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The customer order decoupling point (CODP) is the point in the supply chain where the product is linked to a customer order and is, by definition, the last stock point along the supply chain. The CODP decouples the upstream operations that are made to stock from the downstream operations that are triggered by customer orders. We employed a systematic literature review of the empirical research on the CODP in operations and supply chain management (OSCM). We identified 40 articles that explicitly contributed with empirical results concerning factors and characteristics for the operations upstream versus downstream of the CODP, or between make-to-stock (MTS) and make-to-order (MTO) operations. The 32 factors that were identified were grouped into four main categories: market and product factors, operations factors, supply chain factors, and performance measures. Based on the content analysis, we propose a framework that provides a holistic view on the CODP. The distinctive differences between MTS and MTO characteristics strongly suggest that there are two configurations: one for the upstream MTS-type operations and another for the downstream MTO-type operations. We discuss implications for research and practice and provide suggestions for further research. [ABSTRACT FROM AUTHOR]

The extensive use of external thermal insulation composite systems (ETICS) using expanded polystyrene (EPS) for building insulation in Germany has resulted in accumulating end-of-life EPS-ETICS. To address limited waste management options and enhance EPS circularity, alternative recycling options like pyrolysis or solvent-based recycling need to be implemented. However, efficient recycling requires ex-ante analyses of the corresponding reverse logistics networks, including all necessary pre-treatment and transport processes. This study aims to develop a decision support system to determine optimal EPS-ETICS waste management by minimising the net present value of the corresponding network design. Our mixed-integer linear optimisation model considers decisions on technology, capacity, and location for pre-processing and recycling facilities as well as on material flow allocation. Applied to a German case study, our model finds pyrolysis and solvent-based recycling economically superior to current waste treatment in waste incineration plants. We present an optimal network design combining central pyrolysis with decentral pre-processing. A scenario analysis shows fluctuating styrene and polystyrene prices might favour solvent-based recycling over the optimal choice in pyrolysis, with minor overall cost differences. Further, legal recycling quotas of at least 40% would be necessary to promote solvent-based recycling and enhance EPS circularity beyond what is achievable through pyrolysis. [ABSTRACT FROM AUTHOR]

Cloud Manufacturing (CMfg) is a promising approach that leverages the sharing economy to reduce costs and enhance supply chain flexibility. Particularly, when utilised alongside Additive Manufacturing (AM), CMfg is considered a key enabler for collaborative production (CP) systems. However, there is still a lack of planning models that reduce entry barriers for CP. Therefore, we propose a decentralised CP planning framework for AM. In our approach, machines autonomously select jobs from an existing production plan to forward them to other suppliers that can produce these parts more efficiently. A CMfg platform facilitates job forwarding and creates promising part bundles and manufacturing machines autonomously places bids on the packages via a combinatorial $ 2^{nd} $ 2 nd price reverse auction. Costs of the reallocated bundles are shared throughout a Shapley value-based approach without the need to disclose critical information. We benchmark our proposed framework against a centralised planning approach and find that it achieves comparable effectiveness as the benchmark solution. We also show that this mechanism promotes individual rationality and that agents particularly benefit when participating in both offering and acquiring production jobs through the auction. [ABSTRACT FROM AUTHOR]

Global trade is plagued by slow and inefficient manual processes associated with physical documents. Firms are constantly looking for new ways to improve transparency and increase the resilience of their supply chains. This can be solved by the digitalisation of supply chains and the automation of document- and information-sharing processes. Blockchain is touted as a solution to these issues due to its unique combination of features, such as immutability, decentralisation and transparency. A lack of business cases that quantify the costs and benefits causes uncertainty regarding the truth of these claims. This paper explores how the costs and benefits of a blockchain-based solution for digitalising and automating documentation flows in cross-border supply chains compare to a conventional centralised relational database solution. The research described in this paper uses primary data collected through semi-structured interviews with industry experts, as well as secondary data from literature. Two models based on existing services were developed and the costs and benefits compared and then analysed using the Architecture Trade-off Analysis Method (ATAM) and the Analytic Network Process (ANP). Findings from the analysis show that a consortium blockchain solution like TradeLens is the favourable solution for digitalising and automating information flows in cross-border supply chains. [ABSTRACT FROM AUTHOR]

In this paper, a three-echelon supply chain problem under demand uncertainty is considered. The problem is formulated as a multiperiod two-stage stochastic optimisation model. The first stage, consisting of production and replenishment decisions, is integrated with the second stage, which comprises reactive fulfillment decisions, allowing seamless determination as demands are revealed over time. The demand in each period is characterised by an uncertainty set based on the nominal value and demand bounds. We propose a target-based robust optimisation (TRO) approach to determine the most robust planning with respect to a pre-specified cost target. The proposed TRO approach can trade off the total cost (performance) and model feasibility in the presence of demand perturbation (robustness) by fine-tuning the cost target. The robust counterpart is converted to a quadratically constrained linear programming (QCLP) problem, which can be solved by commercial solvers. Numerical experiments demonstrate that the TRO approach can outperform traditional robust optimisation methods in terms of both cost and feasibility against demand uncertainty by enabling precise adjustment of the cost target. Importantly, the TRO approach provides a flexible means to strike a balance between performance and robustness metrics, making it a valuable tool for supply chain planning under uncertain conditions. [ABSTRACT FROM AUTHOR]

