Sustainable Supply Chain Design Research Articles

Design of sustainable supply chains for managing plastic waste: The case of low density polyethylene

Plastic waste management presents a significant challenge that requires the integration of supply chain and sustainability principles. This study proposes a comprehensive supply chain model for plastic waste and management, specifically low-density polyethylene (LDPE), focusing on economic and environmental considerations. A model based on Mixed Integer Linear Programming (MILP) is developed to address the type of plastic waste management technology, their location through the United States East Coast and the effect of transitioning to an electrified transportation. The model determines plastic waste pyrolysis as the preferred technology to maximize profitability, and mechanical recycling combined with hydrogenolysis and hydrocracking to minimize the global warming potential (GWP). The mix of technologies for minimizing the GWP is highly correlated with the type of transportation, being desired to remove hydrogenolysis when electric trucks are introduced. This electrification of the transportation reduces the emissions by 23 %, but with an increase in the costs by 4 %.

Sustainable cold supply chain design for livestock and perishable products using data-driven robust optimization

ABSTRACT Food products are a critical part of everyday life. To increase the efficiency of the food supply chain, designing a comprehensive mathematical is necessary. This study tries to optimize a protein supply chain. This supply chain is divided into livestock and perishable products. The integration of these two supply chain echelons has been applied to create an extensive model. Moreover, sustainability has been considered as a competitive advantage in the chain. Perishable products are temperature-sensitive. Hence, a cold supply chain has been considered. The model has three objective functions: maximizing the total profit, minimizing the storage cost in the cold chain, minimizing the health risk. In dealing with uncertainty, a data-driven robust optimization method has been used. Therefore, this paper used machine learning to construct the uncertainty sets from historical data. The Torabi-Hassini method has been implemented to solve the multi-objective model. Finally, to show the applicability and efficiency of the proposed approach, a real-world case study on the poultry supply chain, including abattoirs, breeding centers, slaughtering, and selling branches, has been applied. The result shows that this methodology significantly influences total profits and improves the environmental criteria in a real-world case study. Moreover, different sensitivity analyses have been prepared to help managers make a trade-off between the robustness of the model and objective function value with various weights and calculate the influence of supply chain integration on objective functions.

Supply chain design: implications for sustainability

ABSTRACT This paper aims to add sustainable dimensions to the supply chain design (SCD) literature. A systematic literature review method is adopted to comprehensively analyze the papers related to SCD and sustainability literature. This study summarises the drivers, practices, and outcomes of sustainable supply chain design (SSCD), and further investigates the factors that can help companies realise sustainability through SCD. A conceptual framework is developed to connect these two concepts. Further, this study identifies significant research gaps with potential for the future development of SSCD. This paper will help firms identify the enabling factors that promote SSCD to achieve better supply chain (SC) sustainable performance. Meanwhile, this paper extends prior studies of SCD by adding sustainable dimensions. The authors develop a conceptual model that illustrates the antecedents of SSCD implementation and how the SSCD can promote the SC sustainable performance.

Mathematical programming model for cost-optimized and environmentally sustainable supply chain design

Sustainability is becoming increasingly important as a topic in general supply chains and cold chains. This study addresses the critical need for an integrated and comprehensive approach to supply chain design that simultaneously maximizes cost efficiency and incorporates environmental sustainability, focusing specifically on cold chains. Prior research has identified a gap in existing studies, highlighting the absence of an overarching framework from the logistics providers’ perspective. Our novel mathematical programming model introduces a unique strategy that carefully balances environmental concerns and cost optimization, addressing the shortcomings found in previous works. By integrating variables related to distribution, transportation, and inventory management, the model aims to minimize overall expenses and environmental impact, specifically regarding energy consumption and carbon emissions. We formulate and solve the optimization problem through rigorous mathematical programming, offering a flexible solution applicable to various logistics scenarios. The results demonstrate a significant reduction in overall expenses and environmental effects, providing logistics providers with a powerful tool for informed decision-making and sustainable supply chain management. This research contributes to the evolving field of supply chain sustainability by presenting a practical and effective model for maximizing cost savings while promoting environmental responsibility. The study concludes with compelling statistics, revealing a noteworthy decrease in overall expenses by €25 128 146.73 (100.25%) and environmental impact by 17 359.39 (100.04%). The outcomes show a notable decrease in general expenses and environmental effects, giving logistics providers a strong instrument for wise choices and sustainable supply chain management.

