Search Results (958)

Environmental concerns and the increasing scarcity of resources force decision makers in the supply chain to consider reuse and re-production. Closed loop supply chain is a fundamental concept that has attracted the attention of many researchers due to its profitability for businesses as well as its positive environmental and social effects. Closed-loop supply chains and sustainability dimensions are complementary because of their mutual effects. This paper develops a mathematical model to design a sustainable closed-loop supply chain network in the wood–plastic composite industry. Due to the nature of the problem considered, a mixed-integer linear programming method is utilized. The proposed model is a multi-objective model, and the Lp-metric method is used to solve it. The proposed model is applied in a real case in Iran. The proposed model identified 17 optimal provinces for manufacturing centers, 15 for reuse centers, and 9 for reproduction centers. Verification and validation of the proposed model illustrate its capability in real world implications. Full article

In recent years, China has faced the dual challenge of achieving high-quality economic development (HQED) alongside carbon emission reduction (CER), with new-quality productivity (NQP) emerging as a key driver integrating both agendas. Research on the coordinated development of these three dimensions remains limited but is critical for effective policy-making. Based on panel data from 30 Chinese provinces (2014–2023), this study constructs the NQP-CER-HQED evaluation indicator system; calculates the composite index using the entropy weight method and composite index calculation model; computes the coupling coordination degree (CCD) of the three components via the CCD model; analyzes the temporal evolution and future trends of CCD using kernel density and GM(1,1) models; examines the spatial evolution of CCD through Moran’s I index; employs traditional Markov chains and spatial Markov chains to investigate the spatial-temporal evolution patterns of CCD; and applies the geographic detector method to analyze the influencing factors of CCD among NQP, CER and HQED. The findings reveal that (1) the CCD of China’s NQP-CER-HQED has undergone six levels, showing an overall upward trend; (2) temporally, CCD levels improve annually, with all provinces expected to achieve coordinated development by 2026; (3) spatially, the CCD exhibits a “high-east, low-west” tiered distribution; (4) spatially/temporally, the transition of the CCD levels is primarily gradual rather than leapfrogging; and (5) the level of opening up and new-quality labor resources are identified as dominant influencing factors, with the interaction between new-quality labor resources and government support showing the strongest explanatory power. This study provides an analytical framework for understanding the NQP-CER-HQED synergy and offers a scientific basis for sustainable policy formulation. Full article

This systematic search with narrative synthesis examines metaverse business models and their shift toward immersive virtual ecosystems. Following the PRISMA flow for identification and screening to structure transparency, we review 91 publications to map the shift from classical and digital models to metaverse models, highlighting new value propositions, revenue mechanisms, and the integration of VR, AR, and blockchain across the value chain. Our contributions are threefold: we articulate the transition patterns from classical and digital to metaverse business models; we propose a structured metaverse business framework with evaluation dimensions; and we compile a candidate metric set to support comparative analysis. Interpreting the evidence through a socio-technical systems lens, the synthesis indicates an emergent shift in how value is created, delivered, and captured. We identify five core dimensions for assessing metaverse business models: scalability, technological adaptability, user engagement and retention, ethical and sustainability practices, and economic viability as critical dimensions for future comparative analysis of metaverse business models. Building on these findings, we propose a metaverse business framework and a set of candidate KPIs to enable comparative evaluation and guide investment, design, and governance. The paper advances digital transformation theory and outlines a research agenda on dynamic capabilities and the long-term sustainability of metaverse business models. Full article

Supply chains are a primary contributor to global greenhouse gas (GHG) emissions, rendering their decarbonization an essential dimension of sustainable development. Artificial intelligence (AI) provides a transformative pathway by facilitating proactive emission avoidance through operational efficiency, transparency, and resilience, in contrast to post-emission mitigation approaches such as carbon capture. This study explores the potential of AI to support indirect carbon dioxide removal (CDR) via supply chain decarbonization, adopting a comparative case study methodology. Empirical evidence is drawn from Tunisian agri-food, textile, and port logistics sectors, based on multi-source datasets spanning 6–12 months and covering fleet sizes ranging from 40 to 250,000 units. Methodological robustness was ensured through the use of pre-intervention baselines, statistical imputation for missing data (<5%), and validation against 20% out-of-sample test sets. Results indicate that AI-enabled interventions achieved annual avoided emissions between 500 and 1500 tCO₂ and reduced fuel consumption by 12–15%, with sensitivity analyses incorporating ±8–12% error margins. Among the approaches tested, hybrid models integrating operational and strategic layers demonstrated the most pronounced impact, aligning immediate efficiency gains with long-term systemic decarbonization. Furthermore, AI facilitates renewable energy integration, digital twin applications, and compliance with international sustainability frameworks, notably the Paris Agreement and the United Nations Sustainable Development Goals. Nevertheless, challenges related to data quality, computational demands, limited expertise, and organizational resistance constrain scalability. The findings underscore AI’s dual role as a technological enabler and systemic driver of supply chain decarbonization, advancing its positioning within global environmental sustainability transitions. Full article