This study deals with a closed-loop supply chain where inventory levels are controlled by an order-up-to inventory policy. The system under consideration is the cylinder-packaged gas supply chain of Air Liquide company, where empty cylinders used by customers are returned to be filled again by company plants. First, we examine the goodness of fit for demand distributions based on company real data. This enables us to better characterise demands pertaining to different classes of products. Then, we formulate the multi-echelon serial inventory model to be optimised and propose a heuristic to compute the target inventory levels that helps in achieving the desired customer service level while minimising the total inventory cost. The proposed heuristic is easy to implement in the field and gives results close those obtained using a simulation-optimisation approach that is more time-consuming. Finally, we perform a numerical analysis based on company real data and compare several methods that can be used to compute the target inventory levels by varying mainly two assumptions: parameters regarding demand distributions and metrics used to assess customer service levels. [ABSTRACT FROM AUTHOR]

The Indian subcontinent is highly susceptible to natural disasters. To abate the effect of the disasters, the government emanates institutional mechanisms and strategies for disaster preparedness, mitigation and response. Although there is well-established institutional framework in India for disaster management, there is no study that proposes a disaster supply chain structure under the institutional framework and integrates information and digital technologies (IDT) of industry 4.0 within it. The present study overcomes this research gap. It introduces an IDT structure within the institutional framework of India for multi-agency information sharing, coordination and decision making. It formulates a mathematical model and analyses the impact of IDT on the total response time through three scenarios. The results of scenario analysis reveal the significance of IDT on the disaster supply chains and its capability to handle information delays and IDT failure. The present study can be adopted by disaster management institutions to construct and implement better response practices at the operational, planning and strategic levels. Furthermore, the proposed model in the study can be used for vaccination planning, which includes vaccine distribution, monitoring, regulation and effective implmentation as a response against the current pandemic situation caused due to SARS-CoV-2. [ABSTRACT FROM AUTHOR]

International trade, through global supply chains, is central to global sustainable production and consumption. Redistribution of environmental resources impacts through international trade has become apparent in ecological research – and may have long-term design and planning implications for production and supply chain management. However, current trade and production accounting methods are still incapable of providing accurate and reliable results for policymakers and organisational decision makers to manage global and supply chain trade issues. In this study, a blockchain-based conceptual framework for embodied environmental resources accounting in trade is proposed to address global supply chain and trade issues. Framework design, benefits, and challenges are also discussed. Future research and linkage to theory are also provided. This study provides a strong systemic foundation for managing environmental resources at the nexus of international trade, sustainable production, and global supply chains. [ABSTRACT FROM AUTHOR]

In this paper, we are interested in modelling and solving a flow and resource planning problem related to the trade-in, treatment and resale of pre-owned consumer electronic products. This problem is motivated and inspired by the flows and the processes of the company Recommerce Group, which mainly handles traded-in used smartphones in Europe, but also used tablets, smartwatches, game consoles, laptops, etc. Collected products must be directed to refurbishment centres. After having been recorded, cleaned, tested and reset, they may be refurbished, or remanufactured by a subcontractor. They may also remain in their initial state. Finally, they are sold on diversified channels. This problem can be generalised to other refurbishment and remanufacturing activities of used consumer electronic products. We first formulate the problem as a mixed-integer linear program and show its NP-hardness. In order to solve large size real-life instances, mixed-integer programming based heuristic approaches are proposed. Extensive computational experiments on realistic instances are conducted to show the advantages and the limits of the proposed approaches. Several managerial insights are investigated and analysed. [ABSTRACT FROM AUTHOR]

The price of oil is highly complex to predict as it is impacted by global demand and supply, geopolitical events, and market sentiment. The accuracy of such predictions, however, has far-reaching implications for supply chain performance, portfolio management, and expected stock market returns. This paper contributes to the oil price prediction literature by evaluating the predictive impact of the US President's communication on Twitter, while benchmarking various Natural Language Processing (NLP) techniques, including Term Frequency-Inverse Document Frequency (TF-IDF), Word2Vec, Doc2Vec, Global Vectors for Word Representation (GloVe), and Bidirectional Encoder Representations from Transformers (BERT). These techniques are combined with a deep neural network Long Short-Term Memory (LSTM) architecture using a five-day lag for both the oil price and the textual Twitter data. The data was collected during the term of US President Donald Trump, resulting in 1449 days of crude oil price prediction and a total of 16,457 tweets. The study is validated for Brent and West Texas Intermediate blends, using the daily price of a barrel of crude oil as the target variable. The results confirm that including the US President's tweets significantly increases the predictive power of oil price prediction models, and that an LSTM architecture with BERT as NLP technique has the best performance. [ABSTRACT FROM AUTHOR]

