Search Results (199)

Leveraging artificial intelligence (AI)―a cutting-edge technological tool―to drive the new quality transformation of Chinese manufacturing is a crucial foundation for China’s steady advancement of the new real economy, as well as an inevitable requirement for China to align with contemporary economic and technological trends. This study constructs a multi-sectoral equilibrium model to theoretically analyze the focal points of the new quality transformation in Chinese manufacturing and the impact AI has on it, followed by corresponding empirical tests. The results indicate that (1) AI has a positive impact on the qualitative transformation of China’s manufacturing sector; a one-unit increase in a firm’s AI level leads to a 0.171-unit increase in the sector’s qualitative transformation level. (2) This impact exhibits heterogeneity at the firm, industry, and regional levels. At the firm level, the impact varies depending on firm size, digitalization level, operational performance, internal control strength, and governance quality. At the industry level, the impact varies depending on technology intensity, industrial structure, strategic importance, and green development level. At the regional level, heterogeneity is reflected in geographical location, natural resource endowments, and the degree of urban agglomeration. (3) Artificial intelligence promotes the new quality transformation of Chinese manufacturing through the following mechanisms: reducing time lag costs and transaction costs in market penetration mechanisms; enhancing the quality of cutting-edge factor combinations and key core technologies in advanced innovation mechanisms; and improving resource utilization and operational management efficiency in lean production mechanisms. Full article

This study examines the influences of various organizational performance factors on the application of Lean tools and the effects of Lean methodology implementation. Although Lean management has been widely studied, empirical evidence on the combined influence of internal organizational capabilities and external environmental pressures on Lean adoption and outcomes in transition economies remains limited. In particular, the relative importance of internal resources and competitive pressures in shaping Lean implementation results has not been sufficiently explored. Therefore, this study aims to analyze how different organizational and environmental factors influence both the application of Lean tools and the effects of Lean methodology implementation. The independent variables considered include: business performance, organizational culture, company size, technical infrastructure and resources, education and competence of employees, training for Lean methodology, management support, competitive pressure and motivation to reduce costs, degree of innovation in the company, the role of the Lean concept in strategic planning, years of company existence, and years of Lean tool implementation. The research was conducted among food industry companies in Serbia, and a total of 183 valid questionnaires were collected. The results indicate that the application of Lean tools is most strongly influenced by training for Lean methodology, followed by business performance and company size. In contrast, the effects of Lean methodology implementation are primarily affected by competitive pressure and motivation to reduce costs, as well as management support. Furthermore, the analysis shows that Lean application and Lean outcomes function as two distinct dimensions: companies may apply Lean tools without achieving significant effects if managerial support or competitive pressure is insufficient. Conversely, firms with strong competitive drivers and committed management achieve noticeably higher performance improvements even with moderate levels of Lean tool adoption. Overall, the findings suggest that the application of Lean tools largely depends on the company’s internal resources, such as employee knowledge and training, business strength, and scale of operations, while the success and outcomes of Lean implementation are more strongly driven by external competitive pressures and the degree of managerial understanding and support. By distinguishing between the determinants of Lean tool adoption and the determinants of Lean implementation outcomes, this study contributes to a clearer understanding of Lean effectiveness in the context of transition economies. Full article

Urban regeneration has traditionally focused on large-scale developments that aim at increasing the livability and vitality of disadvantaged areas. Alternative views of urban regeneration have emerged to challenge such a structural approach. These novel ideas reflect contextual changes in progressive and innovative Western countries that embrace the culture of experimentation, prefer sharing to ownership, and emphasize participation and inclusion as fundamental aspects of public governance. This article elaborates the idea of lean urban regeneration in the progressive welfare society context, with a special view of citizen and stakeholder involvement through inclusion, sharing, and co-creation. Empirical research utilizes mini cases of the largest cities in the growth triangle of Finland. This article identifies the manifestations of lean urban regeneration and discusses its preconditions and ability to tackle urban development challenges. The results emphasize the framing nature of inclusion, the underutilization of sharing, and the key role of co-creation in lean urban regeneration. A particular potential of lean interventions is based on co-creation as the core of multimodal or hybrid regenerative projects that are firmly anchored on economic inclusion. By utilizing the input of residents, entrepreneurs, and other local stakeholders, it is possible to open up a path to integrated high-leverage activities with a potential to alleviate structural urban problems. Full article

