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The process of sourcing Reclaimed Construction Materials (RCMs) is predominantly manual and hindered by the limited digital presence of RCMs. However, the advancing technological landscape provides an opportunity to create a modular framework that can assess the value proposition of New Construction Materials (NCMs) and RCMs for a project before acquiring them. A field study in the Kitchener/Waterloo region inspired the development of a framework that has three underlying systems encompassing digital tools for data collection and analysis: (1) The Real Environment uses 3D scanners and a spreadsheet software, (2) The Model Environment uses Building Information Modeling (BIM) software and a Life Cycle Assessment (LCA) tool, and (3) The Core Engine uses an optimization program. Real-world data collected from RCM stores (The Habitat for Humanity) and NCM stores (The Home Depot) are used for a realistic demonstration of the framework. By practically applying the framework to source window and door components for a modeled multi-residential building design, an integrated selection of 35% RCMs and 65% NCMs was proposed for the building design. Furthermore, sensitivity analysis is also performed for validation. The framework may disrupt the ongoing building design practices that deem material reuse problematic by enabling flexible sourcing of used and new building materials. A modular and iterative framework for facilitating reuse is thus contributed. [Display omitted] [ABSTRACT FROM AUTHOR]

The recycling of rare earth elements (REEs) yielded a dual benefit by alleviating supply constraints and contributing to environmental preservation. Independent recyclers (IRs), upon extracting REEs from waste materials, not only supplied the recovered REEs to the REE conglomerates but also engaged in competitive relationships by remanufacturing REE products. This study established a closed-loop supply framework, allowing the IR flexibly to choose between remanufacturing or direct sales strategies. Using the Cournot model under inequation constraints and real market data, to explores the impact of REE acquisition prices and recycling technologies on the closed-loop supply chain (CLSC) and society. The results indicated that: (1) The recycling mode and technology do not affect market share. Compared to the IR, REE conglomerate exhibit significant monopolistic advantages, occupying at least 85.1% of the market share, which can increase to a maximum of 98% as acquisition prices rise. (2) The acquisition price of recycled REE has an "inverse U-shaped" relationship with the profits of REE conglomerate and a positive relationship with the profits of IR. (3) The recovery rate is negatively related to the profits of REE conglomerate and positively related to the profits of IR. Increasing the REE recovery rate will enhance the profitability of the IR. (4) In terms of social effects, higher acquisition price of recycled REE continuously reduce consumer surplus and social welfare. Although the REE recovery rate does not affect consumer surplus, it has a significant positive impact on social welfare. [Display omitted] • Focuses on the market and social effects generated by reverse supply of rare earths. • Independent recycler (IR) can flexibly choose recycling and remanufacturing strategies. • Rare earth recycling and remanufacturing boost market diversification and societal welfare. • Recycling technology ensures IR profitability and the stability of the reverse supply chain. [ABSTRACT FROM AUTHOR]

Medical waste generated in healthcare facilities is categorized as hazardous due to its infectious, toxic, or radioactive properties, posing substantial risks to human health and the environment. This research proposes a bi-objective Mixed-Integer Linear Programming model for designing reverse logistics networks that enable both economical and safe medical waste management. Said model determines optimal quantity, depot locations, and routes for transporting waste from its generating points (hospitals) to the treatment and disposal sites (depots). This research addresses a bi-objective location routing problem, with multiple depots, time windows, capacity constraints, and variated waste types, across a multi-period horizon. It is innovative because no previous works have successfully dealt with such a combination of pragmatic features. The Location Routing Problem is an already well-known NP-Hard problem, with the additional aforementioned features further adding to its complexity. Thus, a genetic algorithm to solve large-sized realistic instances within reasonable computing times had been developed. Numerical experiments considered 20 random instances contrasting exact and approximate solution approaches. Also, a medical waste collection case study of a public hospital network in Atlántico Department, Colombia, delivering a Pareto frontier solution set, was introduced. The results demonstrated the efficacy of the proposed genetic algorithm in successfully addressing small instances of the problem, delivering outcomes comparable to the Mixed-Integer Linear Programming model. Furthermore, it yields good-quality solutions in a reduced computational time for larger instances deemed unfeasible for the Mixed-Integer Linear Programming model. This article contributes to both scientific literature and practitioners by presenting a decision-making tool designed to address the medical waste reverse logistics challenge under realistic scenarios. It approaches the issue from a bi-objective standpoint, jointly considering economic factors and biomedical safety. Additionally, the article introduces realistic and pertinent assumptions that have not been explored in previous literature. [ABSTRACT FROM AUTHOR]

Autoclaved aerated concrete is a popular building material in constructing one- and two-family houses because of its low thermal conductivity and fire resistance. Since autoclaved aerated concrete production rose significantly in the 1960s and 1970s, increasing post-demolition volumes can be expected in the following decades. However, these are currently landfilled as high-quality recycling options are still to be established. This study develops a new capacitated, multi-period, and multi-stage network model for optimising a Germany autoclaved aerated concrete recycling network. The multi-period character of the model enables the precise consideration of increasing post-demolition volumes by constantly allowing the move of recycling plants or opening new ones throughout the planning horizon. Additionally, the multi-stage formulation facilitates incorporating an optional second recycling step, which involves additional effort and higher revenues. The model aims to find a cost-minimised recycling network and identify optimal network transformations until 2050. Results show that recycling is preferred over landfilling. The optimised recycling network uses large recycling plants for economies of scale and opens new plants in the future to handle the expected increase in post-demolition autoclaved aerated concrete. Transport costs account for the largest share of total costs (50%), while fixed costs reach around 40%, and revenues offset approximately 20% of all costs. The total costs of the network reach about 2200 M€ until 2050, which is 4600 M€ (68%) less than without establishing recycling. The results offer new insights into cost-minimal network structures and their future development to encourage decision-makers to promote autoclaved aerated concrete recycling. • Post-demolition autoclaved aerated concrete (pd-AAC) wastes are expected to rise. • New network model for optimising an AAC recycling network is developed. • Recycling is preferred over landfilling. • Transport costs account for 50% of total costs. • Establishing recycling could save 4600 M€ in Germany until 2050. [ABSTRACT FROM AUTHOR]

As a breakthrough for alleviating the impact of the energy crisis and improving the environment, the electric vehicle (EV) industry is entering a period of rapid development. The growth of this industry is expected to lead to a dramatic increase in the quantity of end-of-life EV traction batteries in the future, posing significant challenges to environmental pollution and the sustainable development of the EV industry. This study addresses the cascade utilization and uncertainties of waste batteries, by incorporating the development weight of the match degree between urban commercial environments and facility development, proposes a fuzzy chance constrained programming model for the design of multi-level reverse logistics network (RLN) for retired EV batteries. The objective is to minimize network costs and carbon emissions, determining optimal facility locations and transportation distribution schemes. The mathematical model is validated through a real case study in the Yangtze River Delta Urban Agglomerations in China, and sensitivity analysis is conducted to explore the impact of various influencing factors on network design. The results indicate that the development weight significantly influence facility location decisions, while the quantity and quality of battery recycling have a substantial impact on the operational quantities of network facilities at different levels. [Display omitted] • A fuzzy programming model is constructed considering multiple uncertain factors. • Considering the commercial environment, cities are assigned development weights. • Facilities selection opens in cities conducive to their sustainable development. • Quantity, quality, uncertainties, and development weights impact network design. • Effective network design boosts sustainable growth in the electric vehicle industry. [ABSTRACT FROM AUTHOR]