Configuring supply chains (SCs) is critical to spare parts retailers' success, entailing two key aspects: stock deployment into distribution centres (DCs) (i.e. inventory centralisation or decentralisation) and stock supply in each DC (how many spare parts to supply and how often). Given the unpredictability of spare parts demand, stock deployment and supply policies should be regularly reviewed, adapting to fluctuations in customer needs. A viable way to do this is to adopt a multi-criteria ABC criticality classification. However, the multi-criteria ABC criticality classification has often been used to plan stock supply policies in a single DC, but only once to plan spare parts deployment. Nevertheless, the available literature methodology presents major limitations, being not applicable in real companies. Therefore, this paper provides a novel methodology, called SP-LACE, which first reviews the configuration of spare parts SCs based on a multi-criteria criticality classification. Then, allows, for the first time, to evaluate the economic benefits of the reviewed SC configuration. SP-LACE was tested on two case studies and compared with the literature methodology. The results indicate that it provides economic benefits (in terms of total SC cost), overcoming the limitations of the literature methodology and ensuring high service levels. [ABSTRACT FROM AUTHOR]

The effective operations of closed-loop supply chains (CLSCs) can help companies achieve sustainability goals and boost economic performance. In practice, CLSCs must collect used products, a complex process that is often constrained by collection station capacity. However, how collection station capacity influences the bullwhip effect and the dynamic performance of CLSCs remains unclear. Here, we develop a system dynamics model for CLSCs that integrates traditional manufacturing with remanufacturing and explore the effects of the stochastic capacity constraint of the collection station on the bullwhip effect of CLSCs. We find that, generally speaking, a collection station with looser or more stable capacity constraints tends to reduce bullwhip of CLSCs. However, pertinent interactions emerge between the relevant parameters; in some situations, reducing the capacity level of a collection station may be reasonable and beneficial when the stochastic capacity constraint is very stable, or when customer demand is highly variable. We also consider the partial backlog in return collection, a phenomenon associated with the stochastic capacity constraint of a collection station, and identify a new trade-off between CLSC sustainability and economic performance. Ultimately, our findings provide evidence that will guide managers' plans for the capacity management of return collection in CLSCs. [ABSTRACT FROM AUTHOR]

This paper proposes a prediction-based product change recovery strategy for the SC (supply chain) under long-term disruptions. A real-world case composed of multi-period planning and dynamic customer demand is considered. First, to forecast dynamic customer demand, a data-based demand predictive method with feedback errors is designed. Second, to schedule procurement and production in advance, based on the predicted demand, the selection of the supply portfolio is transformed into a bi-objective mixed integer programming problem incorporating product change. Furthermore, goods allocation and customer order fulfillment strategy is also designed to finish the transportation of goods and delivery of customer orders. To systematically synthesise and address the problems aforementioned, a three-stage heuristic method is further developed. Finally, a case study is presented to substantiate the reliability of the proposed strategy via an actual SC model of Dongsheng Electronics Co., Ltd. Based on the results obtained after one month, the proposed disruption recovery strategy can reduce the unit product cost and improve the service level, which outperforms the original method adopted by Dongsheng. Additionally, sensitivity analysis of unit product change cost is conducted to reveal the effect of different unit product change costs on SC performance. [ABSTRACT FROM AUTHOR]

Motivated by the industrial observation of the increasing application of blockchain in the supply chain and its improvement in terms of consumer demand, this study examines the impact of investment decisions of blockchain data acquisition nodes upstream and downstream of the supply chain on firms' product recycling and pricing, market demand, and profits. The influences of different pricing leadership (i.e. supplier-led vs. retailer-led) in a supply chain are also thoroughly investigated. First, the presence of a strong retailer dramatically reduces suppliers' incentive to invest in blockchain. However, the supplier is still likely to invest more in a retailer-led supply chain than that in a supply chain led by itself under certain conditions; that is, the cost of blockchain is relatively small, or consumers' sensitivity to blockchain or product recycling benefits is rather large. Second, the total number of blockchain data acquisition nodes, market demand, and supply chain profit in a retailer-led supply chain are higher than in a supplier-led supply chain. Finally, interestingly, the supplier will be better off in a retailer-led supply chain when the return effect of product recycling is relatively high, while the cost-effectiveness of blockchain investment is relatively low. [ABSTRACT FROM AUTHOR]

The pharmaceutical supply chain (PSC) is a highly important strategic issue in the healthcare domain because of its significant effect on human wellbeing and healthcare costs. This paper provides a mathematical optimization model to design a PSC by considering the drug's corruption. Given the importance of the sustainable development goals, three objectives are considered: economic, social, and environmental. The cost of fixed installation, transportation, holding, collection, distribution, recycling and disposal is reduced by the economic objective. A reduction in greenhouse gas emissions, water use, and nonrenewable energy consumption is achieved by the environmental objective. Based on the social objective, the number of employment opportunities, economic growth, job satisfaction, and national self-sufficiency are all increased, while the number of days lost due to work-related accidents decreases. To achieve the weight of elements in environmental and social objectives, the fuzzy best–worst method is used. Due to the inherent uncertainty in the PSC, its main parameters are referred to as unpredictable, which calls for a robust optimization approach to eliminate the model parameters' uncertainty. A fuzzy programming approach is used to solve the developed model. Numerical evidence drawn from a practical case shows that the suggested model is efficacious and valid. We suggest that the priorities and challenges of sustainable growth contribute to the determination of the PSC's managerial and operational characteristics. [ABSTRACT FROM AUTHOR]