Sustainability implications of establishing a circular European supply chain of battery materials

The increasing number of electric vehicles worldwide leads to strategic challenges in designing battery supply chains. More sites for raw material extraction, battery production, and recycling will be needed to fulfill the future battery demand and the legislative goals regarding recycling rates, recycled content, CO2-limits, and social standards from the European Union for sustainable batteries. Battery manufacturers must also design their supply chains cost-efficiently to compete with non-European battery manufacturers. The environmental and socio-economic impacts of supply chains depend significantly on the supply chain design, which is expected to change in the upcoming years. Therefore, this study aims to investigate battery supply chains in the status quo and 2035 regarding all three sustainability dimensions using the life cycle sustainability assessment (LCSA). The status quo is modelled based on current market shares and without circular supply chains. For 2035, circularity is added with secondary materials in the production and more European-centered supply chains by moving the cell production and the recycling fully to Europe. The results provide insights into the design of sustainable battery supply chains. They highlight that moving a big part of the supply chains to Europe has a more significant influence on the environmental, social, and economic impacts than the circularity of materials. However, the results depend on the current supply chain design and future developments of products and processes as well as the electricity mix.

Design of battery supply chains under consideration of environmental and socio-economic criteria

The demand for electric vehicles is increasing worldwide, leading to a high demand for lithium-ion batteries, whose supply chains are associated with high environmental and socio-economic impacts. Therefore, legal regulations, such as the EU Battery Regulation, force battery manufacturers to use secondary materials, comply with CO2-limits and ensure social conditions along their supply chains. These circumstances make it necessary to assess battery supply chains in terms of their environmental, economic, and social impacts. For this purpose, the life cycle sustainability assessment approach can be used. However, the results of this approach often lead to conflicting goals between and within sustainability dimensions, making it challenging to derive recommendations for more sustainable battery supply chain designs. One approach to solving this problem is to use optimization models that take the three sustainability dimensions into account.To this end, this study aims to combine the results of a Life Cycle Sustainability Assessment of battery supply chains with a decision support model to derive recommendations for action for the design of more sustainable battery supply chains. For this purpose, different spatial-differentiated activities are assessed and included in a decision support model that aims at minimizing the costs of a German battery pack manufacturer, considering environmental, social, and legal restrictions. The decision support model is implemented in Python and solved using Gurobi. The results of the decision support model are compared with the current state of battery supply chains as a benchmark. The result of the study shows that in many of the scenarios studied, the cost, as well as the environmental and social impacts, can be significantly reduced compared to the benchmark. However, if the environmental and social impacts were to be reduced strictly, this would lead to higher costs compared to the benchmark. Furthermore, the results show that a European-centric supply chain would emerge for more environmentally friendly supply chains, while for a more socially friendly supply chain, the focus would be on Japan.

A Sustainable Supply Chain Design for Personalized Customization in Industry 5.0 Era

A Sustainable Supply Chain Design for Personalized Customization in Industry 5.0 Era

Resilient and sustainable global COVID-19 vaccine supply chain design considering reverse logistics

