Sustainable Reverse Logistics Research Articles

Criteria for selecting third-party logistics service providers: Systematic Literature Review

Third-party logistics (3PL) is a strategic business partner for companies in carrying out company business activities that are outsourced or cannot be handled themselves. Mistakes in choosing a 3PL can have negative impacts on the company such as financial losses, reducing service quality, reducing customer trust, reducing the company's image, and so on. This article aims to classify third-party logistics based on current issue trends, the methods used in selecting criteria, and what criteria they produce. Using Systematic Literature Review, researchers reviewed, classified, and analyzed 56 relevant articles published in the 2020-2023 period from the Scopus database. The results of this review reveal that 3PL providers can be classified based on issue trends and company goals in selecting them, namely Traditional 3PL, Sustainable 3PL, Sustainable-resilient 3PL, Green 3PL, Gresilient 3PL, Traditional Third-Party Reverse Logistics, and Sustainable Third-Party Reverse Logistics. The priority criteria in selecting a 3PL provider are closely related to the 3PL classification, the industrial sector and business activity being outsourced, the country where the company operates, and the dimensions or attributes used in developing the criteria.

A two-level decision-support framework for reverse logistics network design considering technology transformation in Industry 4.0: a case study in Norway

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.

Reverse Logistics and Performance of Plastic Bottling Firms in Mombasa County, Kenya

Purpose: The purpose of this study was to determine the relationship between reverse logistics and the performance of plastic bottling firms in Mombasa County, Kenya. Methodology: Cross-sectional research design was employed in the study. The study considered all 27 plastic bottling firms registered by Mombasa County Department of Trade. Stratified random sampling techniques was used to select sample size and Slovin’s formula was adopted to get the sample size for the study. Primary data was collected by use of structured questionnaires. Collected data was analyzed by employing descriptive and inferential statistics as the data analysis techniques. Descriptive statistics gives the profile of the respondents, that is, the frequencies and their percentages; whereas inferential statistics adopts a hierarchical, moderated, multiple regression analysis model in order to determine the effect of the explanatory variable. Statistical Package for Social Science was used as the data analysis tool. Data was presented in frequency and descriptive tables. Findings: The study established that there is a correlation of 0.748 between reverse logistics and performance of plastic bottling firms in Mombasa County. Reverse logistics accounted for 56.0% of the variation in the performance of plastic bottling firms in Mombasa County. Unique Contribution to Theory, Practice and Policy: Systems theory was adopted and validated. By incorporating linking the entire supply chain, Systems theory could assist plastic bottling firms in developing a seamless sustainable reverse logistics. The study revealed that successfully implementing reverse logistics; minimize unnecessary costs, protect the environment and increase firm returns.

An integrated group decision-making framework for assessing S3PRLPs based on MULTIMOORA-WASPAS with q-rung orthopair fuzzy information

Sustainable third-party reverse logistics has gradually risen to prominence as a component of contemporary commercial development as a result of the acceleration of global economic integration and the prominent growth of information technology in the logistics industry. In the procedure of sustainable third-party reverse logistics providers (S3PRLPs) selection, indeterminacy and conflict information bring great challenges to decision experts. In view of the significant superiority of q-rung orthopair fuzzy (q-ROF) set in expressing uncertain and vague assessment information, this essay designs a comprehensive assessment framework through merging the best and worst method (BWM), Multiplicative Multi-objective Optimization by Ratio Analysis with Full Multiplicative Form (MULTIMOORA) and weighted aggregated sum product assessment (WASPAS) method to address the S3PRLPs selection issue with entirely unknown weight information under q-ROF setting. Firstly, we present a novel score function for comparing q-ROF numbers after analyzing the inadequacies of previous works. Secondly, the q-ROF Frank interactive weighted average (q-ROFFIWA) and q-ROF Frank interactive weighted geometric (q-ROFFIWG) operators are advanced based on the constructed operations to take into consideration the interactive impact of information fusion procedure. Thirdly, the q-ROF-MULTIMOORA-WASPAS decision framework is built based on novel score function and the developed operators, in which the synthetic weights of the criterion are determined by the modified BWM and entropy weight method to reflect both the subjectivity of the decision expert and the objectivity of the decision information. Ultimately, an empirical example was used to evaluate S3PRLPs to demonstrate the applicability and feasibility of the developed methodology, and a comparative analysis was conducted with other existing methods to highlight its advantages in dealing with complex decision problems. The discussion from the research indicates that the developed methodology can be used to evaluate S3PRLPs and further improve the quality of logistics services for organizations.