Reverse logistics network design is a complex decision-making problem that involves the reuse, repair, remanufacturing, and recycling of end-of-life (EOL) under the tradeoff among conflicting objectives. The cutting-edge technologies in Industry 4.0 are now leading to an unprecedented and dynamic transformation of reverse logistics systems, which, however, further complicates the initial network design. In this paper, a two-level decision-support framework combined with both optimization and dynamic simulation is proposed to balance the cost, environmental impact, and service level in smart and sustainable reverse logistics network design under a dynamically evolving and stochastic environment. The results of a real-world case study in Norway show that the method can better support robust strategic decisions, eliminate dominated/near-dominated solutions, and yield holistic performance analyses considering smart reverse logistics transformation. The proposed two-level decision-support framework can better analyze the impact of the technology transformation of Industry 4.0 on reverse logistics systems, while it also provides a fundamental structure for digital reverse logistics twin. [ABSTRACT FROM AUTHOR]

Contemporary business models need to re-imagine the production and distribution of goods and services embedding social, economic, and environmental goals concurrently. To this end, reverse logistics in streamlining a circular economy (take, make, use, reuse, repair, and recycle) catapulted to the top of the discussion for collecting and distributing products. Yet, little is empirically known about the role of reverse logistics in the circular economy. This study attempts to fill this knowledge gap in theory and practice through a multiple case study approach including 40 semi-structured interviews with reverse logistics specialists from the four largest retailing firms in the United Arab Emirates (UAE). Findings reveal multiple ways by which reverse logistics contributes to a circular economy: for instance, reverse logistics enables firms to develop a circular product design; the combination of reverse flow with the forward flow consolidates the high volume of products, thus mitigating waste; use of innovative tools (robots, autonomous bikes) in reverse logistics increases the used products' return rate and thereby enhancing recycling; technological advances (e.g. big data and IoT) in reverse logistics help trace the product thus reducing waste. The paper offers several valuable insights for practitioners to build a circular economy via reverse logistics (waste reduction, responsible consumption, and sustainable logistics). Our study also contributes to multiple United Nations Sustainable Development Goals (SDG 11, SDG 12, and SDG 13). [ABSTRACT FROM AUTHOR]

This paper considers an e‐tailing supply chain for fresh produce (E‐FSC) composed of a supplier investing in freshness‐keeping effort and an e‐retailer providing value‐added service. We study the e‐retailer's information sharing strategy with supplier encroachment. First, we discuss the supplier's encroachment strategy without or with information sharing and indicate that the e‐retailer may profit more from encroachment. Second, we explore the e‐retailer's information sharing strategy under two scenarios. Under the independent scenario, the e‐retailer may share information when the freshness sensitivity is comparatively high, which cannot affect the supplier's encroachment strategy. Under the interactive scenario, the e‐retailer influences the supplier's encroachment strategy through an information sharing strategy. The e‐retailer may share (withhold) information to induce (deter) encroachment when the competition intensity is comparatively low or high (moderate). Finally, we discuss the influence of the entry cost on E‐FSC members' profits, which finds that increasing entry cost may improve the supplier's profit. [ABSTRACT FROM AUTHOR]

This research paper aims to investigate the interdependent influences of barriers to implementing reverse logistics in the broad spectrum of processing activities in the conditions of an emerging economy. An effort was made to approach these barriers (i.e., organizational and management barriers, technical and technological barriers, and economic, financial, and market barriers) based on the relevant literature, predominant attitudes, and experts' opinions, thus contributing to the body of knowledge in this domain. Determining the intensity of interdependent influences and the importance of barriers for implementing reverse logistics was performed to determine the most important (key) barriers that can be practically applied as guidelines for decision making. The Fuzzy DEMATEL method was used to determine the intensity of these influences on a sample of manufacturing companies in the Republic of Serbia. The results indicate that the most critical barriers to the successful implementation of reverse logistics are a lack of management support and cooperation with scientific institutions and professional associations to acquire knowledge and follow trends in the field. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has increased medical assistance and service demand, necessitating the development of a comprehensive model for managing medical waste networks. Despite extensive research, there is a lack of models examining infectious and hazardous waste simultaneously. This paper presents a multi-layered bi-objective mixed-integer linear program model, dividing infectious and non-infectious waste into different categories. The model consists of several stages for safe recycling of medical waste. Fuzzy programming and an augmented-constraint approach are employed to tackle uncertainty in parameters. A real case study from Tehran is examined, and numerical and computational results are provided to prove the model's efficiency. The results indicate that insufficient disposal centers may require increasing their capacity. [ABSTRACT FROM AUTHOR]