EOL product returns has become more prevalently practiced in companies in developed nations as a response to government's strict regulations and customers' expectations. Correspondingly, there is a growing body of theoretical literature on the topic within this context as a crucial strategy to accelerate the development of the circular economy (CE). However, consumers' participation in EOL returns of heavy-duty machinery is immature in developing nations due to barriers, and studies are scarce on the analysis of the barriers. To fill this gap, this study aims to identify and analyze the barriers that hinder consumers' participation in EOL returns of heavy-duty machinery within a developing nation-Nigeria. Barriers were identified from published literature and experts' inputs and then, classified under technological, organizational , and environmental (supply chain) categories. Then, analysis was done via a methodology integrating interval-valued neutrosophic analytical hierarchy process (IVN-AHP) with multi-objective optimization on the basis of a ratio analysis plus the full multiplicative form (MULTIMOORA). Findings indicate that the environmental (supply chain) barriers rank the highest, followed by technological barriers. Specifically, consumers participation in EOL returns of heavy-duty machinery in Nigeria is mostly hindered by lack of regulations , lack of financial incentives , lack of skills , undeveloped reverse logistics system and poor access to facilities for recovery operations. Furthermore, we proposed some strategies to support stakeholders to mitigate the barriers. Thus, this study gives valuable guidelines to decision-makers to enable the transition to a CE paradigm in the heavy-duty sector within developing nations for utmost sustainability. [ABSTRACT FROM AUTHOR]

An increasing number of electric vehicle batteries will reach the end of their life cycle with the fast growth of electric vehicles. Since the recycling of retired electric vehicles batteries is of great significance in the light of resource utilization, ecological protection, energy saving and economic benefits, the proper management of electric vehicle battery recycling (EVBR) is crucial for achieving sustainable development. However, due to the involvement of multiple stakeholders, there are many potential barriers in the process of EVBR, and analyzing these barriers can significantly help the recycling management of waste electric vehicle batteries towards a circular economy. Although the literature has focused on analyzing obstacles to implementing reverse logistics for electric vehicle lithium battery recycling from a manufacturer's perspective, less attention has been paid to analyzing barriers to EVBR from a multi-stakeholder perspective. This paper thus aims to investigate the barriers to EVBR from a multi-stakeholder point of view, identify the main barriers affecting battery recycling, and analyze the interrelationships and hierarchies between these barriers. Based on expert opinions and literature reviews, this paper identifies twenty major barriers to EVBR and uses interpretive structural modelling (ISM) method to determine the interrelationships and hierarchies between the barriers, and finally classifies the barriers to EVBR into a seven-level structural model. Furthermore, matriced impacts corises-multiplcation appliance classement (MICMAC) analysis is applied to categorize the identified barriers to EVBR, and the twenty barriers are finally classified into three categories, namely dependent barriers, linkage barriers, and driver barriers. This paper discusses theoretical insights, managerial and practical implications, and measures to overcome EVBR barriers based on the results, which show that the lack of more appropriate incentives is a major barrier to EVBR implementation. This paper provides a solid theoretical foundation for the further development of battery recycling policies, and will also help relevant stakeholders and governments to better understand these barriers and adopt effective approaches to address them. [Display omitted] • This paper studies the barriers to electric vehicle battery recycling. • A hierarchy of potential electric vehicle battery recycling barriers is identified. • Measures to overcome the barriers to electric vehicle battery recycling are given. • Several key theoretical implications and managerial insights are provided. [ABSTRACT FROM AUTHOR]

The increasing prevalence of electric vehicles (EVs) will lead to a continuous rise in the quantity of waste batteries in the future. The topic regarding reverse logistics network design (RLND) for waste batteries has garnered extensive attention from both the academic and societal realms. However, relevant research in this area has yet to delve deeper. This research proposes a mixed-integer linear programming (MILP) model to optimize the multi-level reverse logistics network (RLN) of waste batteries from the perspective of a circular economy. The model aims to minimize costs as an economic objective and to reduce carbon emissions as an environmental objective. It introduces an expected weighting factor to balance these two conflicting goals. Various technological levels are considered for different processing facilities, thereby enhancing the sustainability of the RLN. The model is applied to a numerical case study in the Nanjing Metropolitan Area of China, obtaining optimal network facility location schemes, technological configuration plans, and transportation schemes between facilities. The study emphasizes the significance of selecting different technology types for facilities, as rational process configurations effectively reduce recycling operational costs and decrease network carbon emissions. Sensitivity analysis emphasizes the impact of uncertain factors on RLND, highlighting the imperative need for a forward-thinking approach to ensure long-term sustainable development for enterprises. Managerial insights aim to guide enterprises and government departments, encouraging the adoption of higher technology types to achieve the dual goals of increased revenue and reduced carbon emissions. • A multi-level reverse logistics network suitable for China has been designed. • Reasonable utilization of batteries with varying performance levels. • Consideration of diverse green technologies for enhanced network sustainability. • Reasonable tech configuration reduces costs and carbon emissions effectively. • Encouraging forward-looking network design with advanced technology adoption. [ABSTRACT FROM AUTHOR]

In the circular economy, an effective reverse supply chain is crucial, necessitating consumers to return end-of-life products rather than discard them. However, voluntary returns lack consistent motivation. While incentive programs might enhance return behaviors, the driving factors – whether based on sustainability principles or profit motives – remain unclear. Using self-determination theory, our study examines these dynamics in the cosmetics industry to uncover incentive efficiency and underlying mechanisms. We conducted an online experiment with 509 participants to empirically test four incentive schemes: 1) none, 2) financial, 3) sustainable, and 4) financial and sustainable incentives combined. Mean value comparisons indicate that the willingness to return increases for all participants after being informed about return opportunities, with financial and combined incentives differing significantly from the other groups, displaying the strongest intention to return. Experimental group-specific structural equation modeling analyses indicate that in all experimental groups, perceived intrinsic and extrinsic values positively affect the attitude towards returning packaging, which in turn is positively related to willingness to return. On the other hand, green consumer value only has a positive effect on willingness to return in the context of sustainable incentives. This study represents the first systematic approach to EOL incentive schemes, building on a new theoretical perspective and providing actionable strategies for retailers to advance the role of consumers in the circular economy. • Online experiment with 509 participants to test four different incentive schemes. • Financial incentives increase the willingness to return end-of-life products. • Sustainable incentives have no effect on willingness to return end-of-life products. • Extrinsic and intrinsic values have a positive effect on packaging return attitude. • Green consumer value is only effective in the context of sustainability incentives. [ABSTRACT FROM AUTHOR]

The use of pallets is crucial in supply chain and transportation processes, with wood pallets representing the most common packaging type in the US and in Europe. This work focuses on the environmental and economic impact of wood pallet reverse logistics, quantifying the context in which preemptive remanufacturing schedules are useful. Preemptive schedules allow the service provider to reduce transportation emissions and costs by combining multiple pallet components remanufacturing activities. However, this advantage has to be weighed against the losses associated with repairing or replacing a still functional component earlier than required. An integer linear optimization model analyzes this trade-off, first from an environmental then from an economic perspective. This model is applied using the two most common pallet types as case studies: 48- by 40-inch stringer and block pallets. Different handling and loading scenarios are considered. The impact of transportation distance on the efficiency of preemptive policies is explored through a sensitivity analysis. Results show the positive impact of preemptive remanufacturing on costs and CO 2 -equivalent emissions in all scenarios, with larger benefits in good handling or light loading scenarios. • Preemptive remanufacturing policies for block and stringer pallets are compared. • An optimization model analyzes costs and CO2eq emissions of preemptive repair schedules. • Preemptive policies result in costs and CO2eq emissions reduction by 30–40%. • Up to 50% cost and emission reduction with good handling or light loading conditions. • Results for block pallets are sensitive to distance below 200 km. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the supply chain and reverse channels of expanded polystyrene packaging connection in Brazil and their roles to discuss the main challenges towards circular economy. In order to achieve this goal, we propose a four-step method, anchored in the literature, technical visits, and interviews with experts in the expanded polystyrene (EPS) industry. First, the EPS supply chain was characterised and mapped, and secondly, the stakeholders and logistics activities in reverse channels were analysed. Third, the Brazilian legislation and chain structure was reviewed to obtain an understanding of how this can influence the activities developed in reverse channels. Fourth, with an analysis of the data collected before, the barriers to implement EPS reverse chain were presented. The main results establish that the EPS can complete one cycle of the circular economy, which is recycling, but products need to be separated and washed. The most significant waste generators are public and private institutions, residences, and retailers. Notable barriers to its recycling are a lack of understanding of the nature of expanded polystyrene recycling by Brazilian people, high transport cost due to material density, and the dispersion of post-consumer expanded polystyrene in several regions of the country linked with the small number of recycling facilities. Finally, this issue could be explored in industries and companies that require their managers to adopt strategies to improve reverse logistics in order to promote the circular economy. The companies' actions could facilitate a stronger circular supply chain since they could increase recycling efforts, reduce expanded polystyrene waste, and present new business models. The resulting generation of employment would contribute to the quality of life of contemporary society. The findings presented in the paper enable industries to identify and guide the most demanding significant steps and processes, and to shift the reverse chain and expanded polystyrene recycling to ensure that they operate more efficiently. • Reverse logistics as the first step towards circular supply chain. • The paper maps the expanded polystyrene packaging supply chain and its reverse logistics. • This paper presents the barriers that hinder the reverse logistics in Brazil. • The main challenges are related to the consumers and the recycling industries. [ABSTRACT FROM AUTHOR]