This study proposes a multi-mode, multi-product, and multi-objective optimization model to design a resilient and sustainable global COVID-19 vaccine supply chain network under operational risks. The network includes a forward chain for vaccine supply, production, and distribution and a reverse chain for vaccine waste management. The objective functions comprise minimizing the total network costs and environmental pollution caused by the waste of vaccination centers and the transportation between facilities, as well as considering social impacts (maximizing regional development and the effect of domestic vaccine production on self-sufficiency, and minimizing the impact of vaccine side-effects). Resilience strategies are employed to deal with the disruption risks in different facilities and transportation links of the chain, including multiple sources of raw material supply, vaccine production and distribution, and waste management facilities; import; multiple transportation modes and different vehicles in each mode; inventory holding; capacity expansion; transshipment; and fortification of facilities. Financial parameters, including exchange rate and international transport insurance for importing raw materials and vaccines, are also considered in the presented model. An actual-world case study in Iran is conducted to indicate the model's applicability. Finally, by analyzing the computational results, important research implications are presented. The analyses investigate the conflict of objectives, examine the impact of vaccine side-effects on production and import, assess the efficiency of resilience strategies in the face of disruptions, demonstrate the effect of disruptions on network components, and determine suppliers' share for the supply of raw materials.

Resilient and sustainable supply chain design and planning under supply disruption risk using a multi-objective scenario-based robust optimization model

Resilient and sustainable supply chain design and planning under supply disruption risk using a multi-objective scenario-based robust optimization model

Robust Optimization Model for Sustainable Supply Chain Design Integrating LCA

Supply chain management is the basis for the operations in an organization. The development of realistic supply chain designs that work effectively in the presence of disturbances in a stochastic environment and incorporate sustainability factors, is a complex challenge being investigated in recent years. However, the inclusion of a methodological structured framework to evaluate environmental impacts constitutes a knowledge gap in the literature on supply chain design. This study developed a model for sustainable supply chain design, integrating Life Cycle Assessment and based on a robust optimization approach. The study follows a 4-stage methodology beginning with data collection and the execution of a Life Cycle Assessment. Then, the deterministic modeling is proposed, concluding with a robust model. A bi-objective model is proposed to maximize utility and minimize environmental impact based on demand scenarios. The model was validated with real data from a medium-sized enterprise that produces antibacterial gel, generating as a result, different configuration alternatives for the supply chain to transport the products and raw materials between its elements. The conclusions of this work highlight the importance of including sustainability factors during supply chain design, the consequences and costs of its inclusion, as well as the priority actions that promote sustainable designs.

Assessing the supply chain management of waste-to-energy on green circular economy in China: an empirical study.

One of the industries that makes a significant contribution to the overall amount of greenhouse gas emissions around the globe is agriculture. In this regard, the use of bioenergy in the agricultural and food processing industries might benefit from the implementation of circular economy techniques. Despite the fact that just roughly 9% of the global economy is circular, there have been worldwide efforts to improve that reality. The linear economy, commonly known as the "take-make-use-dispose" model, is in sharp contrast to the circular economy, also known as "grow-make-use-restore," which seeks to influence the flow of materials and energy in order to maximize the benefits to the environment and minimize any associated costs. Garbage-to-energy, also known as WTE, is the focus of both academics and businesses as a direct result of the increasingly diminishing number of energy supplies and the ever-increasing amount of garbage. This project intends to turn trash into profit, lessen the impact waste has on the environment, and generate energy from biowaste by conceptualizing a focus on the supply chain characteristics of waste-to-energy processing. The adoption of a waste-to-energy (WTE) supply chain as a district energy system should be a viable solution toward a circular industrial economy that can solve energy consumption, waste management, and greenhouse gas emission concerns all at once. In the framework of a "circular economy," this study investigates how the management of waste-to-energy supply chains impacts the performance of businesses. The present investigation makes use of life cycle assessments, technical innovation, waste-to-energy conversion, and capacities related to circular economies. The study makes use of data obtained from an online survey that was administered between March 2021 and November 2021 to employees of 285 representative samples drawn from 457 European enterprises and firms that have accepted the concepts of the circular economy. The data is examined using a technique known as partial least squares structural equation modeling (PLS-SEM for short). The findings indicate that waste-to-energy serves as a mediator between the life cycle assessment and the capabilities of the circular economy and that sustainable supply chain management, sustainable supply chain design, technological progress, and waste-to-energy all have positive effects on these metrics.