This study investigates the effect of pyrite content on the flocculation and sedimentation of clay-based tailings composed of kaolin, quartz, and pyrite in seawater at pH 8. A high-molecular-weight anionic hydrolyzed polyacrylamide (SNF 704) was used in batch settling tests, supported by floc characterization with FBRM, zeta potential measurements, and molecular dynamics (MD) simulations. Results showed that increasing pyrite content reduced the maximum floc size and increased the fraction of unflocculated fines, particularly at 10 g/t dosage. Although the fractal dimension remained nearly constant (1.92–1.97 at 10 g/t and 2.05–2.08 at 30 g/t), floc density increased linearly with pyrite proportion due to its higher specific gravity. Zeta potential analysis confirmed strong polymer–pyrite interactions, with charge inversion from +5.3 to −4.5 mV, while MD simulations indicated that adsorption occurs mainly through aliphatic chain segments, in contrast to hydrogen bonding observed for quartz and kaolinite. These findings demonstrate that pyrite affects flocculation dynamics both by its density and by specific polymer–surface interactions, directly influencing floc size, density, and sedimentation performance in seawater thickening systems. Full article

The sustainable management of forest supply chains is particularly challenging in regions affected by socio-territorial conflicts, such as southern Chile, where Indigenous land claims and environmental concerns complicate operations. This study develops and applies a multi-objective mixed-integer linear programming (MILP) model to support tactical planning of the forest-to-lumber supply chain. The model operates the three pillars of sustainability through representative variables: raw material consumption (economic efficiency), transport distance (environmental impact), and exposure to territorial conflicts (social risk). These sustainability dimensions are consistent with the United Nations Sustainable Development Goals (SDGs) 8 (Decent Work and Economic Growth), 9 (Industry, Innovation and Infrastructure), 12 (Responsible Consumption and Production), and 16 (Peace, Justice and Strong Institutions). Computational experiments reveal Pareto trade-offs between productive efficiency and social vulnerability, showing that simpler logistics networks can substantially reduce conflict exposure without significant efficiency losses. Additionally, the strategy of minimizing the production of lumber that does not have immediate demand also helps reduce log consumption and improves log yield. The results provide a decision-oriented framework for conflict-sensitive supply chain planning, contributing to more resilient, socially responsible, and sustainable forest operations in Chile. Full article

Material handling (MH) plays a critical role in the performance, cost efficiency, and sustainability of high-rise construction projects. Despite its significance, MH practices in such projects remain challenged by complex vertical logistics, space constraints, fragmented supply chains, and increasing pressure to align with decarbonisation goals. This study applies a mixed-methods approach that integrates a systematic literature review, semi-structured expert interviews, and a SWOT–AHP (Strengths, Weaknesses, Opportunities, Threats—Analytic Hierarchy Process) model to identify and prioritise factors influencing MH optimisation in China’s high-rise construction sector. Eighteen factors were evaluated across four SWOT dimensions, and expert pairwise comparisons were aggregated using geometric means. The results revealed that Technological Adoption (S1) and Technological Advancements (O3) are the most critical enablers, while High Implementation Costs (W2) and Resource Scarcity (T3) are the most significant constraints. Interactions among these factors highlight the dual importance of internal digital capabilities and external technological trajectories in shaping MH strategies. Comparative analysis with practices in Europe, the United States, and the Middle East demonstrates that digitalisation, financial mechanisms, and policy incentives are globally consistent drivers of MH innovation. The findings advance theoretical understanding by integrating perspectives from the Resource-Based View, Technology-Organisation-Environment, and Institutional Theory, and they offer practical implications for policymakers and industry stakeholders seeking to align MH optimisation with China’s dual-carbon targets. This study contributes to the development of a comprehensive decision-support framework that enhances the sustainability, resilience, and efficiency of material logistics in high-rise construction projects. Full article