Small and medium-sized enterprises (SMEs) struggle to integrate Lean practices with sustainability due to high methodological complexity and the frequent neglect of the social dimension. This study develops the Simple, Sustainable, and Inclusive Lean Model (SSILM), a conceptual framework designed to bridge these gaps. The methodology involved a systematic meta-evaluation of 31 existing Lean–Sustainability models against 14 operational criteria tailored for SMEs. Findings reveal that current models lack social integration and practical scalability for resource-constrained environments. The proposed SSILM is structured in six phases, from characterization to analysis, prioritizing low-cost participatory tools and strategic innovation. This study contributes a theoretical bridge between operational efficiency and the Triple Bottom Line, specifically emphasizing the social pillar. As a conceptual paper, its primary limitation is the lack of empirical field testing, which establishes a clear roadmap for future longitudinal research in industrial contexts. Full article

Lean production philosophy and sustainability approach have become a critical framework for efficiency improvement, waste reduction, and promoting sustainable manufacturing practices. In the age of artificial intelligence (AI), there is a synergy, which has now found new dimensions, data-driven decision-making, predictive analytics, and operational agility. AI technologies promise to transform industrial processes by converging lean production and sustainability principles, a synergy explored in this paper. AI APIs enable the use of AI to improve resource utilization, reduce environmental pressure, and maintain economic growth inherent to all business sectors while also fostering social accountability. In this study, a robust regression model is employed to study the role of AI in moderating the lean practices and sustainability outcomes relationship, using a sample of 528 manufacturing firms. The results show that the contribution of AI technologies to economic, ecological, and social sustainability is effectively multiplied by that of lean production. This research offers a framework to help practitioners and policymakers optimize production systems in line with Sustainable Development Goals. Finally, the study delivers actionable recommendations for navigating skill gaps and cybersecurity risks that were identified. In sum, this paper contributes to the rapidly emerging conversation by providing empirical evidence on AI’s moderating role in the lean–sustainability relationship and offering a strategic framework for practitioners. Full article

Lean Construction has become a key strategy for improving productivity, reducing waste, and increasing efficiency in civil engineering projects. In parallel, advances in digital technologies have transformed the way engineering design and project planning processes are conceived and managed. However, there remains a limited systematic understanding of how emerging technologies support engineering design practices and influence the implementation and performance of Lean Construction in diverse civil engineering scenarios. This study presents a systematic literature review of 70 peer-reviewed articles published between 2019 and 2025, following the PRISMA 2020 guidelines. The selected studies were examined using a structured classification framework consisting of three analytical categories: Technologies and Tools, Construction Methods and Sustainability, and Production Philosophies and Management. From an engineering design perspective, this framework allows the identification of technological trends, design-support tools, and management strategies that influence the planning, modeling, and optimization of construction processes. The results show that digital technologies, such as Building Information Modeling (BIM), automation systems, Artificial Intelligence, and Industry 4.0 tools, play a significant role in supporting engineering design activities by improving project visualization, coordination, and decision-making during the design and planning stages. These technologies contribute to more integrated design processes aligned with Lean Construction principles. At the same time, the analysis reveals that the adoption of Lean Construction technologies varies depending on project characteristics, levels of digital maturity, and regional industry conditions. The main barriers identified in the literature include interoperability limitations, insufficient workforce training, and organizational resistance to technological change. Overall, the review provides a structured synthesis of recent research trends and highlights the technological and managerial factors that influence the successful integration of Lean Construction with engineering design practices in civil engineering. The findings contribute to bridging the gap between technological innovation, design methodologies, and Lean Construction implementation, offering insights for both researchers and practitioners seeking to improve efficiency, sustainability, and design performance in construction projects. Full article

