Supply Chain Uncertainty Research Articles

Sustainability and optimization methods under uncertainties in closed-loop supply chain

Due to the environment-friendly attribution and cost-saving potential of remanufacture, many original equipment manufacturers (OEMs) commence taking it as part of production strategy. While the inherent uncertainties in closed-loop supply chain (CLSC) add to the difficulty in operational management. As the first case on the coupling effect of multi-uncertainties, the paper carries out analyses of eight critical uncertainties and quantifies the impacts on the whole CLSC. Based on mathematical derivation and followed by numerical experiments, the results demonstrate that by formulating appropriate remanufacture-up-to ratio, OEMs are able to adjust the relationship between supply and demand indirectly, and then strike an optimal balance to maximize the economic benefits under multi-uncertainties. The conclusion drew from this study provides a scientific support for practitioners to develop production strategies for optimal material efficiency and sustainable industrial development in CLSC.

Framework Development for The Assessment of The Supply Chain Resilience Using The House of Risk

The COVID-19 pandemic has created uncertainty and disruptions in Supply Chain (SC), which has caused many researchers to re-study Supply Chain Risk Management (SCRM) to deal with risks due to the pandemic. Moreover, the direction of post-pandemic SCRM research is more toward Supply Chain Resilience (SCRes) which is the ability of a supply chain to prepare for disruptions and return to normalcy. Many researchers have started researching SCRes to carry out SC recovery measures. However, research on the quantification of SCRes is still rare and is an opportunity. One of the risk quantification methods in the SCRM field is the House of Risk (HoR). This study develops a SCRes assessment framework with the help of the HoR. HoR has two stages, namely: HoR1 for identifying the risks and HoR2 for mitigating the risks. In this study, one step was added, namely the level assessment stage of resilience. The resilience profile is calculated based on the risk map and mitigation plan. This study succeeded in providing a framework for assessing the level of resilience using the help of HoR. Meanwhile, only an illustrative case study is used. Our future research is on how to apply the proposed resilience assessment framework to a real case. Keywords: supply chain, risk management, supply chain resilience, house of risk, framework

Quality risk and responsive actions in sourcing/procurement: an empirical study of food fraud cases in the UK

It is never an easy task to govern contemporary food systems and prevent contaminated foods from reaching further down the chains. This study aims to investigate how UK managers in food supply chains have perceived food fraud risk in their supply chain and to identify what their actions could be in response to the threat of food fraud. The study adopts the psychometric paradigm approach to measure risk perception and uses the data collected from 113 UK food practitioners to identify the determinants of their responsive actions. The results highlight that most managers have perceived high uncertainty in the food supply chain and considered the disruption of information flow as a major concern in dealing with food fraud. Therefore, this study suggests that putting effort into practices to improve supply chain visibility and facilitate the flow of information are weighted as important in the food fraud mitigation journey. Policy makers should also make better use of the current quality assurance schemes for proactive food quality control and fraud prevention; government agencies should improve the risk communication systems for trustworthy information dissemination.

Supply chain informed principal model with quality uncertainty and information asymmetry in green supply chain

In the green supply chain, due to factors such as technical level and capital investment, quality uncertainty often occurs. At the same time, manufacturers often know more about the uncertainty than the retailers they serve. To address the concerns raised above, we apply the informed principal model and consider a two-echelon green supply chain consisting of one unreliable manufacturer and one retailer. The manufacturer, as the principal, has private information about the green degree, while the retailer only knows its prior probability. We first study the underlying model under symmetric information. Then, under the information asymmetry, we construct a low-information-density model and an interim-efficient model. Finally, the numerical comparison results show that our propositions are valid. The results show that the low-information-density model can eliminate the information asymmetry, but it imposes high signaling cost on the high-quality manufacturer. The interim-efficient model can indeed reduce the cost and the distortion of the wholesale quantity. Moreover, it is worth mentioning that there is a specific threshold for the retailer's prior probability. When the prior probability is greater than this threshold, the interim-efficient model is better than the low–information-density model; otherwise, they are equivalent. Simultaneously, the higher the prior probability, the higher the manufacturer’s revenue. If the manufacturer wants to obtain more benefits, he must increase the retailer's trust by operating with integrity and building a brand effect.