In the context of smart agriculture, the tea industry is undergoing a transformative shift toward intelligent development. As the birthplace of tea, China holds a significant position in the global tea industry, with Anxi County in Quanzhou City, Fujian Province—renowned as the origin of Tie Guan Yin—standing as the world’s largest oolong tea production area. Its intelligent transformation of the tea industry is typical and representative. However, current research on the digital literacy of farmers is not yet mature, and there is a lack of systematic research on this specific group of tea farmers, which to some extent restricts the transformation of the tea industry towards intelligent development. The level of digital literacy among tea farmers is crucial for the intelligent development and transformation of the tea industry. Improving the digital literacy of tea farmers is the key to promoting the intelligent development of the tea industry. Therefore, studying the digital literacy of tea farmers has significant practical significance. This article takes Anxi County as the research area and focuses on moderate-scale tea farmers as the research object. Based on the United Nations Global Framework for Digital Literacy and taking into account the actual situation of tea farmers, an evaluation index system and analysis framework for tea farmers’ digital literacy have been constructed from seven dimensions: equipment and software operation skills, digital information literacy, digital communication and collaboration literacy, digital content creation literacy, digital security literacy, problem-solving literacy, and professional digital literacy. Using literature review, questionnaire survey, interview, and quantitative analysis methods, a questionnaire containing the above-mentioned dimensions was designed. After collecting data, the rationality of the questionnaire structure was verified using SPSS software. The digital literacy level of 440 medium-sized tea farmers from 11 major tea-producing townships in Anxi County was measured, analyzed, and Two-Tailed correlation tests were conducted. The results indicate that there are currently six aspects of digital literacy among tea farmers that are at a moderate level, and professional digital literacy is the weakest among the seven digital literacy. The overall digital literacy level of tea farmers needs to be strengthened. Large-scale tea farmers have the conditions to apply smart agricultural equipment and technology, which can achieve intelligent and refined management of tea gardens and intelligent upgrading of the entire industry chain. Based on the research results of the seven digital literacy of tea farmers, this article proposes improvement measures corresponding to the seven digital literacy of tea farmers from the perspectives of “government, industry associations, and training institutions”, providing reference for Anxi County and other tea-producing areas in the world. Full article

In the context of a complex and volatile domestic and global environment, Chinese enterprises face frequent risks of supply chain disruption that seriously hinder their operations. The rise of the digital economy offers new opportunities to strengthen supply chain resilience. Building on supply chain collaboration and value co-creation theories, this study conceptualizes supply chain collaboration through three dimensions, namely information collaboration, governance collaboration, and innovation collaboration, and explores their role in enhancing resilience. Using panel data of Chinese A-share listed firms from 2011 to 2023, this study investigates the impact of focal firm digitalization on supply chain resilience and its underlying mechanisms. The results indicate that focal firm digitalization generates significant backward spillover effects, enhancing the resilience of its upstream suppliers. Although its positive influence on supply chain stability (measured by supply chain demand and supply fluctuations) is not statistically significant, it substantially enhances recovery (measured by supply chain efficiency) and adaptability (measured by supplier innovation). Mechanism analysis further reveals that digitalization strengthens supply chain collaboration through information, governance, and innovation channels, thereby reinforcing resilience. Moreover, the positive effects are heterogeneous, varying with industry competition intensity, the closeness of upstream–downstream relationships, and suppliers’ regional resource endowments. These findings highlight the need to design digitalization strategies centered on focal firm leadership and upstream–downstream collaboration, thereby advancing both resilience improvement and collaborative mechanism development through differentiated and targeted approaches. Full article

Background: Supplier evaluation and selection are pivotal processes in supply chain management, profoundly influencing organisational efficiency and sustainability. This study addresses the limitations of traditional multi-criteria decision-making approaches, particularly the Technique for Order Preference by Similarity to an Ideal Solution, which often lacks dimensional reduction capability and assumes uniform weight distribution across criteria. Methods: To overcome these challenges, a hybrid model integrating non-negative matrix factorisation, random forest, and the Technique for Order Preference by Similarity to an Ideal Solution is developed for supplier evaluation in the pharmaceutical sector. The method first applies non-negative matrix factorisation to condense twenty-four evaluation criteria into eight core dimensions, enhancing analytical efficiency and reducing complexity. Random forest is then employed to derive data-driven weights for each criterion, ensuring accurate prioritisation. Finally, the Technique for Order Preference by Similarity to an Ideal Solution ranks suppliers and provides actionable insights for decision-makers. Results: Results from real-world pharmaceutical data validate the model’s effectiveness and demonstrate superior performance over conventional evaluation methods. Conclusions: The findings confirm that integrating machine learning techniques with established decision-making frameworks enhances precision, interpretability, and sustainability in supplier selection while requiring adequate data quality and computational resources for implementation. Full article

The earthquakes that impacted Kahramanmaraş on 6 February 2023, caused multidimensional destruction across the southeastern provinces of Türkiye and incurred severe business losses. This study provides a comparative assessment of four heavily affected provinces (Adıyaman, Hatay, Kahramanmaraş, and Malatya) in terms of business losses. Eleven criteria, grouped as human and operational losses (HOL) and commercial and economic losses (CEL), were considered in the evaluation. For the first time, the Ranking Comparison (RANCOM) method was integrated into the Modified Kemeny Median Ranks Accordance (KEMIRA-M) framework to determine the weights of the criteria and ensure consistency in the ranking process. The findings indicate that Hatay suffered the highest level of losses, followed by Adıyaman, Kahramanmaraş, and Malatya, respectively. This study fills a gap in the disaster economics literature by emphasizing workforce and business continuity dimensions, an area where business losses have received relatively less attention. The results highlight that post-disaster recovery policies should not be limited to physical reconstruction but should also emphasize human capital, supply chain resilience, and sustainability-focused recovery strategies. Full article

