Cleaner Logistics and Supply Chain最新文献

{"title":"Optimal location of mass logistics centers: improving transport efficiency for circular material flows","authors":"Mats Janné,&nbsp;Niki Matinrad","doi":"10.1016/j.clscn.2025.100295","DOIUrl":"10.1016/j.clscn.2025.100295","url":null,"abstract":"<div><div>Mass logistics centers (MLCs) are lately facing increasing recognition for their potential to improve transport efficiency in soil and rock material flows and to support circular mass systems, resulting in reduced CO₂ emissions. Despite this, decisions about where to locate MLCs are often made without any systematic analysis and instead are done ad hoc or, at times, based on opinions of experts. This study addresses that gap by proposing an optimization model to determine the optimal location for an MLC within a mass logistics system, where all materials are routed through one or several MLCs. We test the model using experimental data generated based on a real development project in Sweden. Furthermore, we perform a sensitivity analysis on several parameters to investigate their effect on the performance of the proposed model. The results show that a close relationship between transport efficiency, circularity and upscaling rate, transport capacity, and need for space at MLCs exists – the higher the circularity rate, the better the transport efficiency with reduced CO₂ emissions. They also indicate the necessity of finding the right balance between these factors in a given system rather than solely focusing on transport efficiency, to ensure the applicability of the solutions in the real-life system. This study, in a broad way, contributes to understanding how MLCs can reduce the environmental impact of mass transport and supports more strategic planning in infrastructure development.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"18 ","pages":"Article 100295"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pattern-based decision-support-tool to enhance resilience and sustainability in production networks: A framework proposal and application","authors":"Jan Felix Niemeyer ,&nbsp;Robin Maier ,&nbsp;Allan N. Zhang ,&nbsp;Mark Mennenga ,&nbsp;Shanshan Yang ,&nbsp;Zhiquan Yeo ,&nbsp;Christoph Herrmann","doi":"10.1016/j.clscn.2025.100290","DOIUrl":"10.1016/j.clscn.2025.100290","url":null,"abstract":"<div><div>Global production networks have become increasingly complex and interdependent due to decades of intensified globalization. While these developments have driven efficiency gains and competitive advantages, they have also led to significant environmental impacts. In response, regulations such as the Corporate Sustainability Due Diligence Directive are compelling companies to improve sustainability across their value chains. At the same time, recent local and global disruptions have underscored the critical importance of resilience. As a result, organizations must systematically evaluate and improve the sustainability and resilience of both their own operations and the broader production networks. However, research shows that lessons from past crises are often not fully internalized, and companies continue to struggle with fragmented domain-specific knowledge. Moreover, data alone does not yield actionable business insights. It only generates value when effectively combined with analytics and expert interpretation. Many of the proposed solutions for improving sustainability and resilience are not entirely new, but they require more integrated and systematic application to be effective. Against this background, we propose a decision support tool grounded on an iterative, pattern-based methodology. It combines simulation-based analysis using AnyLogistix with a knowledge-based database to enhance resilience and sustainability in production networks. The pattern-based approach enables the systematic identification, capture, and reuse of proven strategies. The methodology is successfully validated through a real-world use case in the electronics industry and shows that both resilience and sustainability can be effectively enhanced through the proposed approach.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"18 ","pages":"Article 100290"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of carbon footprint thresholds for designing climate neutral logistics warehouses in France at the early design stage","authors":"Sébastien Visse ,&nbsp;Francesca Contrada ,&nbsp;Arnaud Lapertot ,&nbsp;Andrea Kindinis ,&nbsp;Abderrahim Boudenne","doi":"10.1016/j.clscn.2025.100289","DOIUrl":"10.1016/j.clscn.2025.100289","url":null,"abstract":"<div><div>Reducing the environmental impact of logistics warehouses is a critical challenge, particularly during the early design phase when limited data is available to guide decision-making. This study aims to establish carbon footprint targets for logistics warehouses in alignment with climate neutrality objectives. Using Life Cycle Assessment (LCA) methodologies, the environmental impacts of 16 Lidl Company logistics warehouses in France were evaluated. A correlation analysis revealed that warehouse size and cold storage capacity are the strongest predictors of carbon footprint (Pearson coefficients of 0.78 and 0.68, respectively). Based on these relationships, a carbon footprint threshold function was developed using a linear regression model optimized by a Non-dominated Sorting Genetic Algorithm II (NSGA-II), achieving an error margin below 7%. The resulting model quantifies emissions per pallet space according to storage type, ranging from 1.11 TCO₂eq/pallet for dry goods (high shelf) to 4.96 TCO₂eq/pallet for fresh-produce block storage. These findings demonstrate that achieving carbon neutrality for logistics warehouses requires not only energy-efficient operations but also substantial reductions in embodied emissions through low-carbon materials and optimized design strategies. The predictive carbon footprint threshold function proposed here provides a robust, data-driven tool to guide the design of future industrial buildings aligned with national and international sustainability goals.