PENGARUH SUPPLY CHAIN MANAGEMENT TERHADAP OPERASIONAL PERUSAHAAN DAN KENDALA PROCUREMENT SISTEM ERP PADA PT UNILEVER INDONESIA TBK

This research aims to determine the effect of Supply Chain Management and constraints of existing ERP systems in PT Unilever Indonesia Tbk is a company engaged in the household production industry by offering food products, beverages, kitchen needs, to toiletries. In an effort to develop its business operations, it is known that PT Unilever Indonesia Tbk implements its management strategy through ERP and Supply Chain Management systems. The ERP system at PT Unilever Indonesia Tbk functions as an information integration tool for all company stakeholders, while Supply Chain Management functions as a tool for monitoring the flow of goods to consumers and the amount of inventory. Thus, the two strategies are related to the certainty of the performance of Unilever employees. This paper aims to analyze the performance and the relationship between supply chain management, and the effect of the ERP system implemented by Unilever companies on operational performance through interaction and communication of information in order to be efficient in implementing supply chain management strategies and ERP systems. The research method uses a document study approach, as well as primary and secondary data collection techniques. The results of the study reveals that the Supply Chain Management strategy of PT Unilever Indonesia Tbk has four components, namely supply chain uncertainty, management of economies of scale, selection of transportation modes, and product inventory control; as well as the ERP and Supply Chain Management systems of PT Unilever Indonesia Tbk have a positive and significant impact on the company's performance so as to obtain profits and achieve company goals.

Impacts of production, transportation and demand uncertainties in the vaccine supply chain considering different government subsidies

Vaccine supply chain is a complex system. In the vaccine supply chain, there are lots of uncertainties in the design and production, delivery and demand of vaccines, in particular, with the continuous mutation of the virus, the components of the vaccine need to be updated in time. These uncertainties may result in huge losses to vaccine manufacturer and retailer. Thus, the government often provides the different subsidies respectively to the producing end or the purchasing end in vaccine supply chain so that the members can own sustainability. Motivated by the above, in this paper, we describe the uncertain characteristics of the vaccine supply chain and consider the different government subsidies. We aim to study the production and pricing decision problems of manufacturer and retailer. Late Rebate contract is one of the commonly used contracts in the vaccine supply chain. Thus, we consider Late Rebate contract in this paper and introduce government subsidies, which are divided into three situations: no subsidy, subsidized manufacturer, and subsidized retailer. We mainly explore whether the different government subsidies can improve the profits of vaccine manufacturer and retailer. Comparing the equilibrium profits of subsidizing manufacturer and subsidizing retailer with the benchmark under no subsidy, the conclusions are that subsidizing retailer can improve the profits of supply chain members, while subsidizing manufacturer cannot achieve this effect. The conclusions in this paper provide guidance and suggestions for the government and decision-makers.

Decision-Making Behaviour Evolution Among Pork Supply and Demand Subjects Under Normalisation of COVID-19 Prevention and Control: A Case Study in China.

Affected by the coronavirus disease 2019 (COVID-19), there were short-term uncertainties in China's live pig industry supply chain. Due to the insufficient supply of pork, the price of pork rose from 33.21 yuan/kg at the end of 2019 to 37.46 yuan/kg in mid-February and fell to 26.41 yuan/kg in mid-May. To restore pig supply and stabilise prices, China issued relevant policies. Given the current effective control of COVID-19 in China, this paper constructed an evolutionary game model of China's pork supply and demand stakeholders under normalisation of COVID-19 prevention and control, analysed the behavioural strategies of consumers, government, and pig farmers, used MATLAB software for data simulation, and expounded on the evolution path and the characteristic rule of tripartite decision-making behaviours. The results showed that government supervision costs, evaluation of government by consumers and pig farmers, government subsidies to pig farmers and consumers, and the proportion of stakeholder behaviours affected the formation of tripartite relationships. The results provide a useful reference for the government to formulate effective policies, increase pig supply, and stabilise pork prices.

