Search Results (2,401)

This study aims to explore allocation strategies for idle emergency supplies in a “demander–platform–supplier” supply chain system along with government regulation during the post-disaster recovery period. Allocation of emergency supplies is a complex task that encompasses resource allocation before and after disasters. It is essential to reduce losses in disaster-stricken areas and support development during post-disaster recovery. However, there is often an excessive supply of emergency materials and a mismatch between supply and demand sides in downstream supply chains, which may lead to severe waste and difficulties in recovering surplus materials. This paper takes idle emergency resource sharing level and corporate social responsibility goodwill as endogenous variables. The allocation approaches are dynamically evaluated by incorporating random elements that influence the endogenous variables. Three stochastic differential games are introduced to examine the interactions between the players. The centralized decision-making satisfies the consistency of overall and individual rationalities at any time in the emergency material allocation process, promoting the optimal sharing levels of emergency materials and overall profits. The decentralized decision-making with cost-sharing contracts achieves local optima and increases the dual marginal effect of the emergency industry chain. This paper incorporates the sharing economy into emergency management, showing how technology-driven sharing platforms can optimize resource utilization. The results suggest introducing cost-sharing contracts between demanders and suppliers can enhance collaboration and effort, leading to better resource allocation and increased efficiency. It contributes to sustainability by promoting efficient resource utilization through idle emergency resource sharing. By optimizing allocation strategies and enhancing corporate social responsibility, the study fosters the long-term viability and resilience of the supply chain system in post-disaster management. Full article

Clarifying the dynamic relationships between urbanization, tourism development, and the ecological environment in underdeveloped regions can assist local governments in optimizing industrial upgrades and environmental management through effective policy planning, despite resource constraints, thereby promoting high-quality urban development. This study, based on data from 32 cities in northwestern China, constructs a multi-dimensional evaluation system incorporating demographic, economic, social, and environmental indicators. Using a PVAR model, the long-term dynamic interactions between urbanization, tourism, and the ecological environment are explored. The results indicate that, although in the initial stages, the three subsystems can support each other, in the long term, tourism has a positive impact on urbanization and the ecological environment, whereas both urbanization and the ecological environment negatively impact tourism. The interaction effects between urbanization, tourism, and the ecological environment are weak, with contribution rates below 20%, failing to create a synergistic development. The primary reason for this issue is that urbanization development policies lag behind the needs of tourism and ecological environment development. Policy recommendations are provided, including optimizing cross-sector collaboration strategies, enhancing urbanization quality, and prioritizing environmental protection, to foster coordinated development among the three. Full article

The construction industry plays a crucial role in the global economy but faces significant challenges, including inefficiencies, high costs, and environmental impacts. Although Building Information Modeling (BIM) has been widely adopted as a solution to these issues, its practical impact remains limited. This study investigates how manufacturers can enhance their contributions to improve BIM’s effectiveness, proposing that coopetition practices—combining competition and cooperation—can positively influence these contributions, thereby enhancing the benefits of BIM. To explore this hypothesis, an Experimental Coopetition Network was implemented in the Portuguese ornamental stone (POS) sector, utilizing Industrial IoT technology to facilitate collaboration among selected companies. The study assessed the impact of coopetition practices on key performance indicators related to BIM, including on-time delivery, labor productivity, and CO₂ emissions. The findings demonstrate significant improvements in scheduling, operational efficiency, and environmental sustainability, validating the hypothesis that coopetition practices can enhance manufacturers’ contributions to BIM. These results suggest that coopetition practices contribute to better project outcomes, increased competitiveness, and sustainability within the construction industry. Despite the promising results, the study acknowledges limitations such as the scope of the sample size and observation periods, indicating areas for future research. This research contributes to the theoretical framework of coopetition, aligning with the United Nations Sustainable Development Goals (SDGs), and provides valuable insights for industry practitioners and policymakers seeking to implement more sustainable construction practices. Full article

