Search Results (156)

This study ground in the Innovation Diffusion Theory (IDT), explores the value of digital twin technology in cross-border logistics risk management. Using structural equation modeling, it examines how five innovation characteristics of digital twins—relative advantage, compatibility, complexity, trialability, and observability—influence risk management capabilities, specifically robustness and resilience, within cross-border logistics systems. The findings reveal that relative advantage, compatibility, trialability, and observability significantly enhance both robustness and resilience, while complexity does not show a significant negative impact. Furthermore, the study confirms that improvements in risk management capabilities contribute positively to competitive performance. This research not only enriches the theoretical understanding of digital twin applications in cross-border logistics but also offers valuable insights for practical implementation by enterprises. Full article

In today’s competitive environment of online service industries, particularly e-commerce, meeting consumer expectations is essential for service providers to ensure service quality. However, service failures are unavoidable, leading to unfavorable consequences for businesses. Understanding the mechanisms for customer recovery after negative service experiences is crucial. Using cognitive–emotional personality systems theory and benign violation theory, this study constructed a theoretical model. A total of 351 samples were collected through a situational simulation experiment for a linear regression analysis. A self-mocking response strategy positively influenced brand trust through perceived brand authenticity regarding the dimensions of credibility, integrity, and symbolism. Simultaneously, brand trust was identified as a key driver of post-recovery satisfaction. This study proposes a chain mediation model, which incorporates perceived authenticity and brand trust, to fully comprehend the mechanisms underlying consumers’ satisfaction after service recovery. Our findings provide empirical evidence for the effects of self-mockery on post-recovery satisfaction, as well as suggestions for marketers seeking efficient means to meet consumers’ emotional and cognitive demands during service recovery situations. Full article

A reasonable water price for interbasin water transfer projects (IWTPs) is vital for solving the problem of unequal water use among different water users caused by different water source supply prices, promoting external water transfer consumption, and ensuring the stable and equitable project operation. However, the formulation of the water price is influenced by many factors, and it is necessary to identify the key factors and their interactions in the water prices formulation for IWTPs. In this study, we identified 15 factors that affect it. This paper used the fuzzy decision-making trial and evaluation laboratory (DEMATEL) to analyze the causal relationships and importance levels among the influencing factors. A four-level hierarchical structural model was established using an interpretive structural model (ISM), which intuitively displayed the hierarchical structure and pathways of each factor. The role of each influencing factor was determined by using MICMAC. Finally, the grey relational analysis method was used to identify the top five key factors: the socioeconomic development level, diversification of water resources, water demand of water users, cost of the project’s water supply, and national policies and regulations. Strategies to improve the formulation of water prices have also been proposed. The results show that the top five factors influencing the water price for IWTPs are the socio-economic development level, diversification of water resources, water demand of water users, cost of the project’s water supply, and national policies and regulations. The water price should be formulated based on the water resource cost, supply–demand relationships of water resources, and policy objectives to ensure scientific and reasonable cost allocation and differentiated pricing. For water-transfer projects with strong public welfare, the government may lower water prices through financial subsidies to alleviate the burden on water users. Full article

Soil literacy, defined as the combination of attitudes, behaviours, and competencies necessary to make informed decisions that promote soil health, is increasingly recognised as a crucial element for sustainable development. This article presents the outcomes of the Soil Literacy Think Tank established under the Soils for Europe (SOLO) project, which aims to identify research and innovation knowledge gaps to strengthen soil literacy in Europe. Drawing on literature reviews, stakeholder engagement, and interdisciplinary dialogue, the paper highlights 18 prioritised knowledge gaps across different topics. These include a lack of integrated pedagogical strategies, limited outreach to specific social groups, and underdeveloped communication methods linking soil knowledge to stewardship actions. The article proposes adaptive and inclusive approaches to soil education that respect multiple knowledge systems and values and emphasises the importance of embedding soil literacy into sustainability agendas and governance processes. By addressing these challenges, the paper contributes to broader efforts supporting the EU Soil Mission and the goals of World Soil Day by promoting public awareness, citizen engagement, and responsible soil care. Full article

