reducing operational and capital costs along the supply chain can increase the competitiveness of the final fuel price and investor willingness to commit funds. Capital cost savings may be realized through co-locating depots with active biomass processing plants, such as saw mills, and through repurposing existing industrial facilities, such as pulp mills, into a biorefinery. Operational cost savings may be gained through the selective siting of depots and biorefineries based on operational cost components that vary geospatially, such as energy rates and feedstock availability. Utilizing depots in a biofuel supply chain to procure and preprocess feedstock has additionally been found to mitigate supply risk in regions of low biomass availability, as well as reduce the biorefinery footprint. A multi-criteria decision support tool (DST) is developed utilized to assess existing industrial facilities for their potential role in a wood-based depot-and-biorefinery supply chain. Geospatial cost components are identified through techno-economic analyses for use as siting criteria for the depots and biorefinery. The “repurpose potential” of industrial facilities is assessed as a siting criterion for candidate biorefinery locations. A case study is presented in the Inland Northwest region of the United States to assess the usefulness of the tool in selecting industrial facilities for a configured depot-and-biorefinery supply chain. The results are compared against optimization runs of the candidate facilities to validate the depots selected by the DST. In two of the three supply chains, the DST selected the same or similar facilities as the optimization run for no net increase in annual cost. The third supply chain showed an approximately 1% increase in annual cost over the optimized facilities selected.

Risk Analysis and Mitigation Using SCOR -Fuzzy ANP

Objective: To identify the supply risk and determine the mitigation strategies that can be applied. Methods: The first method used to analyze risk is SCOR, then risk assessment with fuzzy-FMEA method. The method which can be used is to analyze the risk weight by using Fuzzy method, then selected 80% of the risk that has the highest weight. Furthermore, the data is used to formulate risk mitigation strategy using Fuzzy ANP method. Results: The results of the study showed 80% risk with the highest weight. The results of this research found that the highest risk in the cultivation department is the risk of procedural errors in the process of manufacturing, maintenance or cultivation. While the highest risk for the manufacturing department is the risk of experiencing delays in the supply of mushrooms. Alternative strategies for supply risk mitigation on the part of the cultivation department such as consistent Standard operate procedure OP implementation strategies, timely pickup, and optimization of transportation availability, improvement and improvement of nursery planning. Alternative strategies for supply risk mitigation on the part of manufacturing such as increased communications and inter-division coordination, improved raw material fulfillment, increasing SOP tuning frequency, improvements and optimization of machine. Application: It is concluded that fuzzy FMEA can be used to analysis risk supply accurately and fuzzy ANP can formulate the risk mitigation strategy to support supply performance of high quality and high value selling canned mushroom products. Keyword: Fuzzy-ANP, Fuzzy-FMEA, Mitigation, Supply, Supply Chain Operator Reference (SCOR), Risk

Mitigating supply risk: an approach with quantity flexibility procurement

This paper considers a buyer that procures from its major supplier whose production is subject to random yield risk. To mitigate supply risk, the buyer can procure from another reliable supplier who provides quantity flexibility (QF) contract. Under both deterministic and stochastic demand, we study the buyer’s optimal procurement decisions. We analyze the structural properties of optimal solutions and identify the conditions under which the quantity flexibility procurement policy should be used. We also examine the effect of supply risk, flexibility, wholesale price and demand risk on the procurement decisions. We find that the higher supply risk and demand risk reduce the buyer’s profit but have different impact on the buyer’s order policy. For the QF supplier, it may not obtain more orders by providing larger flexibility to the buyer, on the contrary, doing this may benefit the risky supplier. For the QF supplier or risky supplier, given its competitor’s wholesale price, it can increase its order share by lower wholesale price.

Markov-modulated analysis of a spare parts system with random lead times and disruption risks

Spare parts supply chains are highly dependent on the dynamics of their installed bases. A decreasing number of capital products in use increases the nonstationary supply-side risk especially towards the end-of-life of capital products. This supply-side risk appears to present itself through varying lead times coupled with supply disruptions. To model the nonstationary supply-side risk, we consider an exogenous Markov chain that modulates random lead times and disruption probabilities. Assuming that order crossovers do not occur, we prove the optimality of a state-dependent base stock policy. Later, we conduct an impact study to understand the value of considering stochastic lead times and supply disruption risk in spare parts inventory control. Our results indicate that the coupled effect of random lead times and disruptions can be larger than the summation of individual effects even for moderate lead time variances. Also, the effect of nonstationarity on total cost can be as large as the summation of all risk factors combined. In addition to this managerial insight we present a procedure for supply risk mitigation based on an empirical model and our mathematical model. Experiments on a real business case indicate that the procedure is capable of reducing costs while making the inventory system more prepared for disruptions.