The irregular disposal of fluorescent lamps can cause environmental problems and harms human health. This work has the purpose of analyzing the process of discarding fluorescent lamps of the user industries, located in the metropolitan area of Belo Horizonte, in the State of Minas Gerais. The study was carried out in a quantitative and qualitative approach, with a semi-structured interview applied to the manager of the Special Residues Management of the State Environmental Foundation (FEMA), the head of the Office of the Municipal Secretary of Environment of the City Hall of Belo Horizonte and the director of the decontamination lamps company. It was applied a structured interview, with a questionnaire structured and applied to a random sample of 370 companies from the industrial sector consumers of fluorescent lamps. The results showed that the common waste is still the predominant disposal option, many respondents are not aware of the environmental legislation, and the industries also pointed out that there are many difficulties to implement reverse logistics mainly due to the absence of public power programs for the correct disposal. Therefore, there is a lack of government support and companies' initiative to comply with the legislation, which is bad considering it is a hazardous waste. • Fluorescent lamps are not properly discarded by Brazilian companies. • The companies are still unaware of Brazilian legislation regarding the proper disposal of solid waste. • The government authority is still very negligent. • Brazilian companies are still unaware of the economic potential of proper disposal of fluorescent lamps. [ABSTRACT FROM AUTHOR]

As the speed of mobile phone updates continues to accelerate, the self-service mobile phone recycling mode, led by third-party reverse logistics providers (3PRLs), has ushered in an important developmental era. This paper proposes a novel interval-valued Pythagorean hesitant fuzzy best-worst multi-criteria large group decision-making method to research the selection of 3PRLs. To minimize the influence of subjective factors and maximize the mathematical analysis method, some related improvements have been made to the traditional best worst method (BWM). First, in order to make an effective strategic assessment and achieve overall optimization of the organization, evaluators are grouped by the self-organized maps (SOM) method to balance the coordination ability and professional level of different groups. Next, the interval Pythagoras hesitant fuzzy set (IPHFS) is used to evaluate the criteria of 3PRLs selection. Then, according to above evaluation results, the BWM method and deviation model are combined to determine the weights of criteria. Finally, the traditional BWM is extended by ranking functions to determine the optimal 3PRL. The applicability of the proposed method is numerically demonstrated by solving a real case, and the key conclusions are that the technical factor is important to affecting the choice of 3PRLs. At the same time, the quantity and price of recycled components on End of Life (EOL) and used mobile phones also have important impacts on the selection of 3PRLs. [ABSTRACT FROM AUTHOR]

Under the background of the development of construction waste recycling in China, optimizing the site of construction waste recycling and disposal plant is important, considering not only the cost of construction waste recycling but also the impact on the surrounding environment. This study aims to minimize the cost and negative environmental effects. In order to find the best method to solve the problem of multiobjective function optimization, we propose a multiobjective location model which combines genetic algorithm with probabilistic robust optimization. The model first uses genetic algorithm to get preliminary result and then it uses probabilistic robust optimization to find the optimal solution. The preliminary results show that 1, 3, 5 of the candidate sites more cost-effective and environmentally friendly than other. The fitness value converges at a stable value of 1.55 × 10−5, and the Pareto optimal frontier presents considerable clustering characteristics, which prove the rationality and operability of the site selection optimization model. Meanwhile, the robust model analysis under the given uncertain environment achieves the purpose of further optimization of the site. The research results can provide the government with a theoretical basis for the site selection of construction and demolition waste recycling plants. • A new multiobjective location model is proposed for site selection of waste recycling plant. • Quantitatively describe the impact of cost and environmental constraints on site selection. • The multiobjective location model using GA and Pro more efficiently and accurately than traditional methods. [ABSTRACT FROM AUTHOR]

Over the last twenty-five years, there has been a growing interest in the disassembly line balancing. The key role in reverse supply chains is the most important motivation behind this interest. Cleaner production can be possible via reverse supply chains. The objective of this study is to analyze disassembly line balancing articles in an extended way. In order to achieve this, traditional literature review is combined with bibliometric and social network analysis. This methodology gives the opportunity to identify trends, evolutionary trajectories and key issues in a more scientific and objective way. Future Study Realization Analysis (FSRA) is also proposed in this review as a new analysis tool. It can be able to see all suggestions for future studies in all studies and whether they were studied or not. It is found that disassembly line balancing is immature and there need to write articles to enlarge the problem. It can be seen from bibliometric analysis that there is a rapid development in the last five years. Social network analysis results show that Surendra Gupta is the most authoritative researcher in the network. The noteworthy result of the FSRA is that the future directions of the first article on DLBP are still waiting to study. Findings of this review can be useful for future research in disassembly line balancing. • Disassembly line balancing problem is comprehensively reviewed. • Traditional review is combined with bibliometric and social network analysis. • Future study realization analysis is proposed as a new tool. [ABSTRACT FROM AUTHOR]

Increasing concerns about environmental sustainability strategies, take-back laws and natural resource limitation has highlighted the impact of disposing end-of-life (EOL) electrical and electronic products. To cope with this challenge, manufacturers have integrated reverse logistics into their supply chain or chosen to outsource product recovery activities to third parties. This research studies the remanufacturing processes of reusable products and parts, cost and demand of remanufactured products and parts to determine return quality thresholds during multiple production period. We present a general framework for a third party remanufacturer, where the remanufacturer has the alternative of supplying parts to external suppliers or bringing the disassembled parts to 'as new' conditions. The problem is formulated as a mixed integer non-linear programming (MINLP) problem, where with proposed discretization, the problem turns into a quadratic mixed integer programming (QMIP) problem. Finally, the impact of the quantity of returns, operational cost and upper bound disposal rate using a case numerical study of a personal computer (PC) remanufacturing facility has been studied. [ABSTRACT FROM AUTHOR]

Abstract The closed-loop network design of a hybrid manufacturing and recovering system plays an important role on improving both the production efficiency and environmental quality, especially under a multi-product multi-stage scenario. Besides, with the growing awareness of environmental concerns by legislators, decision makers have been forced not only to enhance utilization of the returned products or components but also to control carbon emission of the whole hybrid system. To optimize the closed-loop logistics superstructure design, a multi-objective model integrating the manufacturing and recovering process in a multi-product multi-stage environment is proposed in this research. Both operations cost and environmental influence are regarded as two objective categories. In addition, the carbon emission regulation is considered in the model by integrating and characterizing the energy input and greenhouse output throughout the hybrid system. Finally, a numerical case originated from an electronic assembly plant is presented under different scenarios to illustrate the effectiveness of the proposed approach. A sensitivity analysis is given to compare the impacts of carbon emission and return rate on each sub-objective of the logistics and environmental issues. Highlights • A closed-loop network for a hybrid manufacturing and recovering system is designed. • The energy input and greenhouse output models are proposed and embedded. • A multi-objective multi-echelon model for carbon-efficient scheduling is proposed. • Impacts on interdependence of economic and environmental dimensions are analyzed. [ABSTRACT FROM AUTHOR]