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"18 ","pages":"Article 100289"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-dimensional perspective to the adoption of green hydrogen as an alternative fuel for the transportation sector: An integrated DELPHI-Fuzzy DEMATEL technique","authors":"Amit Kumar Gupta,&nbsp;Manoj Srivastava","doi":"10.1016/j.clscn.2025.100274","DOIUrl":"10.1016/j.clscn.2025.100274","url":null,"abstract":"<div><h3>Context</h3><div>Hydrogen, produced through electrolysis using renewable energy sources such as solar and wind, is often referred to as the “Fuel of the Future” by many energy experts worldwide. The usage of sustainable energy ensures no emission of greenhouse gases during combustion or production; hence, it is “Green” Hydrogen. India, recognizing its immense potential in solar and wind energy, is striving to take the lead globally in producing green hydrogen and utilizing it in both the industrial and transportation sectors. Globally, Hydrogen is in the early stages of adoption as a transportation fuel, with the potential to replace various fossil fuels, such as gasoline, diesel, aviation turbine fuel, and marine fuel.</div></div><div><h3>Methodology</h3><div>Since hydrogen is widely used in industries such as oil refineries, fertilizer production, and steel plants, this research focuses on analyzing the factors for the widespread adoption of green hydrogen in India, primarily in the transportation sector, grounded on institutional theory. Considering the findings of the literature review and the opinions of experts, a total of 32 factors were identified related to the adoption of alternative fuels, including EVs. A total of eleven interrelated factors were identified through the Delphi method. The factors are further analyzed for cause-and-effect relationships using Fuzzy-DEMATEL.</div></div><div><h3>Finding</h3><div>All core characteristics of a product, viz., price, functionality, performance, quality, conformance, and perceived value, were considered during the finalization of elements. The identified factors are green H₂ price, levelized cost of green H₂, infrastructure, energy efficiency, safety, regulations and standards, incentive mechanisms, environmental awareness, limited financing channels, social acceptance, and motivation.</div></div><div><h3>Novelty</h3><div>Hydrogen as a fuel in the<!--> <!-->transportation sector remains relatively nascent, particularly in developing nations. This study provides insightful information by addressing interrelated political, regulatory, technological, environmental, and economic issues. Additionally, it provides data that can inspire participants to collaborate, enabling India to realize its full potential and lead the world in the green hydrogen industry, thereby fostering environmental sustainability, job creation, and economic growth.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"17 ","pages":"Article 100274"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A stakeholder-centric fuzzy AHP-TOPSIS framework for prioritizing challenges and solutions in the sustainable circular supply chain of electric vehicle batteries","authors":"V.M. Aishwarya ,&nbsp;Banu Yetkin Ekren ,&nbsp;Tej Singh ,&nbsp;Vedant Singh","doi":"10.1016/j.clscn.2025.100272","DOIUrl":"10.1016/j.clscn.2025.100272","url":null,"abstract":"<div><div>The worldwide shift to electric mobility has rendered the establishment of sustainable and circular electric vehicle (EV) battery supply chains an immediate imperative. This study proposes a stakeholder-centric, hybrid multi-criteria decision-making framework that incorporates Fuzzy Analytical Hierarchy Process and Fuzzy Technique of Order of Preference by Similarity to Ideal Solution to prioritize challenges and solutions in the EV battery supply chain. Drawing on stakeholder and sustainability theories, the framework evaluates 10 primary challenge domains, 35 sub-challenges, and 14 solution strategies based on insights from six key stakeholder groups: mining and resource extraction, raw material procurement, manufacturing and product development, supply chain and logistics, product management and strategy, and research and development. FAHP results identify environmental resource and lifecycle concerns and supply network robustness and economic stability as the most significant challenge areas. At the sub-criteria level, stakeholders prioritized scarcity and sustainability of vital resources and vulnerabilities in supply chain architecture. FTOPSIS analysis ranks policy framework and compliance and collaborative and stakeholder engagement as the most influential and widely endorsed solution strategies. A foresight-based sensitivity analysis for the year 2040 compares two contrasting future scenarios: a fully developed circular battery ecosystem and another marked by global supply chain volatility and heavy import dependence. Innovation-driven solutions dominate the former, while policy preparedness and economic incentives dominate in the latter. This study offers a novel, transferable framework that aligns stakeholder priorities with circular economy objectives, providing strategic guidance for fostering resilient and sustainable EV battery supply chains across global regions.