Search Results (1,262)

Artificial intelligence (AI), a transformative force, has revolutionised various aspects of human life and business operations. This has led to a drastic mutation of the career landscape, embedded with vast opportunities as well as challenges, particularly concerning career sustainability (CS). Despite myriad studies on CS, the paradoxical interplay of AI and CS remains underexplored, particularly for expatriates (expats). To address the aforementioned gap, our study incorporates an affordance perspective (AFP), positioning AI as an object and CS as a user context. Specifically, this study investigates whether AI facilitates the orchestration of an enhanced sustainable career within the boundary conditions of knowledge sharing (KS), encompassing both tacit and explicit knowledge pertinent to AI, cultivated through managerial initiatives and employee-driven activities. The study conducted a quantitative survey among 490 expats working in AI-integrated environments in China. The results reveal a curvilinear (U-shaped) relationship between AI and CS, where AI affordance at a moderate level enhances career adaptability and skill development. However, digital affordances become complex beyond a certain threshold, creating several career concerns, such as job insecurity and role ambiguity. Furthermore, the moderating effect of tacit and explicit KS mitigates numerous career disruptions while fostering long-term career growth. The study framed AI as both a tool and a collaborator that illuminates the importance of AI–human intelligence (AI–HI) synergy and knowledge augmentation in navigating digital transitions. Moreover, implications for international career development and human-oriented digital transformation are also discussed. Full article

Strengthening their supply chain resilience constitutes a strategic priority for Chinese enterprises to respond to evolving globalization patterns and sustain long-term competitiveness in an increasingly sustainability-oriented market. This research systematically measures enterprise supply chain resilience by analyzing panel data from Chinese listed firms (2010–2022) through the tri-dimensional constructs of resistance capacity, recovery resilience, and adaptive creativity. Regression analyses demonstrate that digital transformation significantly improves enterprise supply chain resilience, exhibiting dual-threshold characteristics in nonlinear relationships. Mediation tests reveal that information sharing and resource integration capabilities serve as the critical transmission channels. Digital transformation demonstrates strong predictive validity for both the resistance capacity and adaptive creativity of supply chains. The seemingly paradoxical findings on enterprise operational efficiency highlight the need for a more layered and dynamic understanding of its underlying mechanisms. The positive impact of digital transformation on supply chain resilience demonstrates heterogeneity across state-owned versus non-state-owned enterprises, regions, and industry types. The findings offer actionable insights for orchestrating digital transformation initiatives and designing tiered supply chain resilience frameworks that support enterprises’ sustainability goals. Full article

Carpathian mountain grasslands are increasingly affected by management intensification and climatic variability, with consequences for species composition and ecosystem functioning. This study assessed the long-term effects of a mineral fertilization gradient and interannual climatic variability on indicator species dynamics and biomass production in a semi-natural high-nature-value (HNV) grassland in the Apuseni Mountains, based on a 17-year field experiment. Increasing fertilization intensity promoted a clear shift from species-rich oligotrophic communities toward simplified mesotrophic and eutrophic grassland types, accompanied by a decline in indicator species richness and the increasing dominance of competitive grasses. Biomass production increased consistently along the fertilization gradient. Climate-driven effects were assessed using unfertilized control plots, allowing management effects to be disentangled from interannual climatic variability. Variations in temperature and precipitation influenced floristic composition and productivity across the years, highlighting the sensitivity of mountain grasslands to short-term climatic fluctuations. Multivariate analyses revealed increasing vegetation homogenization under high fertilization and distinct year-to-year shifts in species composition under unfertilized conditions. These results emphasize the vulnerability of Carpathian HNV grasslands to both nutrient enrichment and climatic variability, and underline the need for climate-adaptive, biodiversity-oriented management strategies. Full article