Inventory planning under supplier uncertainty in a two-level supply chain

PurposeDue to uncertainty in supply chains caused by the coronavirus disease 2019 (COVID-19), organizations are adjusting their supply chain design to address challenges faced during the pandemic. To safeguard their operations against disruption in order quantities, supply chain members have been looking for alternate suppliers. This paper considers a two-level supply chain consisting of a manufacturer and two suppliers of a certain type of components required for the production of a finished product. The primary supplier (supplier A) is unreliable, in the sense that the quantity delivered is usually less than the ordered quantity. The proportion of the ordered quantity delivered by supplier A is a random variable with a known probability distribution. The secondary supplier (supplier B) always delivers the order in its entirety at a higher cost and can respond instantaneously. In order for supplier B to respond instantaneously, the manufacturer is required to reserve a certain quantity at an additional cost. Once the quantity received from the main supplier is observed, the manufacturer may place an order not exceeding the reserved quantity.Design/methodology/approachA mathematical model describing the production/inventory situation of the supply chain is formulated. The model allows the determination of the manufacturer's optimal ordering policy.FindingsAn expression for the expected total cost per unit time function is derived. The optimal solution is determined by solving a system of nonlinear equations obtained by minimizing the expected total cost function.Practical implicationsThe proposed model can be used by supply chain managers aiming at identifying various ways of handling the uncertainty in the flow of supplies across the chain.Originality/valueThis proposed model addresses a gap in the production/inventory literature.

Planning a circular economy system for electric vehicles using network simulation

The fast-growing market for electric vehicles (EVs) offers great potential for reducing the carbon footprint of the transportation sector but is heavily reliant on electric motors and batteries, which are in turn dependent on the availability of critical materials, e.g., rare earth elements and lithium. Such critical materials are subject to substantial supply chain risk, indicating a potential lack of source materials to meet EV production. To ameliorate this supply chain uncertainty that may compromise the economic competitiveness of EVs, it is essential to establish an end-of-life (EoL) infrastructure that is focused on closing the material loops within the EV life cycle, thus achieving a circular economy. However, there is a lack of research devoted to enabling technologies and supporting tools to design the reverse logistic chain for EVs that considers EoL processing of components in a holistic manner. To close this knowledge gap, this study develops a stochastic activity network to simulate an EV renewal system (EVRS) that has the goal of rebuilding used EVs and extracting maximum value from EoL EV components and materials. Based on the simulation outputs, the process flow and economic performance of the proposed system are enhanced through operation optimization and pricing optimization. The results indicate the technical viability of the EVRS from an operational standpoint and suggest its promising economic potential in industrial practice. As industries around the globe transition to a circular economy, the proposed network simulation framework has enormous potential to be adapted to other products and scenarios to provide decision support in system planning.

A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain

The worldwide COVID-19 pandemic sparked such a wave of concern that made access to vaccines more necessary than before. As the vaccine inaccessibility in developing countries has made pandemic eradication more difficult, this study has presented a mathematical model of a sustainable SC for the COVID-19 vaccine that covers the economic, environmental and social aspects and provides vaccine both domestically and internationally. It has also proposed a robust data-driven model based on a polyhedral uncertainty set to address the unjust worldwide vaccine distribution as an uncertain parameter. It is acceptably robust and is also less conservative than its classical counterparts. For validation, the model has been implemented in a real case in Iran, and the results have shown that it is 21% less conservative than its classical rivals (Box and Polyhedral convex uncertainty sets) in facing the uncertain parameter. As a result, the model proposes the construction of two domestic vaccine production centers, including Pasteur Institute and Razi Institute, and five foreign distributors in Tehran, Isfahan, Ahvaz, Kermanshah, and Bandar Abbas strategically.