Abstract Evidence suggests that manufacturing companies have tried to address the current environmental challenges derived from their operations by implementing various operational environmental sustainability approaches, including green manufacturing (GM), cleaner production (CP), green lean (GL), green supply chain management (GSCM), reverse logistics (RLs) and circular economy (CE). However, although their adoption is well documented in developed nations and few other countries, very little has been done to understand such phenomenon in a rapid developing country such as Thailand. This paper aims at filling this gap by providing light into some fundamental issues regarding the implementation of these approaches in the manufacturing sector of Thailand. A survey-based exploratory research was carried out based on 287 Thai manufacturing companies. The data was analysed using a combination of descriptive and inferential statics. The study revealed that a large amount of investment capacity, and proper training & knowledge are needed to fully implement the studied operational approaches. This resulted in some of the weakest elements of Thai manufacturing firms and hence the main barriers to their implementation. The study also showed that Thai manufacturing firms consider the impact on the environment and benefits from adopting these operational approaches as company's policy and own initiative, environmental awareness, and cost saving from conservation of energy as the main reasons for adopting the studied operational approaches. Finally, the findings also indicate that Thai manufacturing firms tend to implement them because of internal factors and that they lack of motivation from external factors and involvement from other stakeholders. The paper extends the current limited knowledge on the deployment of operational environmental sustainability approaches in Asia, and its results can be beneficial for organisations that aim at effectively adopting them to improve their operation's sustainability. Highlights • Evidence of the implementation of sustainability approaches in Thailand is limited. • Paper provides light into fundamental issues regarding their adoption. • 287 Thai manufacturing companies participated in this survey-based exploratory study. • Study reveals degree of implementation, main drivers and barriers of the studied approaches. [ABSTRACT FROM AUTHOR]

Abstract As the number of scrap cars increases rapidly, the management of their reverse logistics (RL) process has become an urgent issue for decision-makers in contemporary China. The process, capable of generating profits as well as minimizing negative environmental effects, mainly includes products acquisition, collection, inspection and disposition. Although the selection of take-back patterns is an essential part in the process, it is not well addressed by existing studies. Involving numerous related factors, the evaluation and selection of the take-back patterns of scrap cars are a comprehensive problem that can be formulated as a multi-criteria decision making (MCDM) problem. In this paper, we propose a complete method to solve it systematically. Three patterns quite suitable for China are presented and a novel criteria system is developed for choosing the best one. The unavoidable uncertainty in practical situation is also considered in this work. We integrate the grey method and Decision-making and Trial Evaluation Laboratory (grey DEMATEL) to determine the weights of nine criteria, and a fuzzy method and Vlse Kriterijumska Optimizacija I Kompromisno Resenje (fuzzy VIKOR) are adopted to rank the three patterns based on expert evaluations. Sensitivity analysis is also used to test and verify the robustness of the proposed method. Finally, we draw a conclusion that the Producer Responsibility Organization Take-back pattern whose main body is formed by manufacturer union organization is most suitable for China. The study results could provide a theoretical guideline for decision-makers in China as well as other developing countries. [ABSTRACT FROM AUTHOR]

Abstract Recently, a growing interest has been devoted to the role of buying firms in promoting sustainability across supply chains. However, relatively little attention has been given to how the behaviour of a buying firm affects the performance of reverse supply chains. Within this context, this paper investigates the role of Supply Chain Leadership styles on suppliers' performance dimensions related to reverse product flows. Furthermore, the mediating role of two governance mechanisms (namely trust and legal-legitimate power) on this relationship is examined. This study employs structural equation modelling to analyse data collected from 190 manufacturing companies in Malaysia. The paper concludes that transformational and transactional leaderships are significant and positive contributors to suppliers' reverse supply chain performance; trust and power significantly mediate these relationships. [ABSTRACT FROM AUTHOR]

Abstract Recycling aims at preventing rapid depletion of natural resources while transforming produced waste into value for economy. However, this process becomes a major challenge in automotive industry, which requires cooperative engagement of multiple players within a complex supply chain. In line with the essence of the topic, government agencies around the world issue directives drawing regulatory frameworks for designing recycling operations comprising various activities such as collection of end-of-life vehicles (ELVs), recovery of reusable components, shredding ELV's body, recycling valuable materials and disposal of the hazardous waste. In general, the amount of returned product in a reverse logistics network is highly uncertain, and the ELV market in Turkey is no exception to this. For that purpose, this study aims developing a fuzzy mixed integer location-allocation model for reverse logistic network of ELVs conforming to the existing directives in Turkey. Accordingly, this study uses a novel approach and assumes that ELV supply in the network is uncertain. The merit of the proposed mathematical model is proved on a real world scenario addressing the reverse logistics design problem for ELVs generated in metropolitan area of Istanbul. The network generated specifies that recycling process is not profitable under the existing circumstances with the given level of supplied ELV and the returned product records per capita in Istanbul are far beyond the EU averages. Consequently, sensitivity analyses question the reliability of the obtained results. [ABSTRACT FROM AUTHOR]

Abstract This study analyzes the effect of multi-attribute decision making (MADM) on the efficiency of the end-of-life vehicle (ELV) reverse logistics industry in the context of the circular economy to improve resource utilization efficiency. In this paper, the DEA-TOPSIS method, based on a prediction model of Triple Exponential Smoothing (TES), is adopted for multi-attribute decision making with a view to improving industry efficiency, Data Envelopment Analysis (DEA) is used to calculate the input and output indicators' efficiency values and the slack movements of the indicators of input and output decision-making unit's (DMU's) base with TES as the decision-making basis. Meanwhile, the Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is used to rank alternative decision-making schemes. Moreover, the ordering is also carried out using the Additive Weighting, Weighted Product and Elimination et Choice Translating Reality (ELECTRE) method. In this study, the DEA-TOPSIS method is used to make multi-attribute decisions about industry efficiency. Taking Shanghai's ELV industry as an example, this study utilizes 2017 data from seven member-enterprises of the Shanghai End-of-life Vehicle Professional Committee; it uses the DEA-TOPSIS method based on TES to conduct an empirical study on multi-attribute decision making to improve efficiency and analyze efficiency improvement through alternative decision-making schemes. The findings show that the DEA-TOPSIS method based on TES is effective for multi-attribute decision-making to improve the ELV reverse logistics industry's efficiency. The multi-attribute decision-making in this paper facilitates the management and investment decision making of the ELV recycling industry. It also provides an effective solution for managers and researchers in the ELV industry to improve its efficiency. Highlights • Researched MADM to improve the efficiency of the end-of-life vehicles reverse logistics industry. • Used DEA to measure technical efficiency and pure technical efficiency. • Developed a TOPSIS decision-making matrix with each indicator's slack movement as the attribute indicator. • The slack movements evaluated based on a prediction model of TES is proposed as the decision-making matrix. • The AW, WP and ELECTRE method are compared with the TOPSIS in terms of the ranking of decision-making alternatives. [ABSTRACT FROM AUTHOR]

Abstract Rare earth elements (REEs) such as neodymium (Nd) and dysprosium (Dy) are indispensable in modern society because they are vital for creating powerful neodymium-iron-boron (NdFeB) magnets used in many technological applications. These elements have been subject to a significant supply uncertainty. A promising strategy to alleviate supply risk is value recovery from end-of-life (EOL) products. This paper proposes a reverse supply network to optimize: 1) the locations and capacities of dismantling and recycling facilities, and 2) the transportation flows between collection centers, dismantling facilities, recycling facilities, and sales points. Two objectives are considered: maximizing profit and environmental benefits. A Pareto front is created that shows non-dominated optimal solutions. When the model was applied to the United States, California was found to be the most important state for EOL product collection, representing up to 22% of the total collection volume. Nevada, Tennessee, and Delaware were the key states for EOL product dismantling, and Nevada, Texas, and Delaware were the key states for NdFeB magnet recycling. A sensitivity analysis was performed to measure the impact of different NdFeB magnet price on the overall network design. While REE recovery is still at an early stage of the development, this research serves as a blueprint for constructing a profitable and environmentally friendly NdFeB magnet reverse supply chain. [ABSTRACT FROM AUTHOR]