China has experienced a population decline since 2022, and its total fertility rate has dropped to about 1.0 in 2025. This is despite the lifting of the one-child policy in 2015 and the pivot to the two-child policy and three-child policy in, respectively, 2016 and 2021. Based on a review of recent research, this paper provides an interpretation that the continued fertility decline reflects a perfect storm of socioeconomic and demographic processes, long-term effects of the one-child policy, and unprecedented social changes in Chinese society. Socioeconomic and demographic changes since the 1950s prepared the ground for the “late, sparse, few” policy, resulting in a sharp fertility decline in the 1970s. While the one-child policy that followed did not result in a fertility decline in the 1980s, its effects appear to be long-lasting, including concentrated investment by the “inverted family” in the only child that drives up society-wide childrearing costs. Significant improvement in women’s educational attainment, individualistic orientation that prioritizes personal goals, increased diversity in family structure, such as one-person households, and changing views about getting married and having children have all contributed to continued downward pressure on fertility. These findings hint at the relevance of the concept of the second demographic transition for China and suggest that policy is only effective if it is aligned with what people want. Full article

This study addresses the limited understanding of how build orientation and aggressive environments jointly affect the mechanical reliability of L-PBF 316L stainless steel. Specimens were fabricated in vertical, edge, and flat orientations and exposed for 360 h to 1 M H₂SO₄, 3.5 wt.% NaCl, and dry air oxidation at 800 °C. Tensile tests and microstructural analyses revealed strong anisotropy: edge and flat builds showed higher tensile and yield strength, while vertical builds exhibited greater ductility. Aqueous environments caused surface degradation and moderate strength loss, most severe in vertical samples. High-temperature oxidation induced σ-phase precipitation, increasing tensile strength (~20%) but reducing ductility and yield strength. These findings highlight the critical role of building orientation and service conditions in ensuring long-term performance of L-PBF 316L stainless steel. Full article

Hot-fluid injection in thermal-enhanced oil recovery (thermal-EOR, TEOR) imposes temperature-driven volumetric strains that can substantially alter in situ stresses, fracture geometry, and wellbore/reservoir integrity, yet existing TEOR modeling has not fully captured coupled thermo-poroelastic (thermo-hydro-mechanical) effects on fracture aperture, fracture-tip behavior, and stress rotation within a displacement discontinuity method (DDM) framework. This study aims to examine the influence of sustained hot-fluid injection on stress redistribution, hydraulic-fracture deformation, and fracture stability in thermal-EOR by accounting for coupled thermal, hydraulic, and mechanical interactions. This study develops a fully coupled thermo-poroelastic DDM formulation in which fracture-surface normal and shear displacement discontinuities, together with fluid and heat influx, act as boundary sources to compute time-dependent stresses, pore pressure, and temperature, while internal fracture fluid flow (Poiseuille-based volume balance), heat transport (conduction–advection with rock exchange), and mixed-mode propagation criteria are included. A representative scenario considers an initially isothermal hydraulic fracture grown to 32 m, followed by 12 months of hot-fluid injection, with temperature contrasts of ΔT = 0–100 °C and reduced pumping rate. Results show that the hydraulic-fracture aperture increases under isothermal and modest heating (ΔT = 25 °C) and remains nearly stable near ΔT = 50 °C, but progressively narrows for ΔT = 75–100 °C despite continued injection, indicating potential injectivity decline driven by thermally induced compressive stresses. Hot injection also tightens fracture tips, restricting unintended propagation, and produces pronounced near-fracture stress amplification and re-orientation: minimum principal stress increases by 6 MPa for ΔT = 50 °C and 10 MPa for ΔT = 100 °C, with principal-stress rotation reaching 70–90° in regions adjacent to the fracture plane and with markedly elevated shear stresses that may promote natural-fracture activation. These findings show that temperature effects can directly influence injectivity, fracture containment, and the risk of unintended fracture or natural-fracture activation, underscoring the importance of temperature-aware geomechanical planning and injection-strategy design in field operations. Incorporating these effects into project design can help operators anticipate injectivity decline, improve fracture containment, and reduce geomechanical uncertainty during long-term hot-fluid injection. Full article

