Supply Chain Subject Research Articles

Transitioning to a circular economy in the construction demolition industry: a bibliometric analysis

PurposeThis study aims to address the research gaps in the application of circular economy (CE) principles within the construction demolition industry (CDI) by providing an updated overview of key themes, trends and challenges. Using a bibliometric approach, it seeks to highlight the transformative potential of CE adoption in CDI, focusing on strategies for waste reduction, resource efficiency and supply chain optimization to support sustainable development.Design/methodology/approachBibliometric analysis using the Scopus database was employed to systematically review the literature on CE principles in the CDI from 2014 to 2023. The analysis involved a four-step assessment, including qualitative reviews and quantitative evaluations, to identify key themes, trends, challenges and opportunities in CE research within the CDI. The intricate relationship between CE principles with a specific emphasis on CDI, building practices and supply chain management was explored.FindingsThe findings underscore a significant emphasis on circularity principles, interdisciplinary collaboration and the integration of emerging technologies for efficient waste management. Experiencing a remarkable annual growth rate of 60.58%, particularly evident over the past five years, the escalating volume of relevant publications reflects an expanding interest in the CE within the CDI and related supply chain subjects. This underscores academia’s pivotal role in advancing the transition toward a circular construction economy.Originality/valueThe study recommends refining CE strategies by exploring the circular design paradigms, optimizing supply chains, integrating digital technologies, establishing standardized metrics and scrutinizing CE’s impact within the CDI.

Insight into the cooperation behavior among supply chain subjects in resource utilization of construction and demolition waste

Insight into the cooperation behavior among supply chain subjects in resource utilization of construction and demolition waste

Catastrophe-related disruptions’ preparedness and emergency management in Morocco: a proactive risks and resilience digital twin-based analysis

Purpose The purpose of this study is to analyze the operations and performance dynamics of a supply chain (SC) subject to disruptions. The preparedness of Moroccan responders in handling emergencies could be enhanced significantly, by devising digital twin-based decision support systems (DSSs). Design/methodology/approach The authors create a discrete-event simulation model to investigate proactively risks and resilience of a Moroccan basic-items SC (BISC). In this study, the authors analyze the effects of catastrophe-related disruptions (CRDs) on the Moroccan BISC, by the use of a simulation-based decision-supporting quantitative method. Findings In the disruption-free simulation experiment, the outcome was a satisfactory 100% coverage. By implementing CRDs, inventory levels have dropped, service levels decreased, lead time raised and there was an increase in backlogged products and late orders numbers. The highest impact was observed for the shutdown of paths linking suppliers to warehouses, whereas the increase in demand had a comparatively minor effect. The risk analysis approach helps to identify critical products for which the time-to-recover is longer and requires more commitment to enhance their resilience. Practical implications The model serves to deduce quantitative resilience assessment from simulation, streamline the selection of recovery strategies and enable the best-informed reactive decision-making to minimize the impact. Originality/value The research brings organizing solutions to catastrophe-related emergencies in Morocco. It would contribute significantly by visualizing, examining and unveiling the effects of disruptions on a BISC and offering actionable recommendations for remedial measures.

(Invited) Electron Microscopy Investigation of PEM Electrolyzer Degradation at Low Iridium Loadings