Purpose: The uptake of reprocessed construction materials (RCMs) derived from demolition waste (DW) is limited, which questions the long-term sustainability of DW reverse logistics (RL). To address this gap, the current study focused on identifying informational and structural interventions to promote the uptake of RCMs among Australian construction professionals (CPs). Design/methodology/approach: Following a qualitative research approach with thirty-one semi-structured interviews, the study explored potential interventions that can drive broader RCM usage. The study's strength lies in the in-depth qualitative insights gathered through extensive interviews with CPs experienced in using RCMs. Findings: Sixteen informational and structural interventions to promote the uptake of RCMs were identified and mapped against the industry levels at which they should be implemented. RCM suppliers should focus on improving material quality, supply and marketing while minimising material costs. Governments should encourage using RCMs through incentivisation, supportive legislation and approval processes. The significance of awareness building and research was also recognised, which requires the collective efforts of suppliers, governmental and non-governmental bodies and educational institutes. Originality/value: Despite the talk around sustainable consumption, the actual walk towards this is limited from a construction perspective, as seen through the low uptake of RCMs. This study attempts to bridge this mismatch by outlining informational and structural interventions that would drive CPs to walk the talk and use RCMs for construction applications. While most studies on DW RL have focused on improving waste recovery processes, this study takes a less-trodden path and explores the potential for developing markets for RCMs. [ABSTRACT FROM AUTHOR]

Supply chain management and distribution network design has attracted the attention of many researchers in recent years. The timely satisfaction of customer demands leads to reducing costs, improving service levels, and increasing customer satisfaction. For this purpose, in this research, the mathematical programming models for a two-level distribution network including central warehouses, regional warehouses, and customers are designed so that several products with definite demands in multiple periods are distributed from central warehouses to customers. In this problem, two objective functions are considered. The first objective function seeks to minimize the costs of establishment, transportation, inventory, and shortage, and the second objective function attempts to maximize the satisfaction level corresponding with the supply rate of different goods for numerous customers. The presented models include the basic model, inventory-based model, multi-period inventory-based model, and multi-period inventory-based reverse logistics model. The validation and applicability of the proposed models were demonstrated by implementation in a real case study of the automobile industry. The LINGO software 20.0 was used to solve the models. The results show that incorporating the inventory management policies into the basic model and converting from a single-period to a multi-period reverse logistics model will significantly increase company profitability and customer satisfaction. [ABSTRACT FROM AUTHOR]

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Purpose: Neo-institutional theories and their constructs have so far only received limited attention in supply chain management literature. As recent supply chain disruptions and their ripple effects affect actors on a broader institutional level, supply chains are confronted with multiple new and emerging, often conflicting, institutional demands. This study aims to unpack the notion of institutional complexity behind supply chain disruptions and present a novel institutional framework to lower supply chain susceptibility and increase supply chain resilience. Design/methodology/approach: The authors identify the patterns of complexity that shape the supply chain susceptibility, namely, distance, diversity and ambiguity, and present three institutional responses to susceptibility to increase supply chain resilience, namely, institutional entrepreneurship, institutional alignment and institutional layering. Findings: This paper analyses the current situational relevance to better understand the various and patterned ways how logics influence both supply chain susceptibility and the supply chain resilience. The authors derive six propositions on how complexity can be reduced for supply chain susceptibility and can be increased for supply chain resilience. Originality/value: By expanding and extending research on institutional complexity to supply chains, the authors broaden how researchers in supply chain management view supply chain susceptibility, thereby providing managers with theory to think differently about supply chains and its resilience. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior. Design/methodology/approach: Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors. Findings: The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory. Originality/value: The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds. [ABSTRACT FROM AUTHOR]

This article analyzes Reverse Logistics (RL) practices associated with the concept of Circular Economy (CE), comparing studies conducted before and after the implementation of the National Solid Waste Policy (NSWP) in Brazil. Data from companies in the Sul Fluminense region were analyzed using the Analytic Hierarchy Process to prioritize RL practices and identify those related to CE. The research included companies from nine Brazilian economic sectors that engage in some form of RL. The comparison of results aimed to evaluate the influence of the NSWP on these practices, with data analyzed using the Super Decisions software (version 3.2) to establish priorities and aggregate them using the Aggregating Individual Priorities method. It was observed that the implementation of the NSWP in 2010 emphasized the importance of sustainability. Although the concept of CE is recent, its operationalization is based on consolidated RL practices such as recycling, remanufacturing, and material reuse. The study provides insights to optimize and expand these practices, facilitating the transition from a linear economy to a circular one. [ABSTRACT FROM AUTHOR]

In an era where sustainability and efficient resource utilization are paramount, the closed-loop supply chain (CLSC) emerges as a critical approach, particularly in the context of perishable goods. The perishability of products adds a layer of complexity to supply chain management, necessitating innovative strategies for maximizing product life and minimizing waste. This comprehensive review article delves into the integration of perishable products within the framework of CLSC. The study thoroughly examines existing research to identify gaps and outline future research directions. It emphasizes the unique challenges and complexities of managing perishable goods, a crucial but often overlooked component in sustainable supply chain practices. The review highlights the balance between efficiency and sustainability, underscoring the importance of reverse logistics and circular economy principles in enhancing supply chain resilience. By synthesizing various methodologies and findings, the article presents a holistic view of the current state of perishable product management in CLSCs, offering valuable insights for academia and industry practitioners. The study not only contributes to the theoretical understanding of CLSCs, but also proposes practical approaches for their optimization, aligning with broader sustainability goals. [ABSTRACT FROM AUTHOR]