Uncertain remanufacturing reverse logistics network design in industry 5.0: Opportunities and challenges of digitalization

Remanufacturing, a crucial step of reverse logistics, focuses on restoring or enhancing the functionality of waste products. The challenge in planning an effective remanufacturing reverse logistics system lies in the uncertainties from various sources. In addition, the evolving industrial landscape in Industry 5.0 necessitates adaptability to technological advancements. This paper proposes an integrated and digitalized architecture for uncertain reverse logistics network design. A fuzzy optimization model is first formulated to identify potential network configurations under varying demand-satisfying and capacity constraints. These solutions are automatically converted and assessed in a dynamic simulation environment with practical operational logic under a set of real-world scenarios. Numerical experiments are performed to validate the method and show the advantages of integrating optimization with dynamic simulation on a digital platform for strategic network planning. The results, built upon previous research, indicate that while initial investments in technology might be substantial, they may lead to long-term reductions in both costs and emissions. Moreover, collaborative decision-making is essential to mitigate potential disruptions and cascading effects. Our research contributes to the development of a novel integrated decision-support architecture and underscores the role of digitalization and Industry 5.0 in future smart and sustainable reverse logistics planning.

Designing a sustainable plastic bottle reverse logistics network: A data-driven optimization approach

Management of recovery options for plastic beverage containers involves some challenges. Most materials of used containers are recycled and are used to produce new products. The locations of collection facilities are the strategic decisions, affecting the amount collected and the total cost of a Reverse Logistics Network (RLN). In this study, a multi-objective (MO) optimization model is introduced to configure a plastic beverage container RLN, considering economic, environmental, and social objectives. This study also implements a scenario-based possibilistic approach to handle the uncertainty of the parameters. Furthermore, a data-driven fuzzy optimization framework is developed to consider the overlapping and multi-clustered characteristics of historical data samples. The application of the proposed method is demonstrated by considering a network in Vancouver, Canada. The numerical results reveal that the optimal configuration of the RLN resulting from the proposed MO model exhibits significant sensitivity to fluctuations in costs, demands, and the prioritization of the objective functions. Additionally, the proposed data-driven framework can incorporate decision makers' preferences when tuning the conservatism degree of uncertain parameters and the preference level of different objectives of the MO model. Moreover, the developed data-driven algorithm can reduce over-conservatism by 14% and guarantee the feasibility of optimal solutions compared to other data-driven strategies.

Blockchain technology in circular economy: Unpacking the potential issues and critical echoes through data triangulation and natural language processing

AbstractThis study aims to identify the current status, potential issues and critical echoes in the integration of blockchain within circular economy (CE) practices. This study utilizes multiple data sources and synthesizes 91 published articles, and over 11,182 social media documents. Word‐embedding‐based clustering technique is employed to derive topics and themes on the use of blockchain in CE. The result of the study demonstrates that industries seek to implement blockchain for CE practices to automate processes for higher efficiency. However, issues revolving around blockchain governance and ethics, the impact of global trade facilitation, the skills required to implement blockchain, and sustainable reverse logistics within CE practices are major concerns. Additionally, acheiving a good return on investment while using blockchain for CE practices is another factor of concern for decision‐makers. This is the first study of its kind to discover topics, themes, potential issues, and critical echoes of integrating blockchain in CE through data triangulation. The results of this study are relevant to managers and policymakers, providing insights into leveraging up‐to‐date developments to address challenges in integrating blockchain within CE practices.

Assessing the E-Commerce Sustainability Readiness: A Green Logistics Study on Online Sellers

The increasing trend of technological advancement has led to significant changes in how customers purchase goods. Currently, buying products can be done most effectively from the comfort of one’s home through online shopping. Customers send and receive thousands of shipments daily, contributing to many materials and packaging that go to waste. While environmental sustainability is becoming increasingly important in all industries, little is known about the factors that drive e-commerce enterprises to adopt green logistical practices. The current study aims to identify the factors that have the most significance in creating sustainable e-commerce in the future of logistics and marketing. This study performed a statewide online seller survey in the Philippines to acquire data on product characteristics, including how internal processes and external partnerships are used and perceived to minimize the carbon footprint connected with order fulfillment and delivery. It encompassed a sample of 286 online sellers nationwide and employed structural equation modeling to identify the factors influencing green logistics practices within the e-commerce industry. The findings underscore that technology has a positive relationship in fostering sustainability. The results also establish significant positive correlations between sustainable e-commerce practices, government laws, seller behavior, and reverse logistics. Notably, this research sheds light on the intricate dynamics of drivers promoting green logistics within the Philippine e-commerce landscape.