Abstract Waste disposal is a worldwide concern. In the case of the textile and clothing industries, consumption has increased steadily, especially in the clothing business, which generates large amounts of post-industrial waste. The objective of this article is to identify opportunities for improvement in the use of reverse logistics (RL) in clothing industries, as well as to list the existing strengths in the valuation of textile waste (TW) and minimize environmental impacts. To achieve this objective, a questionnaire was developed, validated and applied in a clothing cluster. The questionnaire assessed strengths and weaknesses in 8 dimensions using 32 assertions involving reverse logistics and management of textile waste. We identified in the research that: (i) there are no route facilitators between RL and TW in clothing industries; (ii) there are opportunities for the textile companies to increase the adoption of RL to combat TW; (iii) the main improvement opportunities for increasing cluster advancement in terms of RL and TW are: reuse of TW by the generating company and separating waste according to the composition of materials, which would facilitate the possibility of recycling and disclosing to consumers the importance of social and environmental practices. Conclusion remarks point that, despite the existence of strengths in the use of the RL for the TW valuing in the clothing industry, it is still required a readjustment of the destination of TW as a by-product to be used in a new cycle. Highlights • Opportunities are identified to increase the adoption of reverse logistics in the clothing industry. • The textile residue must be seen as a co-product (raw material) to be used in a new cycle. • Opportunities for improvements to increase the advancement in a cluster of the clothing sector. [ABSTRACT FROM AUTHOR]

Abstract The pharmaceutical industry is increasingly employing reverse logistics practices in their supply chain activities to be more sustainable. However, the absence of voluntary take-back for relocation to needy markets limits the benefits of reverse logistics for sustainability practices in India. Production planning and RL design without taking product category and feedback into consideration are ineffective. Resulting in a pressing need to devise policies by incorporating economic costs, environmental costs, and effective product returns in the model aimed at sustainability through RL. This article demonstrates how the principles of Taguchi's Orthogonal Arrays can be applied in a system dynamics model highlighting the presence of two brand categories (preferred and un-preferred) and their respective RL processes that substantially influences product shelf life, maximum allowable sales loss, and delays in the reverse logistics process. The contributions of this research are: (i) market flooding of expired stock can be alleviated for longer shelf life and preferred brands by increasing marketing efforts. (ii) Increasing safety stocks helps sales in a dynamic market but does not alleviate market flooding. (iii) Due to the absence of feedback between reverse and forward logistics processes, improvements in reverse logistics attributes like product return and claims processing delays do not impact sales rather it alleviates market flooding. The medicine take-back policies in India need to be sensitive to the category of the product. There is also a potential for placing checks on the supply side to alleviate market flooding, and a need to provide feedback between reverse and forward logistics through risk-sharing agreements in order to enable product take-back for both disposal and relocation to needy markets. The possible research extensions include the structural changes in the proposed model to test RL, for sustainability policies and the study of brand/product level competition. Manuscript Highlights • Dynamic relations among factors like production, sales, reverse logistics practices and industry growth is mapped. • Model developed consists of reverse logistics practices for preferred and un-preferred brands. • System Dynamics model is used to capture the market dynamics of the Indian pharmaceuticals industry. • Important control factors are identified to improve existing RL and sustainability. • Structural changes using the SD model are suggested to achieve sustainable goals by the industry. [ABSTRACT FROM AUTHOR]

Abstract An overview of relevant literature shows how supply chain and network flow models represent useful tools in the area of clean energy generation and processing related waste. This paper deals with a specific network flow problem where the mixed municipal waste as a secondary and partly renewable energy carrier is transported from waste producers (municipalities), through pre-processing facilities, to its final treatment in waste processing units and in which the optimal flow is desired. The results obtained for the minimum total costs, including treatment and transportation, correspond to production and savings of a certain amount of CO 2 and other greenhouse gases which is described by Global Warming Potential (GWP). The average cost was 74 EUR/t and average GWP was 37 kg CO 2eq /t. The GWP contribution varies among the waste producers as a result of treating waste in different places and various technologies. However, to identify the individual contributions, the detailed waste flow identification is required. The flow distribution is unknown due to the effect of merging and splitting waste streams in the network. For this reason, a consequent network flow problem for exact waste flows identification is proposed. The model follows the principle ideas of multi-commodity network flow modelling and it reveals the variability of cost and GWP contribution for all producers in the investigated area. The proposed method has been tested through a case study considering treatment of mixed municipal waste. The results obtained by the original implementation in GAMS are presented and discussed in detail. The GWP contribution varied between −173 and 880 kg CO 2eq /t and significant waste producers were identified in the network regarding GWP. The results are important for setting the target for emission reduction in individual regions and for particular producers. The principle can be applied in general to any commodity and network flow problem. Highlights • Emission, processing and cost analysis in a feasibility study for waste treatment. • Branching network structure lead to the loss of information in producer waste flow. • A new computational approach extends a basic flow and capacity allocation problem. • Waste flows are identified to evaluate GWP contribution of the particular producer. [ABSTRACT FROM AUTHOR]

Abstract Reverse logistics (RL) has been regarded as a key driving force for remanufacturing. However, there are great uncertainties in terms of quality and quantity of used components for RL. There are also complexities in suppliers and operations. These make decision-making of RL very complex. In order to identify the best collection mode for used components, a demand-matching oriented Multiple Criteria Decision Making (MCDM) method is established. In this method, the damage level and remaining service life are firstly incorporated into the evaluation criteria of reuse modes, then a hybrid method (AHP-EW) that integrates Analytic Hierarchy Process (AHP) and Entropy Weight (EW) method is applied to derive criteria weights and the grey Multi-Attributive Border Approximation Area Comparison (MABAC) is adopted to rank the collection modes. Finally, sensitivity analysis is implemented to test the stability of the proposed method, and a demands-matching method is proposed to validate and evaluate the feasibility of the optimal alternative. The collection of used pressurizers is taken as case study to validate the applicability of the proposed model. The results showed the effectiveness of the proposed method in MCDM of RL. [ABSTRACT FROM AUTHOR]

COVID-19's aftereffects have had a significant impact on our daily lives. The recent pandemic caused by the new coronavirus epidemic has increased the production of infectious medical waste (IMW) and demand for medical care and protective equipment. Although national and local initiatives are primarily concerned with saving lives and bolstering local economies, hazardous waste management is essential for reducing long-term human and environmental health threats. In this situation, establishing a dependable and efficient reverse logistics network of IMW can prevent the spread of viruses. Few studies have been conducted on this topic and those that have rarely considered how to operate a network of multiple medical waste generation centres (MWGCs) cost-effectively and risk-averse. This study proposes a framework for reducing the accumulation of IMW products using reverse logistics in the context of medical waste management. The optimal values of the multiple objective functions were determined using a multi-objective optimization model. Our proposed framework considers four objective functions and their respective constraints while using data-driven digital transformation in reverse logistics energy optimization for managing single-use medical waste. [ABSTRACT FROM AUTHOR]

The circular construction hub is a logistics point for the storage, processing, and distribution of secondary construction materials. However, its site selection is dampened by the lack of detailed spatial information on material flows. In this study, the quantities and the spatial distribution of material flows are projected using a bottom-up building stock model. The material flows are integrated with logistics networks to assess the environmental impact of transporting materials between the building stock and the circular construction hub. The model is demonstrated on the building stock of Leiden, a municipality in the Netherlands. The results show that the location of future construction and demolition activities has a major impact on transportation carbon emissions. As construction decreases and demolition increases, the relative share of transportation carbon emissions from recycling will increase. The comparison between the two candidate sites for the circular construction hub is made to select the site with lower total transportation carbon emissions. By considering the evolution of building stock, the model can help urban planners make a more comprehensive decision on the location of the circular construction hub. •The quantities and spatial distribution of building material flows are projected using a bottom-up building stock model. •Both forward and reverse logistics networks are considered to account for the transportation carbon emissions of secondary materials. •The location of future construction and demolition activities has a major impact on transportation carbon emissions. •The relative share of transportation carbon emissions from demolition waste recycling may increase due to the reduction in annual new construction. [ABSTRACT FROM AUTHOR]