To effectively solve the reverse logistics distribution problem caused by the increasing number of scrapped parts in the automotive market, this study constructs a multi-trip green vehicle routing problem model with time windows by comprehensively considering the coordination between carbon dioxide emissions and cost efficiency. A hybrid adaptive genetic algorithm is proposed to solve this problem, featuring innovative improvements in the nearest neighbor rule based on minimum cost, adaptive strategies, bin packing algorithm based on the transfer-of-state equation, and large-scale neighborhood search. Additionally, to efficiently obtain location data for supplier factory sites in the distribution network, a coordinate extraction method based on image recognition technology is proposed. Finally, the scientific validity of this study is verified based on the actual case data, and the robust optimization ability of the algorithm is verified by numerical calculations of different examples. This research not only enriches the study of green vehicle routing problems but also provides valuable insights for the industry to achieve cost reduction, efficiency enhancement, and sustainable development in reverse logistics. [ABSTRACT FROM AUTHOR]

This paper explores a dual-channel supply chain within an uncertain environment where a manufacturer produces a green product and a retailer makes sales efforts to attract a higher customer base. Moreover, we incorporate a reverse supply chain model in which the manufacturer retrieves end-of-used products from customers through a collection initiative. Simultaneously, the retailer gathers end-of-used products from customers by implementing an exchange policy facilitated through a coupon applied to the product’s selling price. Then, we explore centralized, manufacturer Stackelberg, option contracts and cost-sharing contracts strategies to maximize supply chain profits under various circumstances. Subsequently, a numerical example is undertaken to showcase the utility of the models and explore sensitivity that examines how different parameters impact the supply chain’s profit. Findings suggest that the supply chain members will be profitable if they engage in the option contract model under a suitable value of the option price and exercise price. [ABSTRACT FROM AUTHOR]

This paper introduces a novel two-phase framework for designing a proactive–reactive scheduling model in the multi-mode resource-constrained project scheduling problem under disruptions. The proactive phase involves constructing a resilient baseline scheduling model using a mixed-integer linear programming model. This phase contributes to a multi-objective model that minimizes the project completion time and total project cost while maximizing resilience criteria. In this context, resilience refers to allocating float time to project activities to protect their start and finish times against future disruptions as much as possible. The reactive phase involves a bi-objective mathematical model that mitigates the impact of disruptions through preempt-repeat, preempt-resume, and activity-crashing strategies. Real-world projects involve many uncertain parameters that can negatively affect the optimization of rescheduling problems if overlooked. Therefore, for the first time, a scenario-based robust optimization approach is proposed to cope with the uncertainty of the reactive phase. Additionally, a novel hybrid multi-objective method based on goal programming is introduced to solve the proposed multi-objective model. Finally, to demonstrate the capability of the proposed approach, an oil and gas project in Iran is regarded as a real case study. The results indicate that the negative impact of disruptions on the makespan and total cost of the project can be largely mitigated by considering resilience criteria in the proactive phase and preempt-repeat, preempt-resume, and activity-crashing strategies in the reactive phase. [ABSTRACT FROM AUTHOR]

The agriculture supply chain is an integral part of the whole agriculture sector. A top-notch cost efficient supply chain management system that can protect itself from outside security attacks and also from malicious activities by supply chain participants without third party intervention is highly demanded in the agriculture field. In this paper, a smart contract based forward and reverse agriculture supply chain management system is proposed that takes into account both internal and external security attacks. Here, peer-to-peer Certificate Authorities provide the rate of the crops and the farmer puts this in the forward supply chain with its price as well as communicates directly with distributors for making transactions with customers through the smart contracts. After receiving the requested crops from the farmer through the distributor, the customer initiates payment contract for the transaction. On the other hand, if a customer is not satisfied, he or she initiates a reverse supply chain. In order to maintain its level of security, this model applies blockchain technology in conjunction with a session key technique. The system computes cost analysis to ensure the immutability of costs and predict future expenses as well as compared with benchmark data. The Real or Random (RoR) based formal as well as informal security analysis is presented here to demonstrate the system's robustness against a wide range of potential security threats and the malicious behavior of different entities. Our results analysis demonstrates the system evaluation in terms of throughput, latency, transmitted message size among different entities and gas consumption. It is observed that the proposed model outperforms than other existing approaches. [ABSTRACT FROM AUTHOR]

In this paper, we consider the process of resource utilization of tunnel slag, and propose a 'regional self-balanced' reverse logistics network. We propose a location-allocation model that takes the uncertainty of availability, various types of output, various types of demand, and various types of facilities into account when solving the location-allocation problem for facilities in the network. According to our research, we obtain a feasible model and algorithm for use in the engineering field, and we find that the logistics cost can be decreased by appropriately increasing the number of facilities and choosing the locations of facilities based on scientific principles, thereby lowering the total cost. We determined the parameters of the algorithm by Taguchi's analysis and verified the effectiveness of the algorithm by comparing it with the exact algorithm and other heuristic algorithms. By analyzing the impact of the availability of tunnel slag on the site selection of facilities, we obtain policy recommendations on the number of facilities. [ABSTRACT FROM AUTHOR]