Environmental and social equity in network design of sustainable closed-loop supply chains

While the whole society is meant to benefit from sustainable development; environmental and social fairness considerations are often overlooked in the design of supply chain networks. The literature acknowledges that a reductionist interpretation of sustainability is often found in existing mathematical formulations due to lack of evaluation of the social dimension. In this paper, we suggest new indicators based on Gini index to measure environmental and social inequalities between regions concerned with installation of new product recovery facilities for the reverse part of a closed-loop supply chain. The initial levels of pollution and unemployment rate in each region are impacted by facility location decisions and corresponding industrial activities. We show through numerical experiments that inequalities between the regions can be diminished as a result of the use of deliberate objectives aiming to reduce environmental and social inequity. Managerial insights and future research directions are also discussed.

Economic and Environmental Viability of Lithium-Ion Battery Recycling—Case Study in Two Canadian Regions with Different Energy Mixes

Lithium-ion battery (LIB) pack is the core component of electric vehicles (EVs). As the demand is continuously increasing, it puts a lot of strain on the battery raw material supply chains. Likewise, the large quantity of spent LIBs from different sources will add to the complexity of end-of-life (EoL) management. Battery recycling processing is a potential source of critical cathode precursor materials as an alternative to virgin raw material sourcing. Indeed, metal sulfates (nickel, cobalt, and manganese) and lithium carbonate could be recovered through EoL processing. This study aims to provide an economic and environmental life cycle sustainability assessment of recycled battery materials. This assessment is based on a bottom-up approach considering geographical boundaries and process data inputs. The two sources of critical cathode battery materials, virgin and recycled battery materials, are compared based on economic and environmental indicators. This study identified the province of Quebec in Canada as the geographical boundary where several battery processing plants have been recently announced. The best available recycling process (hydrometallurgy) was selected. For the virgin materials, this study considers the option of importing from other jurisdictions by using global average supply chain values. Furthermore, a comparison of alternative supply chain configurations was performed using a spatially differentiated approach. The main findings of this study are as follows: (i) the environmental credit of recycled cathode active materials (CAMs) is estimated as −6.46 kg CO2e/kg CAM, and (ii) the overall cost and environmental impacts of producing LIB cathode active material from recycled battery materials can be 48% and 54% lower than production from virgin materials, respectively, considering the upstream, midstream, and downstream stages of the CAM supply chain. The main drivers for the reduction in these financial costs and emissions are the local transportation and the hydrometallurgical process. The assessment results provide insights to support the development of appropriate policies and R&D solutions adapted to local considerations as well as offer additional possibilities to improve the design of sustainable supply chains for LIB recycling.

A novel two-stage multi-objective optimization model for sustainable soybean supply chain design under uncertainty

Soybean is one of the most important agricultural products in international markets due to its high global consumption. However, there are limited studies considering sustainability issues and global economic aspects of the soybean supply chain design and optimization. Moreover, it is challenging to integrate many sustainability criteria into a single-stage optimization model for a soybean supply chain configuration. This research proposes a novel two-stage approach, integrating a multi-criteria decision-making technique and a new multi-objective optimization model to design and optimize a soybean supply chain network in Canada, considering sustainability and global factors. In Stage 1, several qualitative and quantitative sustainability criteria are considered to calculate the sustainability scores for the potential suppliers, using the Interval Type 2 Trapezoidal Best Worst Method. Then, the scores are used as input in Stage 2, where a new optimization model with four objective functions is formulated to design and optimize a soybean supply chain. The objective functions include maximization of total profit, created job opportunities, and suppliers' sustainability, and minimization of CO2 emissions. Then, the Pareto frontier is generated, using the augmented ε-constraint method which helps policymakers to make appropriate decisions. Furthermore, four cases are proposed and analyzed to assess the impacts of the objective functions on strategic and tactical decisions. The results show the importance of the presented method as an integrated approach, considering sustainability pillars in agri-food supply chains. In addition, the results indicate that the proposed stochastic multi-objective model can handle fluctuations in uncertain parameters.