Designing a robust sustainable reverse logistics to waste of electrical and electronic equipment: a case study

Designing a robust sustainable reverse logistics to waste of electrical and electronic equipment: a case study

Multi-echelon sustainable reverse logistics network design with incentive mechanism for eco-packages

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.

The Role of Logispreneurs in Advancing Waste Management in Malaysia: Towards a Sustainable Reverse Logistics and Green Future

Waste management has emerged as a critical challenge in Malaysia, driven by rapid urbanization, industrialization and changing consumption patterns. In response to these challenges, logispreneurs, a new breed of entrepreneurs with expertise in logistics and supply chain management, have emerged as key players in transforming waste management practices in the country. This research explores the vital roles and contributions of logispreneurs in the context of waste management in Malaysia, focusing on their efforts to enhance efficiency, sustainability, and environmental responsibility. Through a simple literature analysis, this study highlights the multifaceted roles that logispreneurs play in shaping the waste management landscape. They pioneer integrated waste collection and transportation systems, leveraging advanced technologies and data analytics to optimize routes and reduce carbon footprints. Moreover, logispreneurs lead the way in establishing reverse logistics networks for recyclable materials, fostering excellent recycling rates and diverting substantial waste from landfills. Logispreneurs specialize in managing hazardous waste materials, and ensuring safe transportation and disposal while complying with environmental regulations. They also contribute to public awareness and education campaigns, raising consciousness about sustainable waste management practices nationwide. This study elucidates the pivotal role logispreneurs play in revolutionizing waste management practices in Malaysia. Their logistics expertise and environmental consciousness amalgam present a promising pathway toward a sustainable future. By optimizing supply chain efficiencies, driving innovation and embracing social and environmental responsibility, logispreneurs are instrumental in building a resilient waste management ecosystem that ensures preservation of Malaysia's natural resources and safeguards the well-being of its citizens for generations to come.

A sustainable green reverse logistics plan for plastic solid waste management using TOPSIS method.

Recycling solid plastic waste is helpful for resource utilisation in a sustainable manner, and this can lead to reverse logistics to recover waste in supply chain management. In developing economies, it is very essential to recover waste and recycle it, as mismanagement of it could hasten the development of negative socioeconomic and environmental issues. This paper investigates plastic waste recycling by means of reverse logistics management. We feature Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), which is a multi-criteria decision-making approach to selecting a suitable warehouse that will assist the decision-maker and supply the product to the re-manufacturing cell by inspecting the waste. The paper also focuses on the carbon emissions that are emitted during re-manufacturing through a mathematical model that minimises the total cost and total carbon emissions. A case study of the plastic re-manufacturing industry in Tripura, India, is shown here to present the steps of the decision support system. The model is programmed with real-life data from the case study and yields a total cost of Rs. 2894.37 and total emissions of 414.15 gm/lt, when the disposal cost is considered; without it, the total cost is Rs. 2668.69 and the total emissions are 413.54 gm/lt. The results obtained are promising for reducing carbon emissions from the recycling process of plastic waste at a lower cost. This research will also help the environment cope with plastic waste, which has become a threat to nature, as well as carbon emissions that come from the industry. Finally, some managerial insights and suitable analyses with pictorial representation are proposed.