E-commerce is a boom in the modern business. E-commerce (electronic commerce) is the activity of electronically buying or selling products on online services or over the Internet. E-commerce is one of the most dynamic and important sectors of the economy as well as one of the main factors leading to greater competitiveness. The development of E-commerce is driven by rapidly expanding Internet access, but also by growing mobility and popularity of portable devices, via which customers order goods and services at a convenient time and place more and more frequently. The strength of a business is determined by how well it can manage to provide its products and services at the right price, time, and quality. In today's fierce competitive world, E-commerce businesses are often up against their peers from different geographical regions. It makes perfect sense for a company to expand its operations geographically, which would allow them the advantages of quickly reaching out to more customers and building good word of mouth for the brand. But, it also give rise to the risks like additional costs associated with logistics, longer delivery time than expected, problems with adjusting the inventory levels to match customer needs at each location, etc. That's why it makes sense to think about Return to Origin (RTO) before calculating revenue and profits. So, this paper is on impact of RTO on E-commerce business and it also discussed preliminary findings of research undertaken with the Indian ecommerce company. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper introduces an evaluated initial model for how product lifecycles can be extended considering new and emerging existential design aspects concerning both general as well as digital/connected products. The initial model, which is cyclic, includes reverse logistics of components and raw materials, as well as information on how to manage data at the end of lifecycles. The aim is to improve long-term sustainability with a high degree of circularity while also achieving increased profitability and competitiveness. Further, we highlighted that product providers must start to evaluate and prepare for how to improve product durability, manage long and extendable lifespans, and achieve circularity with reverse logistics to close the loops. Additionally, updatability and upgradability are also required to stay current with time and create value while being cybersecure. Otherwise, customers' expectations, various legal and regulatory aspects, as well as other existential design aspects can halt or even terminate a product's lifecycle. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Currently, reverse logistics and sustainability are recognized as strategies to enhance the performance of supply chain processes and customer service and to reduce environmental impact, which is reflected in the planning of and reduction in costs throughout the production process. This article developed a bibliometric review that considered the growth of reverse logistics and sustainability from the perspective of different organizations, authors, thematic subareas, countries, journals, keywords, and volume of citations and publications. For this, a methodology was developed that consisted of reviewing previous research, obtaining the Scopus data set, applying the analysis with Microsoft Excel 365 and VOSviewer version 1.6.18 to determine the applications and trends of future research, and identifying the global impact in the last six years on organizations. The search equation with the application of filters resulted in 22,625 articles. The Sustainability Switzerland journal provided the most significant number of contributions in terms of publications, and the Journal of Cleaner Production stood out for its number of citations. Tseng, M.L. and Govindan, K. were the most active authors. China, the United States, and the United Kingdom were the most notable countries. Chinese Academy of Sciences and the Ministry of Education of the People's Republic of China were the most influential institutions. The main findings were the recognition of the potential research lines and industry 4.0 technologies applied in supply chains and the development of sustainable processes with the fusion of reverse logistics, sustainability, and circular economy. [ABSTRACT FROM AUTHOR]

Problem definition: Recent global crises have caused unprecedented economic uncertainty and intensified retailers' concerns over inventory risks. Mitigating inventory risks and incentivizing retailer orders is critical to managing retail supply chains and restoring their norms after severe impacts. We study the allocation of inventory risk using contracts in a retail supply chain with a risk-neutral manufacturer and a risk-averse retailer. We consider two factors that affect the effectiveness of contracting: (1) asymmetric risk aversion information—retailers' attitudes are typically diverse and unknown to the manufacturer, and (2) uncertain outside opportunity—retailers typically face a volatile external business environment. Methodology/results: With a game-theoretic model that captures the interaction among risk aversion, information asymmetry, and outside opportunity, we derive the contracting equilibrium under two widely adopted risk allocation schemes—push (i.e., the retailer bears the inventory risk) and pull (i.e., the manufacturer bears the inventory risk) contracts. Contrary to the conventional wisdom that pull contracts are more effective in risk mitigation, we show that push contracts may induce larger expected order quantities and achieve the highest supply chain efficiency due to the interaction of asymmetric risk aversion information and risky outside opportunities. We also find that the manufacturer may obtain higher profits with push contracts when both the heterogeneity in the retailer's risk attitude and the risk of the outside opportunity are sufficiently high. In addition, when the risk of the outside opportunity is in a medium range, the push contract allows the manufacturer to fully eliminate the information rent and achieve the supply chain's first-best outcomes. We further evaluate the effects of product profitability and demand uncertainty and generalize the retailer's risk measure to any coherent risk measure. Managerial implications: Our analysis highlights the importance of modeling asymmetric risk aversion information and risky outside opportunities in analyzing supply chain contracting. When considering these practical factors, allocating more inventory risks to a risk-averse retailer may be better than a risk-neutral manufacturer. Our results provide novel insights into the selection of proper contract types for managing inventory risks in retail supply chains. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0624. [ABSTRACT FROM AUTHOR]