A scenario-based sustainable dual-channel closed-loop supply chain design with pickup and delivery considering social conditions in a natural disaster under uncertainty: a real-life case study.

In the context of the COVID-19 pandemic, utilizing the potential of online markets to sell products has become increasingly important for creating competitive advantages and ensuring the growth and survival of businesses. The pandemic has disrupted traditional business practices, and with social distancing measures in place, consumers have turned to online channels to meet their needs. As a result, businesses that have adapted quickly to online markets have been able to maintain their customer base and revenue streams. Thus, considering the potential of online markets is of utmost importance in the current pandemic situation. In this regard, the present research aims to provide a practical framework for creating a green and sustainable closed-loop supply chain network (SCLSCN), including the integration of online markets, to assist managers in making decisions that support economic, environmental, and social goals. Accordingly, a multi-objective mixed integer linear programming (MOMILP) optimization model was designed under uncertain demand and disruption caused by natural disasters in Iran's home appliance industry. The study also considered changes in the capacities of online and marketplace sales channels, revealing a significant reduction in costs at each stage. The results show that the increase in demand has a direct impact on the production level, warehousing, and transportation costs, leading to social impacts on the model. However, the current system cannot handle an increase in demand of more than 20%, requiring managers to make decisions to increase production capacity or build new factories. Thus, the study highlights the importance of considering online markets as a means to adapt to disruptions caused by the pandemic and maintain a competitive edge.

Collaborative location routing problem for sustainable supply chain design with profit sharing.

To identify the sustainability synergies in a collaborative Moroccan dry food wholesale chain, we investigate the financial and ecological effects of implementing horizontal cooperation between three competitor shippers. For business-to-business networks, the key objective is to ensure last-mile delivery to their clients in metropolitan areas. The implementation of this alliance requires studying different aspects, among them the design of the transportation network, fair profit sharing, and collaborative delivery planning. Limited studies have considered the effects of integrating facility location and vehicle routing by addressing multiple goals in the design of a sustainable collaborative supply chain. We model the problem as a periodic two-echelon echelon-periodic location routing problem to integrate different decision levels. In order to investigate the trade-offs between the two opposing goals, a multi-objective approach is adopted. The Epsilon constraint method is used to generate a compromise between economic and ecological impacts. Cost and carbon emission sharing are assessed through the Shapley value mechanism. Furthermore, to determine the effect of parameter changes on the attained savings, a scenario analysis is performed. Results show the positive effect of collaboration among shippers and the importance of using integrated network design models. Environmental considerations in the pursuit of economic goals affect the gains produced and result in various transportation network structures. The performance of the coalition varies under different scenarios. Managerial implications are presented.

Sustainable supply chain design under correlated uncertainty in energy and carbon prices

This paper aims to provide an improvement in the modeling of supply chain designs by incorporating correlated uncertainty among multiple parameters, resulting in a more resilient design. A new methodology to generate forecasts for historically correlated time series, regardless of their underlying probability distributions, is presented and applied to generate scenarios for energy and carbon prices, which historically proved to be correlated. These scenarios are then used in a stochastic computation to obtain a three-echelon supply chain design in Europe maximizing the economic performance. The emissions were monetarized through the incorporation of the European Union cap-and-trade emissions trading system into the model. The social impact of the supply chain network is measured in terms of the direct, indirect and induced jobs it creates, which are proportional to the economic performance. By combining the developed methodology with data mining algorithms, a reduction in the number of required scenarios by more than 90% was achieved. The numerical case study moreover shows that the stochastic design ensures an average reduction of emissions by more than 3 ktons compared to the use of a deterministic approach. In comparison, the computation of a stochastic supply chain design without parameter correlation takes 5 times longer.