Against the backdrop of the booming digital economy, innovation has emerged as the core driving force for enterprise development, with employees’ innovative capabilities serving as a key competitive advantage for innovative enterprises. Adopting grounded theory as the methodological framework, we obtain multi-source data to investigate the factors influencing employees’ innovative capabilities and their underlying mechanisms. Furthermore, we develop a theoretical model elucidating the formation mechanism of employees’ innovative capabilities in human–machine collaboration contexts, identifying four core dimensions—innovation drivers, human–AI collaboration patterns, knowledge conversion pathways, and technological breakthroughs—that dominantly shape these capabilities. Thus, we reveal that the formation of innovative capabilities constitutes a dynamic interplay of technology empowerment, cognitive restructuring, and collaborative reinforcement and demonstrate its spiral progression characterized by “triggering, collaboration, and iteration”. This research not only contributes to academic discourse but also offers actionable theoretical and practical insights for innovative enterprises to enhance employees’ innovative capabilities, thereby fostering sustainable development in global competition. Full article

Light pollution is a rapidly growing environmental challenge, with the global brightness of the night sky increasing by an average of 9.6% per year. This study assessed the ecological impact of artificial light at night (ALAN) on protected areas in Poland, including all 23 national and 125 landscape parks, from 2012 to 2023. Based on VIIRS satellite radiance data and modelled sky surface brightness (Sa), we developed and applied the Ecological Light Pollution (ELP) scale, which classifies areas into four classes of ecological impact: strong (ELP-A), pronounced (ELP-B), noticeable (ELP-C), and weak or none (ELP-D). The analysis revealed that 38.5% of protected areas are affected by artificial skyglow at levels classified as ELP-B or ELP-C. Under cloudy conditions, which intensify light pollution effects, 22% of national parks and 41.8% of landscape parks fell into these classes. Notably, Wielkopolski National Park exhibited the most pronounced impact (ELP-B) even under clear skies, primarily due to its proximity to the Poznań metropolitan area. In contrast, Bieszczadzki and Białowieski National Parks recorded near-natural darkness (ELP-D). These light pollution effects can disrupt nocturnal species’ behaviour, reduce biodiversity, and degrade opportunities for dark-sky tourism. The findings emphasise the need for targeted mitigation, including stricter outdoor lighting regulations, formal dark-sky protection zones, and public education to preserve protected areas’ ecological integrity and tourism potential. Full article

Trade ports are the first places where alien species invade and the source of their spread to other areas. Controlling invasions in these regions can effectively reduce invasion pressure and disrupt the spread pathways of invasive species, thereby significantly reducing their threat to local ecosystems and biodiversity loss. Based on 595 field survey plots, the Generalized Linear Model (GLM) and Species Distribution Model (MaxEnt) were employed to analyze and predict the invasion mechanisms and future possible distribution of Solidago canadensis in the Ningbo Port, China. The results indicate that the invasion of S. canadensis in the Ningbo Port was particularly severe, with a 67.7% occurrence rate of all sampling plots in the field survey, and a risk level classified as Grade 1. Biodiversity (p < 0.001) and the minimum temperature of the coldest month (p < 0.01) significantly affect the invasiveness. Highly diverse communities could resist the invasion of alien species, which support Elton’s diversity–invasibility hypothesis. Low temperatures had a restrictive effect on the invasion of S. canadensis. The total suitable area continued to expand under three different climate change scenarios compared to current conditions (increased by 3.73%, 5.67%, and 3.74% by the 2070s). The total potential habitat area of S. canadensis reached its maximum extent (89.77%) under the medium greenhouse gas emission scenario in the 2050s. Meanwhile, the medium suitable area exhibited the greatest fluctuation among the three climate scenarios. Under the low emission condition, the medium suitable area of S. canadensis diminished by 63.10 km², but in the medium and high emission condition, its area expanded by 91.13 km² and 16.20 km², respectively. Under future climate warming scenarios, the invasion risk of S. canadensis in Ningbo Port will continue to increase. The results of our study reveal the diffusion mechanisms of invasive plants at the colonization source, providing important theoretical support for invasive alien species’ initial prevention and control. Full article