In a rapidly evolving technological landscape, manufacturers are increasingly pressured to undertake digital transformation, with smart manufacturing serving as a crucial milestone in this process. This study investigates the key factors influencing the implementation of smart manufacturing from a supply chain perspective, employing the analytical hierarchy process (AHP) to analyze collected data from senior managers of manufacturing firms. The findings highlight several critical factors, including the commitment of senior executives, the recruitment of skilled professionals, interdepartmental collaboration, and financial support. Moreover, this study reveals differing priorities between large and small manufacturers: large firms emphasize the importance of the Industrial Internet of Things (IIoT), while smaller firms prioritize understanding end-consumer needs and product trends. This study emphasizes that smart manufacturing is not only for optimizing the operational efficiency of manufacturing firms but also for supporting sustainability efforts through more effective use of resources and reduced environmental impact of work processes. Full article

Titanium additive manufacturing using powder bed fusion technologies has seen notable growth since 2015, particularly in high-performance sectors such as aerospace, biomedical, and automotive industries. This study focuses on key areas like metallic powder manipulation, laser optimization, and process control, with selective laser melting emerging as the dominant technique over electron beam melting. Advancements in powder materials and laser systems have been crucial to improving the efficiency and quality of the process, particularly in enhancing microstructure and porosity control. The bibliometric analysis reveals significant global interest, driven mainly by collaborations among institutions in Germany, the United States, and China, where further international cooperation is required to scale titanium additive manufacturing. However, additional research is essential to address challenges in scalability, sustainability, and post-processing, thus expanding the applications of PBF technology across industries. In conclusion, titanium processing via powder bed fusion is poised to make substantial contributions to the future of manufacturing, provided current challenges are addressed through innovation and enhanced global collaboration. Full article

This study explores integrating Building Information Modeling (BIM) technology into risk management practices for construction projects, aiming to enhance project performance through improved risk identification, assessment, and mitigation. The research employs the Analytical Hierarchy Process (AHP) to prioritize BIM-based strategies across multiple risk management dimensions, including technical, financial, sustainability, and time management. The findings demonstrate that BIM-based financial strategies rank highest among BIM-driven risk management, followed by sustainability and time. In contrast, technical, operation, and maintenance capabilities have the lowest rank. Given the high priority of BIM financial strategies, they have been applied to conduct sensitivity analysis; the sensitivity analysis results demonstrate the dynamic nature of a BIM sub-criteria strategy in response to changes in the weight of financial considerations. As financial concerns diminish, the shift towards sustainability, health, safety, and time efficiency underscores the importance of a more balanced approach in BIM strategy prioritization. BIM-based risk management improves project outcomes by enabling real-time data-driven decision-making, enhancing stakeholder collaboration and optimizing resource use, cost control, and sustainability. This research contributes to theoretical and practical advancements in construction risk management, suggesting that BIM can be a transformative tool for optimizing project performance while addressing the complexities and uncertainties inherent in the construction industry. Full article

Environmental degradation and economic development have long been seen as incompatible, posing a pressing challenge for society. Government–business collaboration stands as an effective avenue for addressing environmental issues. This paper, using the 2007–2021 Low-Carbon City Pilot (LCCP) program in China as a quasi-natural experiment, explores the impact of governmental environmental regulations on corporate green innovation and examines the moderating role of government–business collusion. The findings indicate that the LCCP policy has effectively promoted corporate green technological innovation, with results remaining robust across various sensitivity tests. Heterogeneity analysis further reveals that the policy’s impact is more pronounced in the eastern regions, state-owned enterprises, and low-tech industries. Moreover, government–business collusion significantly undermines the benefits of green innovation, though this effect is partially alleviated when local government officials are replaced. Under the influence of government environmental regulation, green innovation fosters the sustainable development of enterprises. However, the formation of collusion between government and business diminishes the incentive for companies to take on environmental and social responsibilities. The study enriches the existing literature on environmental policy factors and offers both theoretical and practical insights for the government in formulating relevant environmental policies and promoting corporate green innovation. Full article

Ensuring safety at sea has become a primary focus of marine monitoring, driving the increasing adoption of ship detection technology in the maritime industry. Detecting small ship targets in SAR images presents challenges, as they occupy only a small portion of the image and exhibit subtle features, reducing detection efficiency. To address these challenges, we propose the HCA-RFLA algorithm for ship detection in SAR remote sensing. To better capture small targets, we design a hierarchical collaborative attention (HCA) mechanism that enhances feature representation by integrating multi-level features with contextual information. Additionally, due to the scarcity of positive samples for small targets under IoU and center sampling strategies, we propose a label assignment strategy based on Gaussian receptive fields, known as RFLA. RFLA assigns positive samples to small targets based on the Gaussian distribution between feature points and ground truth, increasing the model’s sensitivity to small samples. The HCA-RFLA was experimentally validated using the SSDD, HRSID, and SSD datasets. Compared to other state-of-the-art methods, HCA-RFLA improves detection accuracy by 6.2%, 4.4%, and 3.6%, respectively. These results demonstrate that HCA-RFLA outperforms existing algorithms in SAR remote sensing ship detection. Full article