The employment of hydrogen as an energy carrier provides a promising solution toward zero carbon emission and battling climate change. To meet the DOE’s Hydrogen Shot goal of $1 per kilogram of hydrogen by 2031, proton exchange membrane (PEM) water electrolysis is a key technology of hydrogen production from renewable energy sources. Successful deployment of PEM electrolyzers requires reducing cost while simultaneously improving performance and lifetime. While cost reduction is expected from a variety of strategies including scaling up, operation optimization, and advanced manufacturing, it remains vital to reduce the use of noble-metal catalyst due to its scarcity and vulnerable supply chain subject to market disturbance. [1]Reducing the loading of iridium catalyst on the anode while maintaining electrolyzer performance and durability is of great challenge. In this talk, we discuss issues in PEM electrolyzer component development and advanced manufacturing of electrode layers related to catalyst loading reduction with an emphasize on analytical electron microscopy which provides valuable insight on materials morphology, crystalline structure, and chemical compositions. The batch-to-batch variance of catalyst morphology and elemental composition/distribution from commercial suppliers will be examined for catalyst down-selection. We then analyze the effect of reducing Ir loading on the electrode layer structure and ionomer distribution. These results are correlated with electrochemical measurements in the electrolyzer cell, which help elucidate the effect of low catalyst loading on electrolyzer performance. Morphologies of degraded low-loading anode catalyst layer and gas recombination layers will be investigated, and the dissolution and migration of iridium will be studied. We will also examine impact of different roll-to-roll manufacturing strategies for low-loading catalyst layers and on electrolyzer durability. Last but not least, we analyze MEAs subject to cation contamination and recovery procedure with electron microscopy. [2]References[1] Alia, S.M., Current Opinion in Chemical Engineering 2021, 33:100703.[2] Funding for this work was provided by U.S. Department of Energy Office of Energy Efficiency and Renewable Energy, Hydrogen and Fuel Cell Technologies Office through the H2NEW Consortium. Electron microscopy research conducted as part of a user project at the Center for Nanophase Materials Sciences (CNMS), which is a US Department of Energy, Office of Science User Facility at Oak Ridge National Laboratory.

A decision support framework to improve flow management in a supply chain subject to risks

ABSTRACT This research aims at developing an approach to assess the probability of meeting customer service level, while considering various risk factors present in a supply chain (supply disruptions, uncertainties in lead times, labour shortages, transport disruptions etc.). The work is conducted in tight collaboration with a leading actor of an aeronautical industry. Our model enables a better management of supply chain flows by improving two KPIs of interest for the company that operates in a MTO environment: on-time delivery (OTD) and depth of delay (DOD), by varying the repartition of flows between possible production and transportation modes. Change in transportation mode is indeed considered as a risk mitigation lever leading to sustainable operations. We first collect input data, which includes data related to the characteristics of the system under study (flow diagram, data pertaining to parameters such as lead time, cost, capacity…) and supply chain risks mapping. Then, we develop a discrete event simulation (DES) model considering supply chain risks to determine the best flow repartition enabling to satisfy KPIs considered. A performance evaluation module enables to calculate the probability distribution of the chosen KPIs. Finally, a multi-scenario analysis is conducted by varying different parameters that have an impact on OTD, DOD and the total cost.

Research of blockchain-embedded agricultural quality credit regulation influencing factors

PurposeThe credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.Design/methodology/approachUsing the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.FindingsThe results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.Originality/valueCredit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

Research on Supply Chain Contract of Omni-channel Retail with BOPS Mode

T With the rapid development of e-commerce, consumers' consumption patterns have changed, more and more consumers are used to shopping online. Therefore, in order to better connect with the consumer market and save total cost of the supply chain, more and more manufacturers have expanded their online channels, which undoubtedly has an impact on the operation of brick-and-mortar shops. Therefore, under the background of new-retail development, BOPS mode is introduced to integrate online and offline. It protects offline physical resources, and brings profit gains to different subjects of omni-channel supply chain. This paper focuses on the omni-channel supply chain members who jointly manage BOPS mode, but as different profit subjects, what kind of supply chain contracts should manufacturers and retailers adopt to guarantee their respective interests, improve the enthusiasm of each subject, and make omni-channel supply chain operate continuously. In this paper, the Stackelberg game model is used to study the influence of traditional wholesale price contract, quantity discount contract, sales rebate contract and revenue sharing contract on the profit and return of manufacturers and retailers in omni-channel supply chain, so as to effectively encourage the main body of omni-channel supply chain to actively provide BOPS, protect offline physical store resources and bring gains to omni-channel supply chain by taking advantage of online and offline advantages. It is found that sales rebate contract and revenue sharing contract can achieve Pareto optimization on the basis of traditional wholesale price contract, and the choice mainly depends on BOPS demand.