Providing effective post-disaster housing remains a globally complex challenge shaped by interrelated constraints, including environmental sustainability, socio-cultural compatibility, logistical capacity, and economic feasibility. Contemporary responses therefore require housing solutions that extend beyond rapid deployment to incorporate flexibility, adaptability, and long-term spatial transformation. In this context, this study advances a design-oriented, computational framework that positions parametric design at the core of post-disaster housing production within the broader digital transformation of the construction sector. The research proposes an adaptive parametric–modular housing system in which standardized architectural units are governed by a rule-based aggregation logic capable of generating context-responsive spatial configurations across multiple scales and typologies. The methodology integrates a qualitative synthesis of global post-disaster housing literature with a quantitative computational workflow developed in Grasshopper for Rhinoceros 3D (version 8). Algorithmic scripting defines a standardized spatial grid and parametrically regulates key building components structural systems, façade assemblies, and site-specific environmental parameters, enabling real-time configuration, customization, and optimization of housing units in response to diverse user needs and varying climatic, social, and economic conditions while maintaining constructability. The applicability of the framework is examined through a case study of the Düzce Permanent Housing context, where limitations of existing post-disaster stock, such as spatial rigidity, restricted growth capacity, and fragmented public-space integration, are contrasted with alternative settlement scenarios generated by the proposed system. The findings demonstrate that the framework supports multi-scalar and multi-typological reconstruction, extending beyond individual dwellings to include public, service, and open-space components. Overall, the study contributes a transferable computational methodology that integrates modular standardization with configurational diversity and user-driven adaptability, offering a sustainable pathway for transforming temporary post-disaster shelters into permanent, resilient, and socially integrated community assets. Full article

To identify the emission reduction potential and policy synergies of Tokyo’s road passenger and urban road freight transport under the “carbon neutrality target,” this paper constructs an assessment framework for megacities. First, based on macroeconomic socioeconomic variables (population, GDP, road length, and employment), regression equations are used to predict traffic turnover for different modes of transport from 2021 to 2050. Then, the prediction results are imported into the LEAP (Long-range Energy Alternatives Planning) model. By adjusting three policy levers—vehicle technology substitution (ZEV: EV/FCEV), energy intensity improvement, and upstream electricity and hydrogen supply decarbonization—a “single-factor vs. multi-factor (policy synergy)” scenario matrix is designed for comparison. The results show that the emission reduction potential of a single measure is limited; upstream decarbonization yields the greatest independent emission reduction effect, while the emission reduction effect of deploying zero-emission vehicles and improving energy efficiency alone is small. In the most ambitious composite scenario, emissions will decrease by approximately 83% by 2050 compared to the baseline scenario, with cumulative emissions decreasing by over 35%. Emissions from rail and taxis will approach zero, while buses and freight will remain the primary residual sources. This indicates that achieving net zero emissions in the transportation sector requires not only accelerated ZEV penetration but also the simultaneous decarbonization of electricity and hydrogen, as well as policy timing design oriented towards fleet replacement cycles. The integrated modeling and scenario analysis presented in this paper provide quantifiable evidence for the formulation of a medium- to long-term emissions reduction roadmap and the optimization of policy mix in Tokyo’s transportation sector. Full article

This study examines how Green Human Resource Management (GHRM) is linked to sustainable organizational performance, encompassing environmental, economic, and social outcomes through the capability-building mechanisms of green innovation (GI) and green organizational culture (GOCL) in emerging manufacturing systems. Drawing on the Resource-Based View and capability-based sustainability perspectives, GHRM is conceptualized as a strategic organizational capability that enables firms in developing economies to beyond short-term regulatory compliance toward measurable and integrated sustainability performance outcomes. Survey data were collected from 446 managerial and technical respondents in Ethiopia’s garment and textile industrial parks, one of Africa’s fastest-growing industrial sectors facing significant sustainability challenges. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with bootstrapping-based mediation analysis, the results show that GHRM is positively associated with sustainable organizational performance, with GI and GOCL operating as key mediating mechanisms that translate HR-related practices into measurable sustainability outcomes. The findings highlight the role of GHRM in strengthening firms’ adaptive and developmental sustainability capabilities by fostering pro-sustainability mindsets and innovation-oriented behaviors, which are particularly critical in resource-constrained and weak-institutional contexts. The study contributes to sustainability and management literature by explicitly linking Green HRM to triple-bottom-line performance through a capability-building framework and by providing rare firm-level empirical evidence from a low-income emerging economy. Practically, the results provide guidance for managers and policy makers to design, monitor, and evaluate HRM systems that intentionally cultivate human, cultural, and innovative capabilities to support long-term organizational sustainability transitions. Full article