Interaction of capacity utilization and inventory efficiency: the moderating role of information sharing

ABSTRACT This paper is aimed at verifying the existence of the systematic contradictions between inventory efficiency (IE) and capacity utilization (CU), two critical indicators of firm performance, in the manufacturing industry and the role of information sharing with supply chain partners in weakening the contradictions through empirical analysis. Raw material and finished goods inventory are studied respectively, and the underlying mechanism is established for each. With a cross-sectional dataset, we estimate systems of simultaneous equations with the three-stage least square (3SLS) method to investigate the interacting effects and further conduct the estimation on subsamples grouped by the moderator to study the moderating effects. The study confirms a significant two-way negative relationship between IE and CU and documents a significant negative moderating effect of sharing demand forecast with raw material suppliers on the interaction between raw material inventory efficiency (RMIE) and CU. The findings suggest managers keep in mind that the two operational objectives cannot be achieved at the same time dealing with supply chain uncertainty and take into account the costs and benefits of capacity and inventory when choosing strategies. They can also improve this situation by cooperating with supply chain partners to share information like demand forecast with them.

Modelling Underload Cascading Failure and Mitigation Strategy of Supply Chain Complex Network in COVID-19

The outbreak of COVID-19 has caused problems such as shortage of workforce, cost increase, cash flow tension, and uncertainty of supply chain. It has a specific negative impact on the raw material supply, procurement management, production resumption, logistics, and market of the supply chain, which can trigger cascading failures in supply chain networks. Aiming at the failure of upstream/downstream firms in supply chain networks due to the decreased product demand/material supply under the COVID-19, the present study adopted an underload cascading failure model for the supply chain networks. In this model, the hierarchical supply chain networks were constructed based on the Erdos Renyi (ER) model and Barabasi Albert (BA) model. The validity of the model was verified under random attack and target attack. In the random attack mode, the influences of model parameters were studied, and in the target attack mode, the influence of target protection and random protection measures on enhancing network invulnerability was also studied. Simulation results showed that the initial load and capacity lower bound of nodes impact cascading failure size. The former has a positive correlation with cascading failure size, while the latter negatively correlates with cascading failure size. Furthermore, random protection measures are more practical to prevent cascading failures.

Inventory availability commitment under uncertainty in a dropshipping supply chain

Dropshipping, where e-retailers manage marketing and dropshippers manage inventory and fulfillment, has become a common practice in e-commerce. However, due to information asymmetry, some e-retailers require dropshippers to share available inventory quantity committed to them on a periodic basis (x-hour, day,...), via an availability commitment. Such commitment leaves the potential for dropshippers to overpromise and exploit availability pooling benefit as it does not involve physical transaction. To further prevent fulfillment failure, some e-retailers stop accepting more orders once remaining promised quantity falls below a promised availability threshold, which is unknown to the dropshipper. In this paper, leveraging the collaboration with a dropshipping furniture manufacturer in the US market, we tackle the inventory availability commitment (IAC) problem for dropshippers at the operational decision level. Three commitment policies are proposed based on varying overpromising allowance: guaranteed fulfillment, controlled fillrate, and penalty-driven fillrate policies. The IAC optimization problem, under uncertain customer demand and retailers threshold, is modeled as a two stage stochastic program. Experimental results on a case study demonstrated that penalty-driven fillrate policy is a dominating policy for a dropshipper under any availability level while the impact of overpromising is maximized under lean availability. E-retailers imposing thresholds tend to receive more availability than those not imposing any threshold in general. However, non-overpromising dropshippers with lean or lower availability level will promise less availability to e-retailers imposing threshold.