A Novel Sustainable Reverse Logistics Network Design for Electric Vehicle Batteries Considering Multi-Kind and Multi-Technology

With the expansion of the new energy vehicle market, electric vehicle batteries (EVBs) have entered a massive retirement wave. The strategic level of facility location and configuration decisions and the tactical level of multi-product flow and multi-technology selection decisions have been integrated into a sustainable reverse logistics network (SRLN). In this paper, we considered multiple kinds of waste electric vehicle batteries (WEVBs) with multiple recycling technology and constructed a multi-level SRLN model for WEVBs with the objectives of minimum economic costs and minimum carbon emissions. To solve this model, fuzzy set theory was applied to the equivalence transformation of constraints, non-interactive and interactive methods were used to solve the multi-objective planning (MOP), and interactive fuzzy programming with priority control was proposed to find the global optimal solution for this model. Finally, numerical experiments demonstrated the feasibility and effectiveness of the proposed model and solution method. The experimental results show that the SRLN model considering carbon emissions can significantly reduce carbon emissions of the network through a slight increase in the initial network construction cost, thus effectively balancing both economic and environmental objectives. In the non-interactive solution, the Lp-metric method has a lower deviation index than the weighted sum method; in the interactive solution, the priority control method proposed in this paper outperforms the TH method in terms of the number of practical solutions and CPU time and shows strong performance in searching and finding optimal solutions. The proposed model and method can provide the theoretical basis and technical support for a WEVB SRLN under the limited information uncertainty environment.

Analyzing sustainable reverse logistics capability and triple bottom line: the mediating role of sustainability culture

PurposeTo overcome the various pressures related to the environmental damage raised by production processes, enhancing sustainable reverse logistics (SRL) capability is a new road for manufacturing companies, as it facilitates them to have more sustainable operations by increasing different performance outputs. This study aims to investigate the relationship between the SRL capability and the triple bottom line (TBL) i.e. economic, social and environmental performance in the context of Turkey's manufacturing industry. The mediating role of sustainability culture has also been examined.Design/methodology/approachUsing survey data obtained from the Turkish manufacturing industry, the partial least square path modeling technique of structural equation modeling has been applied to test the research hypothesis.FindingsThe results of the study indicate that the SRL capability generates not only outstanding environmental and economic gains but also social benefits. The authors also find that sustainability culture is positively associated with environmental and social performance, yet not economic performance. In addition, the findings indicate sustainability culture mediates the relationship between SRL capability and social performance.Originality/valueThis study expands the frontier of managerial knowledge by highlighting the importance of SRL capability for sustainability and exhibiting evidence of the business value of enhancing SRL capability and sustainability culture.

Multi-objective combinatorial optimization analysis of the recycling of retired new energy electric vehicle power batteries in a sustainable dynamic reverse logistics network.

The recycling of retired new energy vehicle power batteries produces economic benefits and promotes the sustainable development of environment and society. However, few attentions have been paid to the design and optimization of sustainable reverse logistics network for the recycling of retired power batteries. To this end, we develop a six-level sustainable dynamic reverse logistics network model from the perspectives of economy, environment, and society. We solve the multi-objective combinatorial optimization model to explore the layout of the sustainable reverse logistics network for retired new energy vehicle power batteries recycling. A case study is implemented to verify the effectiveness of the proposed model. The results show that (a) the facility nodes near the front of the network fluctuate more by opening and closing; (b) the dynamic reverse logistics network is superior to its static counterpart; and (c) cooperation cost changes affect the transaction volume between third-party and cooperative enterprises and total network cost.

A Framework for Adopting a Sustainable Reverse Logistics Service Quality for Reverse Logistics Service Providers: A Systematic Literature Review

Reverse logistics has become a competitive need for sustainability. Lack of resources to apply reverse logistics solutions has severely impacted many supply chains’ costs and customer service, making it impossible to meet the expectations of return processing. In those conditions, client demands for higher service quality are the main drivers of effective sustainability operations. This study aims to establish the sustainable reverse logistics service quality (SRLSQ) theoretical framework offered by reverse logistics services providers (RLSPs). The study conducts a systematic methodology protocol by examining reliable academic periodicals using PRISMA guidelines based on the research scope and identified 56 papers from 2011–2022, with the main research focus on SSQ and RLSQ dimensions to develop a research framework. By re-evaluating those factors using the SRLSQ framework and by including sustainability into the service quality approach, this study expanded the practicability of reverse logistic service quality and sustainable service quality. The results point to a knowledge gap when it comes to quantifying the impact of reverse logistics operation process through a triple bottom line approach on customer outcomes, relationship quality (RQ), and mediation of operation risk factor, which could be examined within various contexts in subsequent work.