Mobility-as-a-Service (MaaS) has emerged as a sustainable solution that integrates multiple transport services through digital platforms. Across different cities, MaaS development exhibits variation in terms of economic support, infrastructure capacity, service integration level, and long-term sustainability orientation. The complexity of multistakeholder interactions and functional components in MaaS ecosystems calls for a more comprehensive performance evaluation framework. To address this, this study proposes a holistic four-dimensional indicator system covering economic, infrastructure, integration and sustainability aspects. To address the hybrid uncertainties arising from the heterogeneous information aggregated by the proposed framework, encompassing both quantitative statistics and qualitative expert judgements, a novel rough–fuzzy best–worst method (BWM) and rough–fuzzy data envelopment analysis (DEA) approach is developed. The empirical application to six representative core cities in China reveals that high performance in “Integration” and “Economic” dimensions plays a pivotal role in determining overall MaaS performance, and coordinated enhancement across dimensions is also important. Comparative and sensitivity analyses validate the framework’s robustness, offering policymakers a reliable tool for benchmarking MaaS maturity. Full article

Firms globally are transforming digitally to enhance performance through building differentiated organizational capabilities within their digital ecosystem to maximize value. Drawing from the dynamic capability theory, this study aims to investigate the sources of sustainable competitive advantage, based on data from the UAE, by examining the impact of strategic orientations on firms’ survival through integrated strategic capabilities, adaptive marketing capability, and market ambidexterity. The choice of the UAE was based on two rational reasons. First, the adoption of new technologies is excelling in the UAE’s competitive environment especially AI, cloud, and data solutions across services industries, e.g., ICT, Telecom, Aviation, etc. Second, the government drives the digital economy to enhance the country’s positioning globally. Following a quantitative approach with a sample size of 185 service firms operating in the UAE, the study identifies how strategic orientations enable service firms’ long-term survival. Moreover, it assesses the moderating role of digital transformation between strategic orientations and sustainable competitive advantage through integrated strategic capabilities. Thus, it provides a better understanding of the dynamic capabilities of firms transforming digitally. The study revealed that strategic orientations positively enable the development of integrated strategic capabilities. The latter mediate significantly between strategic orientations and sustainable competitive advantage. It confirms that digital transformation is strengthening the relationship between strategic orientations and sustainable competitive advantage through the integrated strategic capabilities. The study contributes to evolving new forms of integrated strategic capabilities as sources for sustainable competitive advantage. It confirms the adaptive marketing capability and market ambidexterity integration and thus enriches the dynamic capability theory and ambidexterity theory body of knowledge. Full article

As global sustainable development progresses and the United Nations Sustainable Development Goals (SDGs) gain increasing prominence, pharmaceutical manufacturing firms face mounting challenges in implementing environmental, social, and governance (ESG) practices; these include high environmental compliance costs, limited drug accessibility, and governance inefficiencies. Patient capital, characterized by long investment horizons and high tolerance for risk, is well aligned with the long-term nature of ESG-oriented activities in this industry. Using a sample of pharmaceutical manufacturing companies listed on the Shanghai and Shenzhen A-share markets from 2015 to 2024, this study systematically examines the impact of patient capital on corporate ESG performance and explores the underlying mechanisms. The empirical results show that patient capital significantly improves ESG performance among pharmaceutical manufacturing firms. These findings remain robust across a series of robustness checks, including alternative variable measurements, sample adjustments, propensity score matching, instrumental variable estimation, and changes in the sample period. Further analysis reveals that patient capital enhances ESG performance through two primary channels: alleviating financing constraints and increasing R&D investment intensity. By focusing on the pharmaceutical manufacturing industry, this study extends the literature on patient capital to a highly regulated and socially sensitive sector, providing empirical evidence on how long-term, value-oriented capital can support sustainable development and improve ESG performance in industries with strong public welfare attributes. Full article