Resilience of critical supply chains in pandemics: A model proposal for health personal protective equipment socially optimal distribution

Resilience of critical supply chains in pandemics: A model proposal for health personal protective equipment socially optimal distribution

Game analysis of service quality evolution of online tourism supply chain under PPI participation

ABSTRACT While platform protection insurance (PPI) is extensively employed as an insurance policy in many sharing platforms, research on its influence on the tourism supply chain is lacking. At this point, the quality of online tourism services has taken the brunt of consumer complaints, and new solutions are desperately needed. So, would PPI's involvement increase the quality of online tourism services? In this paper, by constructing an online tourism supply chain consisting of a Tourism Supplier (TS), an Online Tourism agency (OTA), and consumers, we study the conditions of PPI introduction and its impact on online tourism service quality and analyze the behavioral decisions of online tourism supply chain subjects. The study found that in the tourism market with a small amount of demand change, OTA is more willing to introduce PPI, and TS is more inclined to improve service quality, which then lowers the service cost of TS and the level of disclosure of information, the stronger the willingness of OTA to introduce PPI, and the introduction of PPI in the lower PPI penetration rate of the tourism market has a more promotive effect on the TS with lower service cost.

Safe Food Supply Chain as Health Network: An Evolutionary Game Analysis of Behavior Strategy for Quality Investment.

There is a natural relation between human health and the quality of their food and drinks, and elevating the quality input level of food production for all enterprises within the food supply chain system forms the foundation for preventing various potential food safety risks that may be encountered. Unlike the previous research on quality investment of food production by enterprises, this paper probes into the evolutionary routes of the behavior strategy selection of subjects in the food supply chain and the preconditions for the equilibrium points of the social co-governance system. It takes the approach of establishing a tripartite evolutionary game model of food suppliers, food manufacturers and consumers on the basis of the social co-governance framework, in view of the above, this paper focuses on the influence of the reputation mechanism and the market contracts among supply chain subjects on the selection of a behavior strategy for quality investment by enterprises under the condition of lawful regulation by government. The results show that every subject selects their own behavior strategy on the basis of the balance of their respective interests. The net disbursement incurred by enterprises for quality investment and the costs of participation in governance by consumers constitute the dominant factors that influence both enterprises' selection of a behavior strategy and the level of social co-governance. Compared with the increase in economic punishment imposed on suppliers for production of risky food raw materials, it is more efficient to control food safety risks by lowering the costs of quality investment by suppliers. Accordingly, this paper proposes advice on policy in an attempt to provide inspiration for preventing and controlling food safety risks.

Mathematical Modeling of Dynamic Supply Chains Subject to Demand Fluctuations

This research work aims to develop the mathematical modeling for a class of dynamic supply chains. Demand fluctuation corresponds to product demand volatility, which increases or decreases over a given time frame. Industrial engineering practitioners should consider the function that applied mathematical modeling plays in providing approximations of solutions that may be used in simulations and technical implementations at the strategic, tactical, and operational levels of an organization. In order to achieve proper results, two mathematical models are presented in this paper: In addition to a finite-dimensional system of Ordinary Differential Equations (ODEs) for coupled dynamic pricing, production rate, and inventory level, which properly integrates Lyapunov stability analysis of the dynamical system and simulations, there is an infinite-dimensional Partial Differential Equation (PDE) production level modeling system available. Infinite and finite-dimensional systems incorporate a dynamic pricing approach in the mathematical modeling. The main research goal of this work is to explore the dynamic nature of supply chains applying PDE and ODE methods, with proper analytical analysis and simulations for both systems.