To support the 2021 Manufacturing & Service Operations Management (M&SOM) Data-Driven Research Challenge, RiRiShun Logistics (a Haier group subsidiary focusing on logistics service for home appliances) provides MSOM members with logistics operational-level data for data-driven research. This paper provides a detailed description of the data associated with over 14 million orders from 149 clients (the consigners) associated with 4.2 million end consumers (the recipients and end users of the appliances) in China, involving 18,000 stock keeping units operated at 103 warehouses. Researchers are welcomed to develop econometric models, data-driven optimization techniques, analytical models, and algorithm designs by using this data set to address questions suggested by company managers. History: This paper has been accepted as part of the 2021 M&SOM Data-Driven Research Challenge. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72091215/72091210, 71871207, 71991464/71991460, and 71921001]. Supplemental Material: Data and the online appendix are is available at https://doi.org/10.1287/msom.2021.0994. [ABSTRACT FROM AUTHOR]

Despite the recognition that the adoption of the circular economy depends on aligning the new product development process with the principles of circularity, there are still few studies on the barriers to circular product design. This article aims to contribute to this topic by developing an exploratory study to identify and analyze these barriers in the Brazilian context. In addition to a theoretical analysis, the fuzzy analytic hierarchy process was utilized to evaluate the significance of various hindrances and obstacles to circular product design. To gain a better understanding of these barriers, semi‐structured interviews were also conducted. Experts in areas such as sustainability, marketing, and R&D from companies that develop products participated in this research. The results of the study reveal that the difficulties supply chains have in providing circular economy‐based products and reverse logistics systems are among the main barriers. Challenges such as low consumer valorization of these products and a lack of knowledge and technologies were also identified as relevant. By investigating a set of barriers to circular product design, this study extends knowledge about the difficulties companies face in the transition to circular business models. [ABSTRACT FROM AUTHOR]

The shipper lane selection problem (SLSP) is determining which lanes are to be served by the shipper's vehicle fleet or outsourced to the carriers through auction. While the SLSP in previous studies assumes that each lane is associated with a set of discrete times at which it can be served, this study considers a generalized version assuming a lane service time window for each lane, which is named the SLSP with time windows (SLSPTW). The SLSPTW is formulated as a mixed integer linear programming model that minimizes the sum of the transportation and the service/setup costs incurred by the shipper to auction off the lanes served by the carriers. In the proposed two‐stage solution approach, the first stage is designed to generate quickly a set of possible solutions, the best of which is then verified by a decomposed model of the SLSPTW at the second stage. Besides, an iterative‐improvement mechanism for the proposed algorithm is adopted to achieve the efficiency of the solution quality improvement. The effectiveness and efficiency of the developed solution method is demonstrated by the conducted numerical experiments. [ABSTRACT FROM AUTHOR]

In this paper we investigate disposal activities in a reverse logistics models with linear costs structure. The two models have different disposal strategy. The first model analyzes a continuous disposal strategy, i.e. disposal can happen in every time in the planning horizon. This type of models was investigated in earlier works. The second possible disposal strategy assumes that disposal is only at the end of the planning horizon. After characterization of the optimal strategies of the two models we compare the costs and the trajectories of the optimal paths. The result of the paper is that the relevant costs are higher in case of disposal at the end of the planning horizon. It is cost efficient to dispose off the not necessary products inside of the planning horizon. [ABSTRACT FROM AUTHOR]

Extended warranties are widely adopted and accepted in the marketplace by manufacturers and retailers as it helps to enhance the customers' post-sale satisfaction. In closed-loop supply chains, the extended warranty not only generates profit for the manufacturer, but also provides warranty returns of the new products for remanufacturing. In this paper, a two-period model is developed and optimal pricing strategies for the extended warranties are derived. We compare the optimal pricing and retailing strategies of the extended warranties for remanufactured and new products offered by the manufacturer with and without the retailer's own extended warranty while considering the competition between the manufacturer and the retailer for the extended warranty of new products. We find that the introduction of the retailer's extended warranty does not always hurt the manufacturer's profit. Numerical analyses also show that there exists an optimal extended warranty length for the manufacturer that maximises its profit. Moreover, we show that the retailer cannot extract more profit by increasing the length of its own extended warranty. [ABSTRACT FROM AUTHOR]

Consumer behaviour is changing in the e-commerce age for apparel products. More and more consumers tend to bracket, which means they purchase multiple versions of the same product to try at home and return those that do not meet their requirements. This bracketing behaviour can increase the likelihood that consumers buy the good-fit products. However, the tsunami of returns from bracketing has become challenging for online retailers. In this paper, we analytically address this issue by developing profit-maximising models for retailers facing bracketing customers. Our contribution is to explore whether and under what conditions should retailers encourage or discourage the bracketing purchase behaviour. Whether or not bracketing is profitable for retailers depends on the bracketer proportion and retailer's reverse logistics cost. Further, we also find that while the profit is eroded because of the large number of returns, retailers should order more product to meet bracketers' demand. In addition, we generate managerial insights from the findings that help online apparel retailers convert the seemingly harmful consumer returns from bracketing into an advantage. [ABSTRACT FROM AUTHOR]