Sustainable Integrated Fuzzy Optimization for Multimodal Petroleum Supply Chain Design with Pipeline System: The Case Study of Vietnam

Over the years, oil-related energy sources have played an irreplaceable role in both developed and developing countries. Therefore, the efficiency of petroleum supply chains is a key factor that significantly affects the economy. This research aimed to optimize the configuration of the uncertainty multimodal petroleum supply chain in terms of economy, energy and environment (3E assessment). This study proposes a novel integration methodology between a heuristic algorithm and exact solution optimization. In the first stage, this study determines the facilities’ potential geographical coordinates using heuristic algorithm. Then, the fuzzy min-max goal programming model (FMMGPM) was developed to find the multi-objective solutions. In particular, this model allows analysis of supply chain uncertainty through simultaneous factors such as demand, resource, cost and price. These uncertainty factors are expressed as triangular fuzzy parameters that can be analyzed in terms of both probability and magnitude. Moreover, the model is applied to the entire petroleum supply chain in Vietnam, including downstream and upstream activities. In addition, another novelty is that for the first time, pipeline systems in logistics activities are considered in Vietnam’s petroleum supply chain optimization study. The results also show the short-term and long-term benefits of developing a pipeline system for oil transportation in Vietnam’s petroleum supply chain. To evaluate the effects of uncertainty on design decisions, this study also performed a sensitivity analysis with scenarios constructed based on different magnitudes and probabilities of uncertainty.

Cope with the Uncertainty by Systematic Improvement of Lean Supply Chain Management in Shipbuilding

Based on the same author’s previous study, A Systematic Approach of Lean Supply Chain Management in Shipbuilding, this paper presents further analysis on the uncertainty of supply chain management in shipbuilding, clarifies the nature of uncertainty in the supply chain of shipbuilding, and establishes a systematic improvement model of lean supply chain management to mitigate the uncertainty of supply chain in shipbuilding. It refines the systematic approach on the respect of uncertainty and radically improvement of the theory. With the cases study, it is learnt that uncertainty of the supply chain in shipbuilding forces some trivial, particular, and detailed supply to become urgent issues, especially in the later stage when the ship closes to delivery; in these cases, the solution of solving such urgent parts causes the shipyard to pay a much higher cost. Less urgent issues and uncertainty in the supply chain of shipbuilding can not only benefit the total cost of the supply chain but also the efficiency of building processes. In a systematic path, this paper analyzes the root causes of the uncertainty of the supply chain management in shipbuilding in terms of technical specification, standardization ratio, unforeseen damage and defects, and change of demand schedule. The uncertainty of supply chain management in shipbuilding can be mitigated and reduced by means of high-quality design and engineering, higher standardization ratio in the parts and fittings, and proper safety margin on schedule time. After the procedure of LSCM obtained and refined by circulation for perfection, the professional software bund with new technology devices makes digital transformation reality. In the digital LSCM system, all performance measurement results with the original data of LSCM can be calculated and shown for the management. Therefore, the uncertainty of the LSCM in shipbuilding can be easily captured and solved.

Officiating Supply Chain Uncertainties due to COVID-19 Disruptions: Evidences Using Contingency Approach

This paper examines how firms achieve strategic fit with the external environment disrupted by the Covid 19 pandemic. The strategy formulation phase is studied concerning the firm’s size for short-term and long-term time horizons. The context of this study is Covid 19 disruptions and how firms from the Construction industry manage supply chain uncertainties. The qualitative interview technique is used to collect data from 13 contracting firms operating in the construction industry of the United Arab Emirates. The contingency theory approach is used to analyze the strategy formulation of firms during Covid 19 pandemic. Results indicate that while developing strategies to manage supply chain disruptions, medium-size firms tend to be more secure and safe. At the same time, large organizations can deploy their resources to reduce risks caused by supply chain uncertainties. However, for a more extended time, medium-size firms adopt a wait-and-see strategy compared to large firms’ Reactive or Proactive strategies. The use of contingency theory elaborated how construction firms achieve strategic fit to cope with Covid 19 disruptions. Organizations with more resources can opt for more reactive strategies, while most firms wait before taking any particular actions. The disruptions caused by Covid 19 are the first time phenomenon and thus require more detailed knowledge to proactively deals with it. Furthermore, an empirical model to reduce risks caused by Covid 19 disruptions is provided in the end.