Extending the geopolitical supply risk method: material “substitutability” indicators applied to electric vehicles and dental X-ray equipment

While environmental LCA is relatively well developed, impact assessment methods for the “natural resources” AoP are weak. In particular, resource “criticality” is not addressed in conventional environmental impact assessment methods, though it could be captured within life cycle sustainability assessment. In that regard, the present article extends the previously developed geopolitical supply risk (GPSR) method by demonstrating the connection of criticality to a functional unit while incorporating measures of material substitutability to reflect the “vulnerability” dimension of criticality. The GPSR method developed by Gemechu et al. (J Ind Ecol 20:154–165, 2015a) and subsequently extended by Helbig et al. (J Clean Prod 137:1170–1178, 2016a), and Cimprich et al. (J Clean Prod, 2017) is integrated into an LCIA characterization model. Further, semi-quantitative material substitutability indicator values based on a study by Graedel et al. (PNAS 112:6295–6300, 2015) are incorporated to represent the vulnerability dimension of criticality. The method is demonstrated with an update of a previously published case study of a European-manufactured electric vehicle by Gemechu et al. (Int J Life Cycle Assess 22:31–39, 2015b), along with a new case study of dental X-ray equipment. Due to novel aspects of the GPSR method, the latter case involves constructing an unusually comprehensive bill of materials by tracing unit processes to input commodities with identification codes for collecting commodity trade data. Supply risk “hotspots” are often associated with “minor” commodities such as neodymium in an electric vehicle and cesium iodide in a dental X-ray system. Though difficult to measure, material substitutability can mitigate supply risk. Environmental loads of a dental X-ray system are dominated by production of relatively small specialized functional components like capacitors and printed circuit boards, which are far more environmentally intensive per unit of mass than common structural and mechanical components. Thus, small components comprised of minor materials can “pack a punch” from a supply risk and environmental perspective. The GPSR method presented in the present article brings resource criticality assessment to a product-level while addressing a gap in conventional LCIA methods regarding short-run, socioeconomic availability of natural resources. Further, the case studies illustrate the significance of material substitutability in supply risk assessment. Several complications and limitations of the GPSR method offer directions for future research. Nonetheless, the GPSR method complements environmental LCA to better inform design and management decisions on a product-level.

Supply Risk Mitigation Via Supplier Diversification and Improvement: An Experimental Evaluation

Due to the trend towards decentralization and greater complexity in supply chains, companies are increasingly exposed to supply risks. Various strategies to mitigate supply risks have been developed using modeling- based approaches, including risk diversification by dual sourcing and direct investment to improve supplier performance. Yet, despite the overwhelming evidence that managerial decisions are influenced by behavioral factors particularly under risk and uncertainty, such behavioral factors are typically not considered by previous theoretical studies. In this paper, we use controlled lab experiments to evaluate the performances of dual sourcing and single sourcing with supplier improvement strategies to mitigate risks of a buyer facing suppliers with different costs and risk profiles, and develop behavioral theories to elucidate the decision-making process under supply risks more effectively. With dual sourcing, human buyers do not diversify their orders effectively (relying on a more even allocation of orders between suppliers than theory suggests) and exhibit quantity hedging behavior. To explain this phenomenon, we propose and empirically validate a behavioral theory in which human buyers choose order quantities to minimize their disutility from order allocation errors between suppliers. Human buyers use the single sourcing with supplier improvement strategy relatively effectively, despite being subject to supplier selection errors due to bounded rationality.

Wholesale Price Auctions for Dual Sourcing under Supply Risk

ABSTRACTWholesale price bids commonly occur in procurement auctions where dual sourcing is usually employed to mitigate supply risks. When at most two winners are required, unreliable wholesale price bidders face the unique trade‐off between unit margin and quantity allocation that depends on both winners' bids and the reliabilities. Motivated by above facts and considerations, we investigate several auction formats accommodating wholesale price bids for dual sourcing under newsvendor market, with unreliable suppliers possessing private costs. Generalized first‐price auction (GFA) is designed under known cost distribution, while generalized English auction (GEA) and optimal auction with learning (OAL) are examined under unknown distribution. Through a preannounced allocation rule to curb the bidding behavior, both GFA and OAL balance information rent and quantity allocation and generate various diversification degrees. Information asymmetry under GFA depresses the quantity proportion for high‐cost winner, because he charges higher unit information rent than low‐cost winner does. In contrast, two winners in GEA collude at the same price and thus split the order quantity evenly. The full diversification possibly enables GEA to generate higher service level than GFA under high supply risk, although the expected output quantity of GEA is always lower. Regarding the practical requirement for auction format choice, when the costs of implementation and distribution acquisition are not negligible, the previous analysis suggests that the favorable format is driven from GFA or OAL to GEA, as supply risk or the number of bidders increases, or as retail price exceeds a threshold. We also extend to multisourcing cases and examine the impacts of salvage and lost sale on auction format choice.