An adaptive product changeover policy for a capacitated two-product supply chain in a non-stationary demand environment

ABSTRACT The present paper investigates the effectiveness, in terms of fill rate, of a new adaptive production control policy for a two-product, two-echelon (i.e. factory and retailer) supply chain subject to a non-stationary customer demand. To model the capacity constraints more realistically, the factory node consists of an unbuffered production line subject to failures, and non-negligible changeover times. To cope with the disruptive events, we propose a new production control strategy named Adaptive Hedging Corridor Policy. A simulation model based on discrete-time difference equations is developed, and a two-step experimental campaign is conducted to compare the proposed control policy with two well-known alternatives proposed in the literature. The analysis of the results demonstrates the effectiveness of the new adaptive strategy in maximising the fill rate of supply chains subject to a non-stationary demand.

Research on Information Interaction Behavior Between Supply and Demand Sides of Agricultural Products

As the information interaction in the agricultural production process will affect the supply chain structure and production and operation mode of agricultural products, it will have a great impact on its operation efficiency and the quality of agricultural products. This paper uses the theory of information asymmetry and behavioral difference between subjects to solve the problem of information asymmetry between the supply and demand sides of agricultural products caused by it, and puts forward the research on the information interaction behavior between the subjects of agricultural products supply chain.

Measuring the coordination decision of renewable energy as a natural resource contracts based on rights structure and corporate social responsibility from economic recovery

With the rapid development of the times, changes in the manufacturing environment, and the migration of consumers' green consumption awareness, the green product market has expanded, leading to economic recovery. Furthermore, the regulation of the internal status of supply chain subjects causes different rights structures to dominate the market and change on a regular basis. This paper considers manufacturers and service providers of renewable energy products as the research objects and considers the mechanism of product renewability and green finance level. Profit models of renewable energy supply chain members are constructed under various rights structures and CSR-bearing subjects, and optimal decisions under various decision models are analyzed. It is discovered that whether the manufacturer or the service provider engages in CSR, the superiority and inferiority ranking of the three different rights structures will differ depending on the degree to which they engage in CSR. And the conclusion is that when a subject dominates a market, its profit is also maximized. Positive contractual coordination actions by both retailers and manufacturers will drive renewable energy quality. Green finance and green economic growth are becoming increasingly popular. Through contractual coordination, both parties will achieve Pareto improvements. • There is a dire need to measure the natural resource based green recovery. • The embodiment of renewable energy subjects' fulfillment of CSR to ensure green recovery. • We consider manufacturers and service providers of renewable energy mechanism of green finance for green recovery. • When any subject dominates the market, its profit is also more optimal. • The support for green finance and green economic growth increases significantly led to green economic recovery.

Organisational Complexity of the Eurofighter Typhoon Collaborative Supply Chain

ABSTRACT The European Union (EU) promotes arms collaboration as a stepping-stone towards the evolution of an integrated European defence technology and industrial base. It will necessarily comprise prime contractors and their attendant supply chains, with the latter particularly important because they represent a refined regional division of labour, promoting efficiencies through skill-based specialisation. Paradoxically, however, Europe’s largest military aerospace collaborative venture, the Eurofighter Typhoon, possesses a complex supply chain subject to political and institutional strictures, as well as potential inefficiencies. Partner nations prioritise national sovereignty objectives through duplicated assembly lines and work allocation arrangements based on juste retour (fair share) rather than market-driven competitiveness criteria. The purpose of this paper, then, is to explore Typhoon’s supply chain complexity, especially the impact of juste retour policy. The findings from this analysis will highlight important policy issues influencing the future supply chain model of Europe’s successor 6th-Generation fighter programme.

The optimal recovery-fund based strategy for uncertain supply chain disruptions: A risk-averse two-stage stochastic programming approach

For a supply chain subject to uncertain production disruptions, the joint optimization of investment intervention on recovery speed and duration of disrupted production capacity and location and inventory management has not been well studied. In this paper, a novel recovery strategy is introduced and studied, which uses investment to adjust the recovery speed and duration of production capacity, and two recovery behaviors responding to different types of disruptions are modeled. Considering uncertain disruption scenarios and their ripple effects over the supply chain, a risk-averse two-stage stochastic programming model (RTSPM) is established to study the integrated supply chain management of selection of distribution centers, multi-period inventory, transportation flows, and recovery-fund based mitigation policy. The RTSPM incorporates the risk preference of managers in decision making. We propose a trust-region-based decomposition method to solve the RTSPM and demonstrate its efficiency by benchmarking on state-of-the-art commercial solvers. Through numerical examples, we deeply analyze the effectiveness of RTSPM and the relations of optimal recovery investment decisions with the uncertain disruption factors. Finally, we provide implications and suggestions induced from the models and findings to aid the decisions on renting of distribution centers and the emergency investment and operational decisions when suffering the disruptions.