Occupational Health and Safety systems, as well as physical Ergonomics, serve a common goal, which is to eliminate safety-related injuries within production systems. The analysis of potential hazards that could compromise the safety of operations’ employees assists in preventing a high rate of safety-related injuries. Safer processes result in a high output rate and, hence, a profitable business. Focusing on the accuracy of problem solving and failure prediction analysis on new processes could potentially result in zero safety-related injuries, good-quality products, cost reduction, and the elimination of delays within the processes. This research seeks to add more knowledge to the fields of Occupational Health and Safety systems and Total Productive Maintenance by combining lean manufacturing troubleshooting models with Ergonomic analysis, as well as Hazard Identification Risk Analysis, to predict future kaizen projects for businesses. The proposed upgrade to the problem-solving model was developed by evaluating and reviewing the impact of Ergonomic analysis on different production systems. It was found that Ergonomic analysis provides solutions for a more comfortable working environment; hence, the existing troubleshooting model was combined with an Ergonomic exercise. The proposed model is more beneficial to production systems. It could potentially result in zero safety-related injuries, high-quality products, more accurate problem analysis, and more innovation by enabling kaizen projects. The proposed model was applied in the electronics industry, where it resulted in drastic improvements. The old method, which was causing fatigue, was eliminated, and a new machine was designed and prototyped. The new machine assisted the company in this case study in reducing delays, eliminating defects, and reducing costs. Furthermore, the proposed troubleshooting model evaluated an impactful kaizen project, which was the introduction of new technologies that will eliminate the power-up stage. Full article

Data suggest that both pancreatic and intestinally produced glucagon-like peptide-1 (GLP-1) increases in response to inflammation. Here, we set out to determine the tissue-specific function of increased GLP-1 during inflammatory stimuli. Using our innovative mouse model of tissue-specific Gcg (the gene that encodes GLP-1) expression, we explored the function of GLP-1 under severe inflammatory conditions induced by lipopolysaccharide (LPS) administration in lean and obese mice. High-fat diet (HFD) increased the LPS-induced suppression of feeding and increased the plasma levels of pro-inflammatory cytokines and GLP-1. Both pancreatic and intestinal Gcg expression contribute to LPS-induced increases in GLP-1, but Gcg was not necessary for the glucoregulatory or suppressed feeding responses to LPS. While Gcg was not necessary for systemic cytokine increases with LPS in either chow- or HFD-fed mice, whole-body Gcg-null animals had increased macrophage accumulation and an increased expression of genes reflecting pro-inflammatory signaling in the pancreas. We then performed flow cytometry on the pancreas from mice expressing a fluorescent marker on the GLP-1 receptor (GLP-1R). In response to LPS, we found that pancreatic CD64+/CD11b+ macrophages expressed the GLP-1R. We conclude that under severe inflammatory conditions, pancreatic production of GLP-1 functions in an immunological rather than a metabolic role to directly regulate local macrophage accumulation. Full article

In light of the rapid adoption of text-to-image (T2I) tools in higher education, this study develops a stimulus–organism–response (S-O-R) model to explain the sustainable and responsible use intentions of text-to-image generative AI tools in higher education. Focusing on both university students and faculty, the model conceptualizes perceptions of ease of use, information quality, and ethical awareness as external stimuli; technology- and ethics-related anxiety as internal emotional states; and algorithmic trust, perceived risk, and sustainable use intention as behavioral evaluations and responses. Grounded in the Stimulus–Organism–Response (S–O–R) framework, we integrate the Technology Acceptance Model (TAM), Technology Threat Avoidance Theory (TTAT), and the DeLone–McLean (D&M) model to propose a layered mechanism, with personal innovativeness serving as a moderator. Utilizing 807 valid survey responses, we employed structural equation modeling and fuzzy-set qualitative comparative analysis. The results reveal that (1) the overall chain is supported: perceived ease of use, information quality, and ethical awareness primarily influence sustainable use intention indirectly through anxiety, trust, and risk; (2) although higher usability and quality do not alleviate anxiety, they coexist within a complex pattern of trust amid anxiety; and (3) high levels of personal innovativeness diminish the linear effects of trust and risk on intention. Configurational evidence further indicates multiple pathways leading to high sustainable intention, whereas low intention is typically characterized by uniformly low perceptions, emotions, evaluations, and innovativeness. By framing sustainable adoption through a coupled trust–risk–anxiety lens, this study extends the understanding of generative AI use in education and offers actionable implications for promoting responsible and sustainable practices in universities. Full article