Bridging and buffering: Strategies for mitigating supply risk and improving supply chain performance

The area of buyer-supplier risk management is increasingly drawing the attention of academicians and professionals. However, less focus has been given to identifying the right mitigation strategy (specifically, bridging and buffering) for firms having different strategic orientations (such as, prospector, defender and analyzer). To this end, we review the literature and present a theoretical model grounded in strategic choice theory that explores how firms operating in different business environments respond to buyer-supplier risk by adopting appropriate mitigation strategies. The relationship between buyer and supplier is influenced by motivating factors (for example, trust and dependence) as they are the key elements of social exchange theory. Based on a sample of 184 responses from a survey with Indian organizations, we validate the theoretical model and test the research hypotheses using structural equation modelling. Findings reveal that the decision of firms to adopt a particular mitigation strategy varies with the environment in which the firm operates and this decision is majorly influenced by motivating factors. Another interesting finding shows that these mitigation strategies help the firms in managing buyer-supplier risk and enhancing downstream supply chain performance.

The Coevolution of Relationship Dominant Logic and Supply Risk Mitigation Strategies

How and why do risk mitigation strategies evolve? And which resources are needed for engaging in such changes? This paper contributes to the understanding of risk management in supply chains by developing theory about the interplay between supply risk mitigation strategies and the purchasing team's relationship dominant logic (RDL), which we define as the purchasing team's orientation toward and shared cognitive map of the management of its supply chain relationships. Specifically, we propose that RDL and supply risk mitigation strategies are fundamentally intertwined. Following a Straussian approach to grounded theory, this study analyzes data generated from the purchasing teams of Western green‐tech firms trying to mitigate supply risk for technically indispensable rare earth metals from China. Our findings from this context that is heavily shaped by state‐influenced supply chain members show that the firms chose their mitigation strategies in line with their RDL. Human capital, social capital, and financial capital seem to moderate the link between RDL and mitigation strategies. We link our findings with the strategic management literature in deriving theoretical propositions concerning these relationships.

Supply risk mitigation: a multi-theoretical perspective

Due to the increasing level of supply risk, it is imperative to obtain a better understanding of the nature of risk which is a premise to developing well-grounded risk mitigation strategies. This paper examines how to mitigate supply risk enlightened by discussing the concept of risk in association of three closely related concepts which are uncertainty, variability and trust. The proposed three perspectives are supported and explained using four case studies comprising of two manufacturers based in Australia and four suppliers based in China. The study provides evidence that supply risk can be mitigated by high level of information and knowledge sharing as well as building trust, commitment and goal congruence in a buyer–supplier relationship. It offers theoretical and managerial implications.

Risk Mitigation Benefit from Backup Suppliers in the Presence of the Horizontal Fairness Concern

ABSTRACTThe backup supply strategy is demonstrated as an effective approach to mitigating supply risk. We study a supply chain in which a leader manufacturer designs a contract to a potential backup supplier to mitigate the yield uncertainty of the primary supplier. In this context, the backup supplier may compare with the primary supplier and have horizontal fairness concerns. We model the contract design problem using a Stackelberg game and characterize the optimal decisions for the manufacturer and backup supplier, in both fairness and off‐fairness settings. The theoretical results show that the leader manufacturer must sacrifice his own payoff to balance the payoffs of both suppliers. As a result, using a self‐interested backup supplier is the dominating strategy, whereas using a fair‐minded backup supplier is only suggested when the reliability of the primary supplier is low and the fairness concern of the backup supplier is not strong. Additionally, the backup supplier only benefits from fairness concerns when the level is not exceeding a threshold value. With regard to high fairness levels beyond this threshold, fairness concern has negative effects on the monetary payoff and even might lead to loss of the business. By conducting laboratory experiments, we provide evidence of the horizontal fairness concern from the backup supplier. Further, we show that if the primary supplier also has horizontal fairness concerns, the leader manufacturer can conditionally benefit from a promoted yield reliability due to an extra effort from the primary supplier.