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"17 ","pages":"Article 100272"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145363545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breaking new ground in sustainability (SD): a novel integrated framework for eco/green-innovation (EI) and green supply chain management (GSCM) implementation in emerging economies – evidence from Jordan’s industrial transformation","authors":"Lana Freihat ,&nbsp;Zayed Huneiti ,&nbsp;Wamadeva Balachandran","doi":"10.1016/j.clscn.2025.100279","DOIUrl":"10.1016/j.clscn.2025.100279","url":null,"abstract":"<div><div>The Emerging economies face a Sustainability (SD) paradox is the need to adopt green logistics and supply chain practices while constrained by limited resources and inadequate institutional frameworks. This study tackles three core challenges: (1) the absence of context-specific theories explaining Eco/Green-Innovation (EI) integration within Green Supply Chain Management (GSCM), (2) lack of empirical insights into SD implementation in Middle Eastern industries, and (3) the missing link between organizational practices and progress toward UN Sustainable Development Goals (SDGs).The research introduces four innovations: (1) a mixed-methods design combining PRISMA-based literature review with a case study for both breadth and depth, (2) the first validated measurement framework for EI–GSCM integration in the Middle East, (3) a theoretical model combining Resource-Based View, Institutional Theory, and Diffusion of Innovation Theory to explain implementation under constraints, and (4) an SDG-mapping method directly linking SD practices to specific SDG targets. Key insights include: green procurement as the most effective starting point (78 % adoption); Green Human Resource Management (GHRM) as a vital mediator (r = 0.399); the need for integrated, not sequential, implementation; Total Quality Environmental Management as a strong secondary approach (65 %); and practical pathways linking practices to SDG 12.This is integrated empirical and theoretical study on EI and GSCM tailored to emerging economies, offering practical frameworks and advancing sustainable supply chain transformation. Building on these findings, future research should explore emerging eco-technologies such as artificial intelligence, blockchain, and smart irrigation systems to enhance SD performance.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"17 ","pages":"Article 100279"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Turning challenges into opportunities when adopting remanufacturing by original equipment manufacturers","authors":"Jelena Kurilova-Palisaitiene ,&nbsp;Paulina Golinska-Dawson ,&nbsp;Leire Gorroño-Albizu ,&nbsp;Johan Vogt Duberg","doi":"10.1016/j.clscn.2025.100265","DOIUrl":"10.1016/j.clscn.2025.100265","url":null,"abstract":"<div><div>The recent trend towards sustainable production and consumption contributes to the development of the remanufacturing industry worldwide. Despite the growing number of independent remanufacturers, remanufacturing is practiced by a limited number of European original equipment manufacturers (OEMs). There is a gap in OEM knowledge on remanufacturing as well as a lack of successful cases of OEMs adopting remanufacturing. Yet, the remanufacturing research focuses on <em>why</em> instead of <em>how</em> to adopt remanufacturing. As a result, many OEMs willing to adopt remanufacturing find themselves lost in numerous challenges. The <strong>aim</strong> of this paper is to identify OEM challenges when adopting remanufacturing and develop recommendations on how to turn challenges into opportunities. To achieve this aim, we utilize literature review and case study research methodologies. In the literature, we identified 12 clusters of challenges on OEM <em>micro</em>- and <em>meso</em>-levels and verified those at eight case companies. We then outlined the recommendations for OEMs on how to turn challenges into opportunities.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"17 ","pages":"Article 100265"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to make low-carbon supply chain decisions: considering technology spillover and unit R&D costs","authors":"Li Yuping ,&nbsp;Lin Zigan","doi":"10.1016/j.clscn.2025.100270","DOIUrl":"10.1016/j.clscn.2025.100270","url":null,"abstract":"<div><div>In the context of low-carbon economic development, the vertical spillover effects of emission reduction technologies and the unit cost of emission reduction (CRICF) within supply chains significantly influence firms’ emission reduction decisions and profit distribution. This study investigates the impacts of vertical spillover effects of emission reduction technologies (SCERT) and CRICF on decision-making and coordination in low-carbon supply chains, exploring supply chain decision models under different scenarios and their effects on firm profits, consumer surplus, and social welfare. The primary findings are as follows: First, an increase in SCERT significantly enhances the emission reduction technology levels