Prioritising critical success factors of sustainable reverse logistics for e-commerce organisations in India - MCDM approach

Prioritising critical success factors of sustainable reverse logistics for e-commerce organisations in India - MCDM approach

A q-rung orthopair fuzzy combined compromise solution approach for selecting sustainable third-party reverse logistics provider

PurposeReverse logistics (RL) is a type of supply chain management that moves goods from the end customer to the original manufacturer for reuse, remanufacturing and disposal purposes. Owing to growing environmental legislations and the development of new technologies in marketing, RL has attracted more significance among experts and academicians. Outsourcing RL practices to third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies due to complexity of RL operations and the lack of available resource. Current sustainability trends have made 3PRLP assessment and selection process more complex. In order to select the 3PRLP, the existence of several aspects of sustainability motivates the experts to establish a new multi-criteria decision analysis (MCDA) approach.Design/methodology/approachWith the growing complexity and high uncertainty of decision environments, the preference values of 3PRLPs are not always expressed with real numbers. As the generalized version of fuzzy set, intuitionistic fuzzy set and Fermatean fuzzy set, the theory of q-rung orthopair fuzzy set (q-ROFS) is used to permit decision experts (DEs) to their assessments in a larger space and to better cope with uncertain information. Given that the combined compromise solution (CoCoSo) is an innovative MCDA approach with higher degree of stability and reliability than several existing methods.FindingsTo exhibit the potentiality and applicability of the presented framework, a case study of S3PRLPs assessment is taken from q-rung orthopair fuzzy perspective. The assessment process consists of three sustainability aspects namely economic, environment and social dimensions related with a total of 14 criteria. Further, sensitivity and comparative analyses are made to display the solidity and strength of the presented approach. The results of this study approve that the presented methodology is more stable and efficient in comparison with other methods.Originality/valueThus, the objective of the study is to develop a hybrid decision-making methodology by combining CoCoSo method and discrimination measure with q-ROFS for selecting an appropriate sustainable 3PRLP (S3PRLP) candidate under uncertain environment. In the proposed method, a novel procedure is proposed to obtain the weights of DEs within q-ROFS context. To calculate the criteria weights, a new formula is presented based on discrimination measure, which provides more realistic weights. In this respect, a new discrimination measure is proposed for q-ROFSs.

A new last aggregation fuzzy compromise solution approach for evaluating sustainable third-party reverse logistics providers with an application to food industry

In today’s world, reverse logistics (RLs) activities have become increasingly crucial for companies looking for improved customer service, cost reduction, and sustainability perspectives. Limited resources, and insufficient technology and knowledge, have led manufacturing firms to cooperate with professional RL providers. However, evaluating the right third-party reverse logistics providers (3PRLPs) is a complex, uncertain multi-criteria decision-making (MCDM) problem, which is affected by many conflicting qualifications, the complexity of the human mind, and imprecise and uncertain information. This paper aims to introduce a novel framework that integrates fuzzy best worst method (BWM) and a new last aggregation fuzzy compromise solution for providing systematic decision support for organizations to select the most preferred partner. The reasons behind choosing both methods in an integrated way are that; the fuzzy BWM requires a smaller number of comparisons but can provide more reliable weights due to consistent criteria comparisons. Furthermore, the approaches based on compromise solutions are powerful decision-making tools because a compromise solution is a more feasible solution closest to the ideal that can be efficient in selecting the best alternative in the presence of conflicting decision criteria. Therefore, the fuzzy BWM approach is utilized to investigate the performance criteria of the 3PRLPs from economic, environmental, and social aspects of sustainability as well as risk factor. Expert weights and the preferences of sustainable 3PRLPs are then calculated simultaneously using a new last aggregation fuzzy compromise solution. Compared with the available literature, the proposed framework considers all possible sustainable criteria along with risk factor, which offers greater flexibility for experts to articulate their evaluations. In addition, the last aggregation fuzzy method eliminates distortion and loss of information and allows decision-makers to control the outcome’s precision. Moreover, the applicability of the proposed method is numerically demonstrated by developing a decision-support tool for the food industry. Sensitivity analysis and comparative analysis further illustrate the flexibility and practicability of proposed framework through which the decision-makers can make more accurate judgments regarding the evaluation of 3PRLPs.

Optimization of sustainable reverse logistics network with multi-objectives under uncertainty

Optimization of sustainable reverse logistics network with multi-objectives under uncertainty