This study examines how leadership styles and organizational culture influence the eighth Lean waste—unused human potential—in contemporary organizations operating within the context of artificial intelligence (AI) adoption. Using quantitative research design and a sample of 200 employees from public and private sectors, the results show that leadership styles and cultural dimensions significantly predict five categories of human-potential losses: creativity, innovation, motivation, communication, and role clarity. Autocratic and task-oriented leadership styles exhibit positive associations with these losses, while democratic and people-oriented leadership exhibit predominantly negative associations. Organizational culture dimensions, particularly involvement, adaptability, and mission, strongly reduce human-potential losses. Although AI is not measured as an empirical variable, it is considered as a contextual factor that heightens the importance of human-centered leadership and adaptive cultures. The study contributes to Lean management research by integrating behavioral, cultural, and contemporary technological perspectives and highlights practical implications for managing human potential in an evolving technological environment. Full article

Obesity, type 2 diabetes (T2D), and insulin resistance are pervasive metabolic disorders marked by chronic low-grade inflammation and systemic metabolic disorders. The emerging field of immunometabolism highlights how interactions between immune processes and metabolic pathways in adipose tissue, liver, muscle, and pancreatic islets contribute to disease pathogenesis. Lipid dysregulation plays a central role in these processes, with distinct lipid molecules identified in obese patients as compared to lean patients that correlate with insulin resistance, inflammation, and vascular dysfunction. This Special Issue compiles a multidisciplinary body of research aimed at elucidating molecular mechanisms, identifying novel biomarkers, and exploring innovative therapeutic strategies. Key contributions include studies on omega-3 long-chain polyunsaturated fatty acids (LCPUFAs) and their differential associations with neurocognitive development; the potential of beta-defensin 2 as a biomarker linking gut-derived inflammation and metabolic dysfunction; and the promotion of adipocyte browning by Carnosic acid via AMPK activation and GSK3β inhibition. Additionally, reviews of phytochemicals underscore their multisystem therapeutic potential, while investigations into sodium–glucose cotransporter-2 (SGLT2) inhibitors suggest possible metabolic and neuroprotective benefits beyond glucose control. Maternal lipid metabolism during pregnancy and its impact on maternal fetal health further emphasize the clinical complexity of lipid dysregulation. Despite promising insights, significant gaps remain regarding causality versus correlation in lipid biomarkers, standardization of analytical methodologies, tissue heterogeneity, and unintended effects of metabolic interventions. Collectively, these studies underscore the necessity of integrative, mechanism-driven research to bridge fundamental biology with translational and clinical applications, ultimately advancing precision therapies for metabolic diseases. Full article

Despite significant research interest, the understanding of how to systematically implement Lean practices in supply chains remains limited. Therefore, this study analyzes the impact of blockchain technology on implementing Lean principles within supply chain networks. A theoretical model was developed based on a comprehensive literature review, utilizing innovation diffusion theory, agency theory, and transaction cost economics. The LDA topic modeling, based on big data from the past decade, was employed to explore key areas and essential industry practices related to blockchain technology. By cross-validating big data analysis and survey results, we also developed reliable metrics that can be used to study blockchain utilization in SCM. The hypotheses were empirically tested using survey data from 219 US enterprises that have adopted blockchain technology. The empirical results revealed that blockchain adoption significantly improved Lean management practices within supply chain networks. Furthermore, research has shown that blockchain can significantly enhance operational performance, including cost reduction, quality improvement, delivery capacity, and greater flexibility. These compelling results suggest that blockchain has the potential to serve as a powerful platform for systematically integrating and orchestrating Lean management practices across the entire supply chain network, thereby achieving operational excellence. An in-depth discussion of the study’s practical implications and theoretical contributions is presented. Full article