With the pollution caused by express packaging waste, eco-packages are being commonly used to promote a green supply chain. However, extant research has yet to address the efficacious reverse logistics network design problem while considering both economic and environmental consumption in the recycling process. In this study, a multi-echelon reverse logistics network is designed to collect eco-packages from customers, instead of door-to-door recycling by couriers. This study aims to solve the capacity location-routing problem in a reverse logistics network integrated with the incentive mechanism for customers, which is regarded as NP-hard. To avoid the combinatorial explosion, a multi-objective hybrid genetic algorithm-tabu search (MOHGATS) is developed to reduce search space and improve search speed by changing search strategies. Computational experiments are conducted to verify the proposed model and algorithm based on several test instances and a real-world case study. The impacts of the quantity of eco-packages, the incentive costs for customers, and the quantity and capacity of recycling stations on the reverse logistics network are explored from both economic and environmental perspectives, providing a reference for practical operation and promotion of eco-packages on a large scale. [ABSTRACT FROM AUTHOR]

Distribution networks aim to get the right products to consumers at the right time and in the right place. When consumers return these products, another type of logistics network is involved. This function of returning end-of-life products is referred to as reverse logistics. A critical characteristic of these reverse logistics networks is the dependence of material flow on the voluntary action of the consumer. Therefore, the success of an end-of-life collection strategy depends on the ability to anticipate the collection rate of end-of-life products at specific locations by understanding the factors that influence consumer behavior. However, there is no established tool or methodology for assessing the impact of consumer decisions on reverse logistics material flows. Therefore, this paper proposes an agent-based simulation tool to predict the performance of a reverse logistics network, taking into account the location of collection points, socio-demographic information, attitudes towards sustainable development, as well as the consumption profile. More specifically, this paper presents the configuration, calibration and validation of a simulation tool modelling the return of empty glass bottles in a small group of municipalities in Québec, Canada. Experiments also demonstrate the tool's ability to provide useful information to support the design of collection strategies that maximize return rates while minimizing installation and operating costs by optimizing the number of drop-off depots in the reverse logistics network. • Drop-off points for post-consumer voluntary glass collection. • Agent-based simulation model of consumer waste management (at consumer level). • Configuration, calibration and validation of a simulation model with empirical data. • Experiments performed with the model evaluates different logistics configurations. • Results suggest that population-specific characteristics can influence return rates. [ABSTRACT FROM AUTHOR]

An upcoming directive requires the recycling of end-of-life (EoL) textiles. In this paper we show how this recycling could be arranged in such a way that the value of the recycled material exceeds the costs of recycling. We approach this via an embedded case study by examining the end-of-life (EoL) textile recycling supply chain in Finland. The study builds a cost model based on empirical and secondary data to estimate and compare the costs of different alternatives for the EoL textile supply chain. Different alternatives are designed by using postponement-speculation concepts. The four identified EoL textile supply chain alternatives are: postponed centralized sorting with manual, semi-automated or automated sorting, and speculative local sorting. The results suggest that postponed centralized sorting is the most efficient, as it enables investments in sorting automation, but it requires local pre-sorting to avoid contamination. At least in the EoL textile supply chain, the logic of using postponement-speculation strategies is the inverse of that in forward supply chains. Therefore, when in forward supply chains look possibilities for postponement, speculation strategies are relevant in EoL supply chains. Additionally, the proposed recycling system concentrates on material recovery as currently majority of EoL textile end up as disposal or they are exported for developing countries for reuse even if the items are no longer reusable. • Value of obtained materials may exceed the costs of end-of-life textile recycling. • Postponement-speculation concepts offer new approach to design reverse supply chains. • Study provides cost comparison of different alternatives for the EoL supply chain. • Defining the place of sorting collected materials is the key issue. [ABSTRACT FROM AUTHOR]

Abstract Reverse logistics is indispensable for resources reuse and circular economy, and a reverse logistics network optimization problem for end-of-life vehicles is studied frequently. Recent researches have focused on the material flow for different end-of-life vehicles. However, the primary question for an end-of-life vehicles recovery network is to determine optimal network nodes. To account for it, we considered a facility location allocation problem of end-of-life vehicles recovery network, and established a mathematical model to solve it. The model is used to achieve the minimization of cost for deciding optimal locations of end-of-life vehicles recovery network. The facility location allocation problem is a non-deterministic polynomial complete problem proved with increase in the number of candidate locations. This type of problem usually handled by a metaheuristics. Therefore, we proposed a valid novel approach based on artificial bee colony to solve the problem. Artificial bee colony is an optimization method that imitates bee behavior. Also, the proposed algorithm is applied to two different scale real-life cases, and some comparisons with several presented algorithms are presented to illustrate the effectiveness of the presented method. [ABSTRACT FROM AUTHOR]

Abstract This paper aims to better manage the reverse supply chain of the automotive industry in the context of green, circular, and sustainable development by predicting the number of end-of-life vehicles to be recycled through the establishment of a multi-factor model. The prediction of the number of end-of-life vehicles to be recycled in this paper will support the end-of-life vehicle recycling industry in terms of recycling management and investment decision-making and provide a reference for the formulation and implementation of policies relating to end-of-life vehicles. To solve the problems posed by nonlinear characteristics and uncertainty in the number of end-of-life vehicles recycled, and deal with the multiple factors influencing the recycling number, this paper presents a combined prediction model consisting of a grey model, exponential smoothing and an artificial neural network optimized by the particle swarm optimization (PSO) algorithm. Using Shanghai's end-of-life vehicle reverse logistics industry as an example, this study selects historical data about end-of-life vehicles recycled in Shanghai during the 2005–2016 period, identifies multiple influential factors, and validates the effectiveness and feasibility of the prediction model through empirical research. This paper proposes an effective prediction model for end-of-life vehicle industry managers, researchers, and regulators dealing with the industry's common challenges. Highlights • Hybrid prediction model based on grey model and artificial neural network predicts end-of-life vehicles recycling volume. • Hybrid prediction model improves prediction performance on data featuring randomness and small sample size. • Hybrid prediction model improves prediction performance of end-of-life vehicles recycling volume affected by multi-factors. • Artificial neural network prediction model using particle swarm optimization algorithm has better prediction performance. • Model proposed in this paper is tested by application to real-life data from the reverse logistics industry in Shanghai. [ABSTRACT FROM AUTHOR]

Abstract Corporate social responsibility (CSR) is gaining popularity among researchers and practitioners due to its strong influence on the global market. Recently, the decision-makers of footwear companies have given special attention on CSR issues due to increased stakeholders' awareness on social and environmental issues. In this study, the fuzzy analytical hierarchy process (FAHP) has been used to identify and evaluate drivers to CSR-based sourcing in the context of the footwear industry of Bangladesh. A total of 20 drivers are identified through a literature review and experts’ opinions. The results indicate that financial drivers are paramount toward CSR-based sourcing into existing supply chains followed by environmental drivers. This study offers some managerial implications that may assist companies to incorporate CSR-based sourcing into existing supply chains. The identified drivers may guide footwear companies in strategic planning to create a sustainable business structure in the competitive market. Highlights • Identification of key drivers and sub drivers for implementing CSR-based sourcing in the footwear industry. • Model framework development using Delphi method and fuzzy AHP. • Prioritization of the key drivers and sub drivers for implementing CSR based sourcing in the footwear industry. • Discussion of practical implications of the model frameworks. [ABSTRACT FROM AUTHOR]

Abstract The application of reverse logistics (RL) is expanded prominently due to environmental issues, and profit related to the returned products. RL includes all activities associated with product recovery such as repairing, recycling, remanufacturing, and disposing. Several partners are required to collaborate efficiently on account of obtaining optimal outcomes. In this sense, the selection of partners in RL can be considered as a multi-criteria decision making (MCDM) problem. In this research, it is aimed to apply fuzzy analytic network process (FANP) to convert the environmental qualitative factors to the quantitative parameters. Furthermore, an optimization model consisting of multiple echelons, components, and products is introduced for the RL in multiple periods. A multi-objective mixed-integer linear (MILP) programming model is employed to maximize the total profit, green practices, and on-time delivery with minimization of defect rate in the proposed RL. Finally, the multi-objective model is solved to achieve non-dominated solutions between the objectives. The proposed method is helpful in selection of the best third party reverse logistics provider. Highlights • Electronic reverse logistics configuration and third party selection concurrently. • Utilizing fuzzy ANP method to consider green performance. • Proposing a multi-objective model for an electronic reverse logistics network. • Considering profit, environmental practice, defect rate, delivery as objectives. • Applying distance technique and ε -constraint method to find non-dominated solutions. [ABSTRACT FROM AUTHOR]