In the context of increasing resource scarcity and pervasive uncertainty, informed economic decision-making requires access to timely and accurate information. Real-time sustainability monitoring tools, such as sensor- or RFID-based systems, have become essential to capture dynamic changes in production environments. Given the growing importance of sustainability, evaluating the environmental impact of production systems through Life Cycle Assessment (LCA) is critical, while economic dimensions are typically addressed via Life Cycle Costing (LCC). However, conventional LCA and LCC approaches often rely on static or outdated data, limiting their applicability in dynamic environments. This paper presents an integrated framework for the real-time assessment of Life Cycle Assessment (LCA) and Life Cycle Costing (LCC), utilizing Radio Frequency Identification (RFID) technology to facilitate continuous data collection throughout the production chain. By combining environmental and economic assessments with real-time data streams, the proposed framework supports more adaptive, transparent, and sustainable decision-making in resource-constrained industrial contexts. Full article

Recent research has increasingly emphasized the synergies between Supply Chain Management Practices (SCMPs) and Quality Management Principles (QMPs), particularly through the emerging concept of Supply Chain Quality Management (SCQM). Despite this recognition, empirical evidence on how these practices interact to influence performance remains very limited, especially in the context of developing countries. This study addresses the gap by interviewing 70 Tunisian agri-food companies to investigate the relationships between five dimensions of SCMP, strategic supplier partnerships, customer relationship, information sharing, information quality and postponement, and the seven principles of ISO9001 QMP: leadership, engagement of people, improvement, customer focus, process approach, evidence-based decision making, and relationship management. Using factor analysis and structural equation modelling, the study explores the mediating role of competitive advantage (CA): price/cost, product quality, product innovation, delivery dependability and time-to-market—on operational performance. The findings indicate that analyzing SCMP, QMP, and CA as aggregated blocks does not produce significant explanatory correlations. Instead, judiciously reorganizing their sub-constructs into five integrated groups provides a more effective model: (1) information and decision capacity, (2) customer-centric innovation, (3) process management and agility, (4) supplier and network management, and (5) leadership and workforce engagement. This integrated classification offers managers a coherent framework for implementing SCMP and QMP to enhance competitiveness results. Full article

Wireless sensor networks play a crucial role in IoT applications. Traditional range query methods have limitations in multi-sensor data fusion and energy efficiency. This paper proposes a new range query method for two-layer wireless sensor networks. The method supports data fusion operations directly on storage nodes. Communication costs between sink nodes and storage nodes are significantly reduced. Reverse Z-O coding optimizes the encoding process by focusing only on the most valuable data. This approach shortens both encoding time and length. Data security is ensured using the Paillier homomorphic encryption algorithm. A comparison chain for the most valuable data is generated using Reverse Z-O coding and HMAC. Storage nodes can perform multi-sensor data fusion under encryption. Experiments were conducted on Raspberry Pi 2B+ and NVIDIA TX2 platforms. Performance was evaluated in terms of fusion efficiency, query dimensions, and data volume. The results demonstrate secure and efficient multi-sensor data fusion with lower energy consumption. The method outperforms existing approaches in reducing communication and computational costs. Full article

This article addresses the contemporary and highly relevant research area of business sustainability, which attracts the attention of both scholars and management practitioners. Although the social dimension of sustainability is gaining increasing importance, there remains a research gap regarding the extent to which social initiatives contribute to sustainable outcomes. This study specifically focuses on the social dimension of business sustainability. The primary objective of the study is to examine the relationship between activities within the social dimension and sustainable outcomes. Moreover the study extends earlier research by contributing new empirical evidence from the Polish context, thereby enriching the existing body of knowledge. The study encompasses 303 organizations operating in Poland and utilizes a questionnaire-based survey. The collected data were employed to construct a regression model. The results indicate statistically significant relationships between social outcomes and key variables, namely, societal values and employee-related outcomes. The results indicate that social value creation and value chain integration are the strongest predictors of sustainable outcomes The variables were measured using subjective indicators. In addition, the research was conducted only in companies operating in Poland, and the results may be typical of businesses operating in this country. Therefore, the research should be extended to other countries, and it would be particularly interesting to compare with companies operating in countries where sustainability-related indicators are highly rated. It would also be very interesting to expand the data gained through questionnaires through interviews and case studies, linking social-focused business activities to the benefits that businesses can achieve in the area of sustainable outcomes as a result. Full article