Exploring antecedents for the circular economy capability of micro, small and medium enterprises: An empirical study

AbstractMicro, small and medium enterprises (MSMEs) play an important role in the economies of developing countries. The circular economy (CE) is considered a long‐term initiative for protecting the environment by reducing waste and greenhouse gas emissions, recycling and ending planned obsolescence. This research aims to explore antecedents for the CE capability in the context of the Indian MSMEs. The current study used the extended theory of planned behaviour and institutional theory to measure CE capabilities. Seven hypotheses are developed in this study. The survey‐based research is carried out with 296 responses from the MSMEs of different sectors in India. Hypothesis testing is done using the structural equation modelling approach. Major constructs identified for this study are green economic incentives (GEIs), social pressure (SP) and attitude. These constructs have a significant association with the CE capability of MSMEs. Environmental commitment (EC) and sustainable supply chain design (SSCD) act as mediators. Insights from this study will help the top management of MSMEs to understand antecedents for CE capability. The findings show that SP and GEIs are positively associated with EC and SSCD. It is found that EC and SSCD play a complimentary mediation role. The research findings will provide a solid foundation for understanding the importance of CE capability in MSMEs and developing strategic plans to facilitate implementing CE in these small sized firms.

Sustainable plant-based dietary supply chain design to reduce malnutrition in deprived areas

Food and Agriculture Organization (FAO) of the United Nations has reported that malnutrition elimination and people’s eating habits have the immense potential to alter the world food demand in 2050. Hence, strategists should incorporate the mentioned elements to properly manage the food industry. This paper aims to present a comprehensive model for integrating strategic and tactical decisions to manage a forward environmentally-friendly perishable food supply chain (FSC). Public health is applied in the form of plant-based diets to overcome nutritional deficiencies and depends on the product’s mineral features at the time of delivery. Our proposed model can be employed by the government and non-profit organizations when the salient purpose is to ameliorate the irreparable effects of malnutrition. The model can provide the food sector managers with valuable insights into designing a greener, more responsive, and more profitable supply chain. The resultant managerial insights after solving the proposed model for a real case study are 1) The importance of agricultural production to building a sustainable food system cannot be overemphasized; 2) For managers to alleviate malnutrition while minimizing costs and environmental burdens, the product's nutrient profile is of a higher priority regardless of its deteriorating speed; 3) Improving the nutritional value of processed products seems to be more effective than establishment and manufacturing costs to ensure the selection of processed products in diets; and 4) Dietary diversity can be achieved by incurring a 14% increase in total costs.

A Simulation Approach for the Design of More Sustainable and Resilient Supply Chains in the Pharmaceutical Industry

In a world facing unprecedented challenges, such as climate changes and growing social problems, the pharmaceutical industry must ensure that its supply chains are environmentally sustainable and resilient, guaranteeing access to key medications even when faced with unanticipated disruptions or crises. The core goal of this work is to develop an innovative simulation-based approach to support more informed and effective decision making, while establishing reasonable trade-offs between supply chain robustness and resiliency, operational efficiency, and environmental and social concerns. Such a decision-support system will contribute to the development of more resilient and sustainable pharmaceutical supply chains, which are, in general, critical for maintaining access to essential medicines, especially during times of crises or relevant disruptions. The system will help companies to better manage and design their supply chains, providing a valuable tool to achieve higher levels of resilience and sustainability. The study we conducted has two primary contributions that are noteworthy. Firstly, we present a new advanced approach that integrates multiple simulation techniques, allowing for the modeling of highly complex environments. Secondly, we introduce a new conceptual framework that helps to comprehend the interplay between resiliency and sustainability in decision-making processes. These two contributions provide valuable insights into understanding complex systems and can aid in designing more resilient and sustainable systems.