Mechanical loading generated during physical activity and exercise is a fundamental determinant of musculoskeletal development, adaptation, and regeneration. Exercise-based mechanotherapy, encompassing structured movement, resistance training, stretching, and device-assisted loading, has evolved from empirical rehabilitation toward mechanism-driven and precision-oriented therapeutic strategies. At the macroscopic level, biomechanical principles governing load distribution, stress–strain relationships, and tissue-specific adaptation provide the physiological basis for exercise-induced tissue remodeling. At the molecular level, mechanical cues are transduced into biochemical signals through conserved mechanotransduction pathways, including integrin–FAK–RhoA/ROCK signaling, mechanosensitive ion channels such as Piezo, YAP/TAZ-mediated transcriptional regulation, and cytoskeleton–nucleoskeleton coupling. These mechanisms orchestrate extracellular matrix (ECM) remodeling, cellular metabolism, and regenerative responses across bone, cartilage, muscle, and tendon. Recent advances in mechanotherapy leverage these biological insights to promote musculoskeletal tissue repair and regeneration, while emerging engineering innovations, including mechanoresponsive biomaterials, 4D-printed dynamic scaffolds, and artificial intelligence-enabled wearable systems, enable mechanical loading to be quantified, programmable, and increasingly standardized for individualized application. Together, these developments position exercise-informed precision mechanotherapy as a central strategy for prescription-based regenerative rehabilitation and long-term musculoskeletal health. Full article

This study investigates how strategic foresight can enhance FinTech governance and policy resilience in emerging economies, using Kuwait as an illustrative case. It aims to identify which foresight interventions should be prioritized across alternative futures to strengthen innovation, security, and institutional adaptability within the digital finance ecosystem. A scenario-based Multi-Criteria Decision Analysis (MCDA) framework is applied, combining the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Expert evaluations were conducted to assess five foresight interventions against eight policy and performance criteria across three plausible scenarios: Optimistic Growth, Status Quo, and Crisis and Contraction. Sensitivity analyses were performed to validate the stability of intervention rankings. The results reveal distinct priorities under each scenario: SME-oriented digital finance platforms and talent development dominate under growth and stability, while cybersecurity investment becomes paramount during crisis conditions. Regulatory fast-tracking maintains a consistent, moderate influence across all contexts. These outcomes underscore the need for adaptive, context-sensitive policy design that accommodates uncertainty. The framework provides policymakers with a structured approach to align FinTech strategies with long-term national visions such as Kuwait’s Vision 2035, while offering transferable insights for other emerging economies. The study’s originality lies in integrating strategic foresight and MCDA for FinTech governance—a methodological and practical contribution to foresight-informed policymaking. Full article

The island of Gran Canaria (Spain) has undergone a significant transformation in wildfire dynamics over the past two decades, characterized by a decline in wildfire frequency but a marked increase in the severity and spatial impact of extreme events, particularly within the wildland–urban interface (WUI). This study analyzes wildfire activity between 2000 and 2020 using official datasets and statistical trend analyses, incorporating robust severity indicators and measures of burned area concentration. Results show a statistically significant decreasing trend in the number of wildfires, while burned area is extremely concentrated in a small number of high-intensity events, with four large wildfires accounting for more than 97% of the total affected area. Climatic influences on wildfire activity were assessed through the analysis of long-term meteorological indicators, focusing on trends in extreme heat days and precipitation as proxies for thermal stress and fuel moisture availability. The results indicate a substantial modification of the background climatic framework under which wildfires develop, although no direct causal relationships are inferred. In parallel, territorial processes—such as rural abandonment, increased fuel continuity, and the expansion of dispersed housing beyond consolidated settlements—act as key amplifiers of wildfire risk. Overall, the findings highlight a transition from emergency-oriented fire suppression toward resilience-based wildfire management, emphasizing the need to integrate climate adaptation, territorial planning, and stricter land-use regulation in WUI areas. Full article