The Clean Energy Technology Research Institute (CETRI) at the University of Regina, Canada, serves as a collaborative hub where a dynamic team of researchers, industry leaders, innovators, and educators come together to tackle the urgent challenges of climate change and the advancement of clean energy technologies. Specializing in low-carbon and carbon-free clean energy research, CETRI adopts a unique approach that encompasses feasibility studies, bench-scale and pilot-plant testing, and pre-commercial demonstrations, all consolidated under one roof. This holistic model distinguishes CETRI, fostering a diverse and inclusive environment for technical, scientific, and hands-on learning experiences. With a CAD 3.3 million pre-commercial carbon capture demonstration plant capable of capturing 1 tonne of CO₂ per day, and a feed-flexible hydrogen demonstration pilot plant producing 6 kg of hydrogen daily, CETRI emerges as a pivotal force in advancing innovative, reliable, and cost-competitive clean energy solutions, essential for a safe, prolific, and sustainable world. This paper provides a comprehensive overview of the diverse and impactful research carried out in the center, spanning various areas including decarbonization, zero-emission hydrogen technologies, carbon (CO₂) capture utilization and storage, the conversion of waste into renewable fuels and chemicals, and emerging technologies such as small modular nuclear reactors and microgrids. Full article

The automotive supply chain is one of the top eight value chains that cause 50% of global emissions. Despite its significance, limited literature has researched the role of insurance companies in addressing automotive supply chain emissions. This research explores strategies developed by insurance companies for addressing carbon emissions in the automotive supply chain in the UK. It employs a qualitative multiple case study approach and conducts in-depth analysis of main drivers, barriers, and strategies in four insurance companies in addressing automotive supply chain emissions. It finds that cost savings and competitive advantage, changing mindset, impending regulation, market changes, and increased connectedness are the main drivers. But further progress is slowed down by five main barriers: ‘the complexity of tracking and quantifying emissions’, ‘conflicts of interest in the supply chain’, ‘skill shortage’, ‘lack of accountability’, and ‘profit prioritisation’. To overcome this, the study establishes five main strategies for insurance companies to follow: ‘circular business model with green parts and repair-over-replace methodologies’, ‘supply chain collaboration’, ‘quantifying emissions and setting key performance indicators’, ‘higher weighting for ESG in tenders and policies’, and ‘education and awareness’. If followed correctly, businesses will be able to achieve ‘emission reductions’, ‘gain competitive advantage’, and ‘reduce costs in the supply chain’. Taking into account these findings and the academic literature, this study develops a framework for insurance companies to mitigate automotive supply chain emissions. This is one of the first papers to study carbon emissions in automotive supply chains from the perspective of the insurance industry. It provides practical implications for the insurance industry in developing carbon emission strategies in automotive supply chains. Full article

Understanding the spatial correlation of transportation carbon emissions and their influencing factors is significant in achieving an overall regional carbon emission reduction. This study analyzed the structure characteristics of the expressway carbon emission correlation network in Guangdong Province and examined its influencing factors with intercity expressway traffic flow data using social network analysis (SNA). The findings indicate that the correlation network of expressway carbon emissions in Guangdong Province exhibited a “core-edge” spatial pattern. The overall network demonstrated strong cohesion and stability, and a significant difference existed between the passenger vehicle and freight vehicle carbon emission networks. The positions and roles of different cities varied within the carbon emission network, with the Pearl River Delta (PRD) cities being in a dominant position in the carbon network. Cities such as Guangzhou, Foshan, and Dongguan play the role of “bridges” in the carbon network. The expansion of differences in GDP per capita, industrial structure, technological level, and transportation intensity facilitates the formation of a carbon emission network. At the same time, geographical distance between cities and policy factors inhibit them. This study provides references for developing regional collaborative carbon emission governance programs. Full article