Based on panel data from 274 prefecture-level cities in China (2011–2022), this study employs a peer effects model to examine three questions: whether peer effects exist in sustainable rural development, what mechanisms underlie them, and which regions are imitated. It thereby offers a new perspective on the endogenous drivers of rural development. The main findings are as follows. Baseline regression results confirm a significant positive peer effect on rural sustainable development. This result remains robust after a series of tests addressing endogeneity and robustness, including the replacement of explanatory variables, data indentation, exclusion of provincial capitals, placebo tests, and instrumental variable estimation. Heterogeneity analysis reveals that central and western regions are more inclined to learn from other cities in the process of sustainable rural development, whereas the eastern region leans more toward innovation. After the Rural Revitalization Strategy was introduced in 2017, regions have actively explored new rural development models, leading to a decline in the peer effects coefficient compared to the pre-2017 period. Mechanism analysis indicates that both learning-based imitation and competitive imitation serve as channels for peer effects in rural sustainable development. A region’s own development experience does not suppress peer effects. Economically more developed regions are more likely to become imitation targets. Moreover, performance pressure on local officials and the degree of competition among prefecture-level cities strengthen the peer effects. After reclassifying peer groups based on economic structure and geographical location, results show that in the process of rural sustainable development, local governments primarily learn from other regions within the same province that share similar economic structures and are geographically proximate. Based on these findings, this paper proposes differentiated policy recommendations to support sustainable rural development. Full article

This paper addresses the critical problem of stabilizing an inherently unstable bicycle robot at low or zero speeds using advanced control strategies. The key objective is to develop a feedback controller that actively operates a handlebar, as well as a reaction wheel, maintaining balance while keeping performance indices low, including energy consumption. It is the energy consumption that makes the platform attractive for the users by extending the time of operation, not only due to the actions connected to motor design and battery design, but to the control system itself. To design and verify the control law that enables stabilization, and reduces energy consumption, bicycle dynamics and controllers based on linear quadratic regulator (LQR) techniques are designed, along with their robustified variants accounting for actuator failures and model uncertainties, and an innovative event-triggered control (ETC) scheme to reduce control updates and energy use. Simulations demonstrate effective stabilization from various initial lean angles under realistic conditions, with robustness notably improved at zero speed, where balancing is most challenging. Extending control to include both reaction wheel and handlebar actuation enhances dynamic maneuverability and energy efficiency. The event-triggered approach significantly lowers computational and actuator energy demands by updating controls only when needed, reducing mechanical wear. This research contributes to electromobility by improving the control and energy efficiency of personal transport devices like electric bicycles and autonomous bicycles, which rely on stable balancing mechanisms for safety and user comfort. The findings support future experimental validation and IoT implementation, pushing forward controlled, energy-conscious stabilization for emerging personal electromobility solutions. Full article

How individuals and organizations interface with the digital economy has been largely influenced by transformations ushered in on the global financial map by the rapidly expanding Financial Technology (FinTech). This paper seeks to shed light on the successes of FinTech, namely on how it contributed to sustainability through financial inclusion, reduction in reliance on cash and the promotion of an innovation-driven economy known for being paperless. Based on contributions from students at Taif University in Saudi Arabia, determinants of FinTech adoption intentions are analyzed using data from n = 544. Our study focuses on evaluating the effects of financial, technical and external factors on adoption behavior by using a two-prong approach: first, we use the DeLone and McLean IS Success Model; then we employ a Second-Order Construct using Structural Equation Modelling (SEM). The results indicated that the strongest effects on attitudes stem from technical factors—information, system and service quality. Additionally, they also show that adoption intention is considerably shaped by financial as well as external dimensions. The Saudi Vision 2030 has set national goals of digital transformation, financial inclusion and human capital empowerment. This study provides a modest contribution to those goals by fostering FinTech adoption among the youth. Furthermore, its findings also offer educators, policymakers and Fintech providers a platform to enhance literacy, strengthen trust and develop sustainable digital finance ecosystems in line with the Kingdom’s Vision 2030 objectives. Full article