The effects of employee commitment and environment uncertainty on product quality: The mediating role of supply chain integration

The main objective of the study was to test the relationship between the uncertainty of supply chain, employee commitment and product quality with the mediating role of supply chain integration. The uniqueness of the study is that it focused on the mediating role of supply chain integration in the automobile sector of United Arab Emirates (UAE). This research is quantitative in nature. For the analysis, structural equation modelling is used. The population of the present research is the employees working in the automobile sector of UAE. A Likert scale questionnaire was used to support this study. The questionnaire was distributed among 481 respondents by using simple random sampling. The usable response rate was 66.66%. The findings of the study confirmed the direct relationship between supply chain integration, product quality, employee commitment and environmental uncertainty. This study fills the gap of limited studies regarding supply chain integration in the UAE automobile sector. The findings of the study are also helpful for policymakers in developing automobile strategies.

Optimal Scheduling of COVID-19 Pandemic Supply Disruptions Under Uncertainty

With the outbreak of COVID-19 pandemic, the problem of supply chain emergency scheduling has had a great influence on economic benefits of enterprises. The uncertainty of the COVID-19 pandemic and uncertainty of supply chain have made the problem of emergency scheduling more complicated. In this study, a multiobjective multiperiod mixed-integer programming optimization model was developed, in which two conflicting benefit factors, cost and service level were taken as the optimization target of the model. Cost and service level were normalized, and the weighted sum was taken as the objective function, which transformed the problem into a multiperiod nonlinear one. Two algorithms of Bi-level Modified Hybrid Genetic Algorithm (BMHGA) and Bi-level Hybrid Genetic Algorithm (BHGA) were designed to solve the model. Three emergency strategies have been proposed, including enabling alternative suppliers, repairing failure nodes and enabling internal suppliers’ flexibility. The parameter of disruption scenario and its solution method were designed. Finally, the practicability of the proposed model and algorithm was demonstrated through application to a case study of an electronics supply chain. The results indicated that the optimal solution of two algorithms was between 2%-5%, and BMHGA could obtain a better optimal solution.

Supply chain ambidexterity and performance under uncertainty: The case of inter-island logistics in Indonesia

This study investigated the impact of supply chain ambidexterity on supply chain performance (SCP) under uncertainties. The dynamic capability theory of firms was adopted in the supply chain to design a research framework that recommends a supply chain strategy under uncertainties pertaining to inter-island logistics in Indonesia. This study involved the survey of 140 large-scale companies delivering products across the Indonesian islands to identify the supply chain uncertainties by analyzing data using SmartPLS. The supply chain ambidexterity (SAM) was identified to exhibit no direct correlation with SCP; however, agile supply chain (ASC) and lean supply chain (LSC) could indirectly relate the SAM and SCP. For supply chain professionals, the results indicated that SCP cannot be achieved solely through SAM, thereby necessitating the development of LSCs and/or ASCs, driven from SAM, to achieve SCP. Thus, this study empirically confirmed ASC and LSC to be effective practices for mitigating supply chain uncertainties by mediating supply chain ambidexterity on SCP.

Circular Economy: A Product Life Cycle Perspective on Engineering and Manufacturing Practices

Realization of a Circular Economy is paramount to solving global challenges in resource scarcity, sustainable manufacturing, and supply chain uncertainty. A Circular Economy (CE) is an economic system hallmarked by linearity reduction, decoupling of economic growth and resource depletion, and favoring regenerative models that consider sustainability. Growing support for a CE is leading to the proliferation of new economic terms, standards, and research to meet the different goals of CE. However, gaps exist in the formalization of these CE terms, frameworks, and research contributions. This paper provides a system-level context for a CE from the perspective of manufacturing in the product life cycle. We do this using the standard process modeling representation IDEFØ. The main contribution of this work is to provide the general context for a CE system by examining each CE activity involved in the creation of a product, reviewing the current literature, identifying current CE standards status and directions, and discussing CE concepts present in current business practices. This work will act as a reference for identifying gaps in research and standards development for integration of CE in manufacturing practices. Through this work, we identified two opportunities for furthering CE progress: metrics for measuring CE success and a standard CE framework with term definitions.