As industries evolve towards greater digitalization, integrating Building Information Modeling (BIM) and digital twin technologies presents a unique opportunity to enhance sustainability in industrial infrastructure. This paper formulates a comprehensive set of principles aimed at guiding the sustainable integration of these technologies within the context of modern industrial facilities, often referred to as “Factories of the Future”. The principles are designed to address critical sustainability challenges, including minimizing environmental impact, optimizing resource efficiency, and ensuring long-term resilience. Through a detailed examination of lifecycle management, data interoperability, and collaborative stakeholder engagement, this work provides a strategic framework for leveraging digital technologies to achieve sustainability goals. The principles outlined in this paper not only promote greener industrial practices but also pave the way for innovation in the sustainable development of industrial infrastructure. This framework is intended to serve as a foundation for future research and practical application, supporting the global shift towards more sustainable industrial operations. Full article

The mismatch between supply and demand and inefficient supply in China’s agricultural product market is quite severe, making agricultural supply-side structural reform an important topic and task for rural economic work in China. The successful implementation of agricultural supply-side reform requires a comprehensive agricultural social service platform and system to support it. However, the current agricultural social service platform system in China faces issues such as a lack of coordination among service entities and poor information communication, making it difficult to meet the demands of supply-side reform. To address this issue, under the new circumstances of supply-side reform, this paper proposes the idea of reorganizing the agricultural social service platform and system through industrial chain collaboration theory, and applying “internet +” for technological reengineering of the agricultural social service platform system. Based on this, a new agricultural social service platform system architecture is constructed, which includes service entities, service platforms, service content, and operational models. The research findings provide guidance for agricultural product producers, distributors, sellers, and related service entities along the agricultural industry chain on how to use “internet +” for collaborative decision-making. This approach is beneficial for addressing the supply-demand imbalance and low resource allocation efficiency in China’s agricultural product market, thereby advancing the structural reform of China’s agricultural supply side. Full article

The Fourth Industrial Revolution (4IR) has ushered in a new era of technological advancements that are transforming industries worldwide. One such technology that is revolutionizing the construction industry is mechatronics, which has the propensity to enhance the operations, activities, productivity and efficiency of the sector’s activities. Despite the numerous advantages of mechatronic technologies, their successful implementation in the context of developing countries poses unique challenges and considerations. Therefore, this study seeks to identify and evaluate the critical success factors (CSFs) for mechatronics implementation in architecture, engineering, construction and operations (AECO) projects. Existing CSFs were extracted from extant studies, which helped formulate the questionnaire disseminated to 372 construction professionals in Nigeria, including architects, builders, quantity surveyors, and engineers (mechanical, civil, electrical). The methodology also employed exploratory factor analysis (EFA), which facilitated the identification of key themes within the data. Through this application, six clusters of CSFs were revealed: organizational factors, financial considerations, technological aspects, collaboration and knowledge sharing, regulatory and policy factors, and sustainability and environmental considerations. From a theoretical perspective, the identified clusters of critical success factors provide a comprehensive framework that encompasses various dimensions of successful mechatronics adoption in the Nigerian construction industry. This study advances scientific knowledge on CSFs for the adoption of mechatronic technologies in the Nigerian construction industry, providing a comprehensive understanding of the factors that drive successful implementation. For policymakers, this study’s findings will be invaluable in shaping supportive policies and strategies that foster the widespread adoption of mechatronics in the construction sector. Full article

While AI-driven automation can increase the performance and safety of systems, humans should not be replaced in safety-critical systems but should be integrated to collaborate and mitigate each other’s limitations. The current trend in Industry 5.0 is towards human-centric collaborative paradigms, with an emphasis on collaborative intelligence (CI) or Hybrid Intelligent Systems. In this survey, we search and review recent work that employs AI methods for collaborative intelligence applications, specifically those that focus on safety and safety-critical industries. We aim to contribute to the research landscape and industry by compiling and analyzing a range of scenarios where AI can be used to achieve more efficient human–machine interactions, improved collaboration, coordination, and safety. We define a domain-focused taxonomy to categorize the diverse CI solutions, based on the type of collaborative interaction between intelligent systems and humans, the AI paradigm used and the domain of the AI problem, while highlighting safety issues. We investigate 91 articles on CI research published between 2014 and 2023, providing insights into the trends, gaps, and techniques used, to guide recommendations for future research opportunities in the fast developing collaborative intelligence field. Full article