Abstract With the focus on sustainable development, the value recovery from End-of-Life (EOL) and End-of-Use (EOU) products has been given considerable attention by the whole society. Reverse logistics is the process for value recovery and re-creation through a series of activities, i.e., repair, remanufacturing, recycling and energy recovery. However, due to the stochastic reverse product flow, unstable quality of used products, and the price fluctuation of recycled and remanufactured products, the planning of a reverse logistics system is more complex compared with that of a forward supply chain. In this paper, we propose a two-stage stochastic bi-objective mixed integer programming model for the network design problem of a multi-product multi-echelon sustainable reverse logistics system under uncertainty, which aims at providing a set of Pareto solutions between profitability and environmental performance. Furthermore, due to the heterogeneous nature, the processing operations performed at remanufacturing and recycling centers for different products are by no means identical. Different from the previous modelling efforts derived from a genetic "capacitated location problem", this paper considers the impact from the system flexibility on sustainable reverse logistics network design. Thus, the model is formulated in two parallel ways with either efficiency-focused non-flexible capacity or effectiveness-focused flexible capacity. The experimental analysis illustrates that increasing environmental requirement will decrease the profitability of the reverse logistics system, while, increasing flexibility may yield positive impacts on both economic and environmental performance when the efficiency loss is kept at a proper level. Highlights • Incorporating flexibility in sustainable reverse logistics network design. • Formulating mathematical model for decision support under uncertainty. • Different solution methods were tested, compared and discussed. • Results were analyzed for providing managerial implications. [ABSTRACT FROM AUTHOR]

Abstract A comprehensive tyre remanufacturing supply chain strategic planning model is proposed under uncertainty and group decision making environment for reconfigurable supply chain to integrate business economics with carbon tax policy. To solve the proposed fuzzy multi-objective mixed integer programme model, a methodology is designed by combining various techniques. Numerical experiments were conducted to provide important policy insights for industry practitioners and the government such as (1) developed carbon tax-reward policy and carbon-tax- reward-forex policy other than carbon tax policy for future tyre remanufacturing supply chain carbon emission policies, (2) evaluated the possible influence of distance of used product suppliers from initial deposit facility on reconfigurable tyre remanufacturing strategic supply chain planning, (3) designed the measure of the greenness i.e. the greenness index of various tyre remanufacturing supply chains to compare various supply chains in the tyre remanufacturing industry, (4) suggested the foreign exchange (forex) reward rate for a tyre remanufacturing supply chain on basis of its greenness index in the tyre remanufacturing industry. Graphical abstract Image 1 Highlights • Tyre remanufacturing network design with carbon emission in group decision making. • Integrated solution methodology using various techniques in group decision making. • Proposed carbon tax, carbon tax - reward and carbon-tax- reward-forex policies. • Proposed Greenness index to compare Tyre remanufacturing supply chains. • Proposed Forex saving reward rate for Tyre remanufacturing supply chains. [ABSTRACT FROM AUTHOR]

This paper investigates a two-echelon reverse supply chain (RSC) consisting of a single remanufacturer and a single collector. The collector by offering a reward persuades consumers to take back their used products. Only items that meet the minimum quality level are accepted to be refurbished. There are two sources of uncertainties in the investigated RSC: (1) uncertainty in quality of returned products, (2) uncertainty in remanufacturing capacity. Under these circumstances, the amount of offered reward to consumers is a key problem. To optimize the whole RSC, the collector should determine the reward amount by considering the possibility of idle/overload capacity of the remanufacturing process. In the investigated RSC, the quality of returned products follows a uniform distribution and remanufacturing capacity follows a normal distribution. A customized revenue sharing mechanism is developed to share the risk of uncertainties between two members, fairly. The results indicate that, when remanufacturing capacity is limited, the suggested revenue sharing contract is able to share risks between participants and creates a win-win situation. In addition the suggested scheme is able to achieve channel coordination. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive content analysis-based literature review of studies on Inventory Routing Problem incorporating sustainability-related aspects. A total of 40 journal articles are selected from Web of Science and Google Scholar databases, and are reviewed by categorizing them into single-objective and multiple-objective models. The review suggests that studies with single-objective models covered areas including waste management (in reverse logistics models), returnable transport item management (in closed-loop supply chain models), waste prevention and reduction (in models with perishable products), and emission reduction (in models with emission caps and carbon price). Studies on reverse logistics are limited to collecting and storing waste at a collection site, while including waste processing and disposal operations could make them more applicable. Studies on closed-loop supply chains are few with a focus on managing returnable transportation items. Future studies could consider remanufacturing, recycling and disposal of products for efficient waste management. Most of the papers in logistics of perishable products considered waste prevention rather than waste reduction. Previous studies related to emission reduction using carbon policies mainly focused on emissions from transportation. Including emissions from other logistics operations could be useful from a practical perspective. Relatively few studies developed multi-objective models. Environmental objectives in multi-objective models focused on minimizing total emissions. Few studies considered social objectives related to minimizing inventory of hazardous material and infectious medical waste, and improving customer satisfaction. Other social aspects such as those related to traffic congestion and job creation could be considered in future studies. Furthermore, application of efficient models and solution approaches to real case studies could be valuable. [ABSTRACT FROM AUTHOR]

Awareness of environmental pollution, interest in recycling, and the importance of closed-loop supply chain management are all on the rise. In a closed-loop supply chain, production planning is influenced by uncertainty not only from customers’ demand, but also from collectors due to difficulties in the reverse logistics flow. Therefore, it is important to develop a robust closed-loop supply chain model to respond to uncertainty from reverse logistics. In this study, we develop a deterministic mixed-integer optimization model and robust counterparts to cope with the uncertainty of recycled products and customer demand in the fashion industry. We show that a robust counterpart with a budget of uncertainty is equivalent to a robust counterpart with a box uncertainty under special conditions. To avoid the conservatism of a robust solution, an alternative optimization problem is developed to take advantage of the budget of uncertainty. To verify the performance of the proposed model, numerical experiments are conducted. The simulation results show the proposed model responds robustly to uncertainty and is superior to a deterministic model and other robust counterparts. [ABSTRACT FROM AUTHOR]

In recent years, factors such as lack of valuable resources, economic importance, environmental concerns and increased customers' awareness caused the researchers to consider the design of a reverse logistics network. In this study, the process of collecting and remanufacturing polyethylene terephthalate bottles was considered. A mixed-integer linear programming model for a reverse logistics network was designed. A real case study of polyethylene terephthalate bottles was implemented in one of the northern cities of Iran to show the applicability of the model. The objective function was to minimize the total costs. In the current network model, new collection centers and remanufacturing centers can be opened. Also, the optimal number and location of the facilities along with the flow between them were determined. The obtained results clearly demonstrated that the proposed model is efficient and applicable. Moreover, this paper provided effective and reliable managerial implication solutions for decision makers of polyethylene terephthalate bottle reverse logistics network. Two meta-heuristic algorithms, namely the genetic algorithm and imperialist competitive algorithm, were applied to solve large-scale problems. The efficiency of the two proposed algorithms and the optimum solution of the LINGO software were compared in terms of the CPU time and objective function value. To achieve reliable results from these algorithms, parameter setting was utilized by the Taguchi method. [ABSTRACT FROM AUTHOR]