of both upstream and downstream firms in the supply chain, while also driving up product prices; however, SCERT does not affect the proportion of emission reduction levels between suppliers and manufacturers. Second, under both centralized and decentralized decision-making frameworks, an increase in CRICF reduces firms’ emission reduction technology levels and profits, and differences in CRICF between suppliers and manufacturers influence their respective emission reduction decisions and profit allocation. Third, the centralized decision-making model outperforms the decentralized model in terms of supply chain profits, market demand, consumer surplus, and social welfare. Finally, this study designs a Nash bargaining mechanism, demonstrating its effectiveness in coordinating the supply chain and achieving Pareto improvements in profits for both suppliers and manufacturers. The results suggest that enhancing the research and development of emission reduction technologies, strengthening technical exchanges between upstream and downstream supply chain entities, improving firms’ bargaining power, and increasing consumers’ low-carbon preferences are critical to promoting coordination and sustainable development in low-carbon supply chains. This research provides theoretical support for firms’ decision-making under the constraints of emission reduction technology spillovers and costs, while offering managerial insights for policymakers.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"17 ","pages":"Article 100270"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A sustainable crowd shipping model using public transport for low-carbon urban logistics","authors":"Hisatoshi Naganawa ,&nbsp;Enna Hirata ,&nbsp;Russell G. Thompson","doi":"10.1016/j.clscn.2025.100276","DOIUrl":"10.1016/j.clscn.2025.100276","url":null,"abstract":"<div><div>This study proposes a novel approach to sustainable urban logistics through a crowdsourced co-modality transportation system (CCTS) integrated with public transport networks. The research introduces a dual-layer multi-modal CCTS framework that optimally combines conventional delivery services with crowd shipping, leveraging existing passenger transport infrastructure to reduce environmental impacts. A dynamic programming model is developed to optimize mode selection, incorporating multiple transport modes in the context of physical internet, congestion constraints, train capacity, and carbon footprint considerations. By employing heuristic search methods for parcel locker placement, the study enhances last-mile delivery efficiency. Using Osaka as a case study, simulation results demonstrate that engaging commuters as delivery agents and integrating smart parcel lockers can significantly reduce urban freight emissions – achieving up to 80% carbon savings in specific scenarios. These findings highlight the potential of public transport-based crowd shipping to enhance delivery efficiency while contributing to cleaner and more sustainable cities.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"17 ","pages":"Article 100276"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk evaluation in the implementation of sustainable measures in the supply chain operations: A Fuzzy Delphi-DEMATEL approach","authors":"Venkateswarlu Nalluri ,&nbsp;K. Meghana Chowdary ,&nbsp;Long-Sheng Chen","doi":"10.1016/j.clscn.2025.100262","DOIUrl":"10.1016/j.clscn.2025.100262","url":null,"abstract":"<div><div>Sustainable supply chain operations in developing countries like India face significant challenges due to fragmented risk management frameworks, regulatory uncertainty, infrastructural bottlenecks, and resource limitations, these issues hinder the effective implementation of sustainable measures. A critical problem is the lack of a systematic understanding and clearly defined causal relationships among the risks that impact sustainability initiatives. This study aims to holistically evaluate the causal relationships between these risks associated with the implementation of sustainable measures in supply chain operations. Key Risk Factors (KRFs) were identified through a thorough systematic literature review and validated using the Fuzzy Delphi Method (FDM). Further, to examine the causal relationship among KRFs used the Fuzzy DEMATEL method. This study result was confirmed that difficulty in importing technology and process, market competition, and changes customer in expectations are major risks. The management and operational, and logistics and infrastructural were determined as minor risks. This study contributes by identifying KRFs and evaluating their causal relationships in the implementation of sustainable measures within supply chain operations, through a combined Fuzzy Delphi–DEMATEL approach. By modelling the structural influence among KRFs, the study provides practical insights for service supply chain operators to design targeted risk mitigation strategies. These insights are vital for supporting the adoption of sustainable practices in the unique context of India’s supply chains. This research adds to the existing literature by comprehensively identifying and classifying stakeholder-driven causal relationships among KRFs in service-oriented supply chains using Fuzzy Delphi–DEMATEL approach.</div></div>","PeriodicalId":100253,"journal":{"name":"Cleaner Logistics and Supply Chain","volume":"17 ","pages":"Article 100262"},"PeriodicalIF":6.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}