A tripartite evolutionary game research on information sharing of the subjects of agricultural product supply chain with a farmer cooperative as the core enterprise

In order to explore the interaction law of information sharing behavior of decision‐making subjects in the agricultural product supply chain, this paper establishes a tripartite evolutionary game mathematical model, uses the replicator dynamics equation to analyze the dynamic evolution process of the three‐dimensional dynamic system, and carries out numerical simulation analysis. The results show that there are seven key factors affecting the information sharing decisions of the decision‐making subjects. This paper explores the specific role of these influencing factors and finds ways to improve supply chain performance. Finally, the study proposes four suggestions for supply chain information sharing management.

Designing and planning the downstream oil supply chain under uncertainty using a fuzzy programming approach

This paper addresses the strategic and tactical planning of a downstream oil supply chain (DOSC) subject to different sources of uncertainty. This problem is formulated as a mixed-integer linear programming (MILP) model, whereas uncertainty is tackled using chance constrained programming with fuzzy parameters. The MILP model aims at determining the network design and the products distribution plan in a cost-effective way. A real case study on the Brazilian oil industry is used to validate the model. The proposed model shows to be a valuable decision-support tool in order to aid the decision-making process in the strategic and tactical planning of real-life problems.

Contract strategies in competitive supply chains subject to inventory inaccuracy

We use a newsvendor model to investigate equilibrium contracting strategies and their impact on the members in two competing supply chains that are subject to inventory inaccuracy. The suppliers are Stackelberg leaders and can choose either a wholesale-price contract or consignment contract. As a result, we analyze three cases: the wholesale price contract case, consignment contract case, and hybrid contract case. We first analytically derive the optimal outcomes of each case and then analyze the equilibrium behaviors of suppliers and retailers under both symmetric and asymmetric settings. Our results show that the consignment contract is no longer the dominant strategy for dominant suppliers when inventory inaccuracy is considered, even though it is considered as the channel-coordinating contract format in the traditional supply chain. Specifically, in the symmetric case, the wholesale price contract is the equilibrium contracting strategy when inventory inaccuracy is below a certain threshold. In the asymmetric case, the hybrid scenario occurs when the high-cost supplier chooses the wholesale price contract, and the low-cost supplier chooses the consignment contract when inventory inaccuracy is less than a certain value. Furthermore, our results demonstrate that the threshold point of inventory inaccuracy is interrelated with the channel cost-sharing rate and level of chain-to-chain competition between supply chains.

Research on Quality Investment and Pricing Decision Sequence of Complex Equipment Supply Chain Considering Manufacturer's Incentive Strategy

For the demand uncertainty of complex equipment two-stage supply chain, the influence of different quality investment and pricing decision sequence on expected revenue and demand, with the consideration of incentive strategy between manufacturers to suppliers, manufacturer determines the basic quality and compensation for suppliers, suppliers determine the parts wholesale price and quality investment, then manufacturer decides the complex equipment product price. This paper set up two quality investment and price decentralized decision sequence: a Stackelberg game model, a vertical Nash game. Conditions of suppliers decisions are obtained, and the changes of pricing, quality investment, demand and profit of supply chain members are analyzed. It shows that making quality investment and wholesale price decisions simultaneously is best for manufacturers and integrated supply chain; determining quality investment and then set the wholesale price at the same time is the best choice for the whole suppliers. For individual suppliers, there is no absolutely dominant decision-making sequence. By comparing the model and different parameters, the paper provides a management basis for improving the quality and performance of supply chain subjects.