Growing environmental concerns and potential economic profitability have driven many manufacturers to manipulate reverse logistics (RL). Due to complexity of RL operations and the lack of available resource, outsourcing RL practices to third party reverse logistics provider (3PRLP) is preferred as a strategy. One of the most essential and risky processes for carrying out RL outsourcing is the selection of the optimal 3PRLP from alternatives. The 3PRLP selection is generally recognized as a hybrid-information multi-criteria decision making (HI-MCDM) problem incorporating multiple criteria which are usually in conflict with another criterion and expressed by various formats of information, i.e., crisp numbers, intervals, linguistic terms, and fuzzy numbers, for best retention of original assessment in fuzzy environment. The psychological behavior of decision maker (DM) in selection under environmental pressure has been proved to weigh heavily with decision solution, yet not been properly considered in existing literature. In response to this issue, the main evaluation criteria are investigated in this paper and an integrated cumulative prospect theory (CPT) based HI-MCDM approach is developed to appraise and identify sustainable 3PRLPs. The suggested approach is illustrated by a case study from computer manufacturing industry. Lastly, comparison with FTOPSIS and a sensitivity analysis are performed to confirm the validity and robustness. The results indicate that considering psychological factor in decision making contributes to avoiding potential loss risks. This study will offer informative insights to managers for outsourcing to a capable 3PRLP. [ABSTRACT FROM AUTHOR]

Due to rigorous environmental legislations and competitive economics worldwide, a growing number of companies are devoted to recovering and remanufacturing used products. Consequently, over the past few decades, the management of manufacturing/remanufacturing systems has been receiving increasing attention from researchers and companies leaders. Most of the existing research papers in the literature considered that remanufactured products have the same quality and price as new ones. However, in practice, the market perceives new items as higher quality products rather than remanufactured items. This paper aims to bridge the gap in research on manufacturing/remanufacturing supply chain, by investigating an optimal storage and manufacturing/remanufacturing planning, while taking into consideration the difference between new and remanufactured items, random machine failures, carbon constraints and distinct random customer demands for both items types. Furthermore, to make our system more realistic, it is assumed that the return rate of used items depends on the sales in the past periods, machine repair time is stochastic and set-up time period is not negligible. In this study, two models are developed, considering carbon emissions or not, to determine the optimal values of the manufacturing/remanufacturing period lengths and serviceable stock capacities of new and remanufactured items. Numerical results are provided to illustrate the impact of set-up cost, percentage of returned used items, machine availability, carbon cap and carbon trading price on the optimal storage and production planning. Moreover, the influences of carbon cap, carbon trading price and percentage of returned used items on carbon emissions have been analyzed. The results reveal that set-up cost, percentage of returned used items and machine availability have significant impact on storage and production planning of new and remanufactured items. In addition, the results indicate that a lower carbon cap and/or a high carbon trading price, induce the producer to collect and remanufacture used items and curb carbon emissions. [ABSTRACT FROM AUTHOR]

This study examines reverse supply chains in the electronics industry. The analysis characterizes the flow of resources among firms in a reverse supply chain in the Norwegian electronics industry. The study subsequently examines influences of governance mechanisms and culture on the social, ecological, and economic performance in the supply chain. Based on principal-agency theory, the authors implicate collaboration, monitoring, and specific assets as determinants of the interfirm culture operating in the reverse supply chain. The interfirm culture and collaboration serve as antecedents to triple bottom line performance. Data collected with Norwegian electronics collectors indicate that collaboration and interfirm culture influence ecological, economic, and relational components of sustainable performance. [ABSTRACT FROM AUTHOR]

This research aims to propose a forecasting model to a tire closed-loop supply chain, highlighting the relationship between the number of tires inserted in the market and the number of tires routed to the destination. The methodological approach applied in this research is the Transfer Function Model. We illustrate the application of the model in a state located in the Midwest of Brazil. For this purpose, the number of tires placed on the market for after-market and the size of the current fleet of these places, representing the amount of tires entered the market for new cars sold were adopted as model input variables. We considered the volume of recycled tires collected and sent for disposal as the output variable. Therefore, this study enabled us to identify the variables that influence the return of scrap tires, the amount of returned volume tires, and the time of this return to facilitate the management of the tires of the closed-loop supply chain [ABSTRACT FROM AUTHOR]

The purpose of this article is to identify opportunities to recover value from waste in the process industry. Reverse logistics deals with value recovery in industrial processes. The main reverse channels are reuse, remanufacturing, and recycling parts and materials. The motivation of the study is to find which processes in the process industry offer better opportunities to recover value, which would justify further research. The hypotheses are that supply, manufacturing, maintenance, distribution, and post-consumption processes offer opportunities to reuse, remanufacturing, and recycling used materials and parts. The research method is the multiple case studies in three companies in the process industry: beverages, packaging, and construction chemicals. The main research techniques were document analysis, meeting with experts and guided visits, and non-participant observation. The study concluded that the combination of channels and processes with higher potential for value recovery are reuse in manufacture and distribution, remanufacturing in maintenance, and recycling in postconsumption. The supply process has little potential for value recovery in the studied cases. Another finding is the relevance of the role played by cooperatives and municipalities in the recycling channel. [ABSTRACT FROM AUTHOR]

The emergence of stricter environmental regulations and the growing environmental consciousness of customers have forced industries to start thinking about environmental operations management with the help of reverse logistics application. In this process, influential factors such as drivers and barriers have to be examined, and stakeholders' different perspectives on RL implementation and development should also be considered. This paper presents a multi-perspective framework for reverse logistics implementation using the lens of stakeholder theory. The multiple stakeholders' perspective framework was developed based upon a structured literature review process. Fifty-four papers concerning these topical areas were thoroughly assessed and classified according to their structural dimensions and analytical categories. Two extensive lists of 37 drivers and 36 barriers, categorized and analyzed against the dimensions and categories, served as a basis for the development of the referred framework. Thereby, the overall contribution of this work proposes an understanding of the factors required for employing reverse logistics from multiple perspectives, including those of the company, society, government, and customer. Additionally, each perspective is discussed separately with the aid of previous works developed in the field. Most of the encountered barriers are placed in the firm's perspective; however, these barriers may be an effect from outside impediments. On the drivers' side, the factors must be acknowledged so managers can prepare for changes by exploring these positive influential factors. A consideration of the influential factors from multiple perspectives is critical for creating a comprehensive industry strategy to successfully implement product return. [ABSTRACT FROM AUTHOR]

The degradation of the environment, caused in part by end of life and end of used products, necessitates the set-up of recovery networks. These networks may be owned by the manufacturer or they can be outsourced to third parties. Most manufacturers prefer outsourcing, so this study proposes a benchmarked recovery process for third party reverse logistics providers (3PRLP) by evaluating design criteria, implementation criteria, process control characteristics, and business orientation policies. Expertise efficiency of third party providers dictates their competitiveness and/or survival. In an effort to help third parties enhance value recovery from the process in the market, this paper seeks to establish a meaningful benchmark that will dictate best practices through quality function deployment (QFD). In particular, the paper offers a theoretical background to measure the relative importance among the various types of criteria. The proposed technique also helps to establish guidelines by which to prioritize the various characteristics. This study finds that the main driving factor regarding waste management centers on mandatory laws. It also concludes that when government relaxes its policies, environmentally oriented businesses are able to strengthen their systems. [ABSTRACT FROM AUTHOR]

Strict environmental regulations and diminishing raw material resources have strengthened the importance of reverse logistics at an increasing rate. However a substantial amount of risk is involved in the reverse supply chain which has to be managed by organisations effectively. The risks associated with reverse logistics have however not been addressed appropriately. In response to this knowledge gap, this study aims to prioritize the risks in reverse logistics Risk prioritisation is a multi-criteria decision making (MCDM) problem. In this work, risks involved in reverse logistics are prioritised using hybrid multi-criteria decision making methods. A case of plastic recycling firm is discussed for the illustration of the approach. The major contribution of this work lies in the development of linkages among the various functions in reverse logistics. The results indicate that managing inventory has a significant impact on reverse logistics. It was observed that social concern with respect to protecting the environment in general is based on the cooperation of customers. The findings of the study will provide useful insight to the supply chain managers and researchers for decision-making in reverse logistics. [ABSTRACT FROM AUTHOR]