Mine water is both wastewater and a valuable unconventional water resource, and its recycling is crucial for the sustainable development of coal-resource-based cities. In response to the complex interactions among multiple stakeholders in the process of mine water recycling, this study innovatively develops a four-party evolutionary game model involving local government, coal mining enterprises, mine water operators, and water users. For the first time, key variables—mine water pricing, water volume, water rights trading, water resource taxation, and objective utility of water resources—are systematically integrated into a multi-agent game framework, extending the analysis beyond conventional policies, such as penalties and subsidies, to explore their impact on recycling behavior. The results show the following: (1) There are 10 possible evolutionary stabilization strategies in the system. The current optimal strategy includes supply, input, use, active support, while the ideal strategy under the market mechanism includes supply, input, use, passive support. (2) Local governments play a leading role in collaborative governance. The decisions of coal mining enterprises and mine water operators are highly interdependent, and these upstream actors significantly influence the water users’ strategies. (3) Government subsidies exhibit an inverted U-shaped effect, while punitive measures are more effective than incentives. The tax differential between recycled and discharged mine water incentivizes coal enterprises to adopt proactive measures, and water rights trading significantly enhances the users’ willingness. (4) Mine water should be priced significantly lower than fresh water and reasonably balanced between stakeholders. Industries with lower objective utility of water tend to prioritize its use. This study provides theoretical support for policy optimization and a market-based resource utilization of mine water. Full article

Climate change undermines progress toward sustainable development goals. This paper uses a two-way fixed-effects model to examine whether and how climate change affects firms’ operating risk from the perspective of heat exposure. The sample comprises 29,128 firm-year observations of Chinese listed firms for the period 2010 to 2021. The main results are as follows: (1) Increased heat exposure leads to higher corporate operating risk. (2) The impact of heat exposure on operating risk varies on firm characteristics. Specifically, manufacturing firms, small firms, and firms located in less developed cities are more susceptible to heat exposure. (3) The mechanism analysis shows that heat exposure exacerbates operating risk by affecting operating income and inventory management. This paper contributes to prior research on the economic impacts of climate change. In the context of climate change, these findings are of significant value in raising corporate awareness of climate change and motivating corporate involvement in low-carbon initiatives that contribute to climate adaptation and mitigation efforts. Full article

The first few days of the second Trump presidency saw a flurry of executive orders targeting immigrants, the transgender community, blacks, and federal government employees. The resulting “shocks” to the system are unprecedented, causing many to question the continuation of American democracy. These actions are a few of many policy preferences developed by conservatives and captured in “Project 2025”, spearheaded by the Heritage Foundation and with the overall intent of restructuring the federal government to suit authoritarian aims. Using a theoretical framework regarding policy entrepreneurs (PEs), I argue that conservative PEs (CPEs), under the aegis of the Republican Party and a second Trump term, are encouraging a shift away from a federal democratic republic to an authoritarian regime. CPEs of interest include elected officials, think tanks, media outlets, interest groups, and political operatives; collectively, these entities constitute a network of mostly unnoticed conservative political professionals using the mechanisms of policy entrepreneurship to damage American democracy. Overall, the actions CPEs take in terms of setting the agenda, controlling the electoral process, and informing the media indicate an eventual abandonment of democratic norms, an inclination towards the establishment of an authoritarian regime, and acceptance of said regime by a significant portion of the American people. Full article

In this study, we proposed a fast and accurate PatchMixer-based framework (Patch-TS). After the data were processed, which included missing values and normalization, the environmental factors were selected via the Pearson correlation coefficient method. Then, the newly developed sap flow prediction model was trained. The resulting data demonstrated that the coefficient of determination (R²), mean squared error (MSE), and mean absolute error (MAE) are 0.921, 0.00824, and 0.0497, respectively. The R² of Patch-TS further improved to 0.929 after 7 factors were extracted via the Pearson correlation method. Furthermore, we comparatively analyse the mitigating effects of RevIn (Reversible Instance Normalization) and Dish-TS on data drift. In addition to the predictive performance of the models under different prediction windows, Patch-TS outperforms the other models. The results demonstrate that the model developed in this paper is an effective tool for accurately predicting sap flow, which is a valuable contribution to the practical management of trees and forests. Full article

The safe operation of power transmission lines is critical for ensuring the stability of the power supply, especially given the increasing frequency of extreme weather events and the risks posed by tree growth. This study proposes a novel method for detecting and predicting the tree barrier risks on transmission lines using Unmanned Aerial Vehicle–Light Detection and Ranging (UAV-LiDAR) technology. The method employs point cloud classification to effectively separate ground, conductor, tower, and vegetation points, followed by 3D reconstruction of the power lines using the catenary equation. Tree growth models are integrated with measured data to predict future tree barrier risks. The experimental results demonstrate that the point-cloud-based method detects 31 tree barriers, with an RMSE of 0.08 m, while the 3D-reconstruction-based method detects 32 tree barriers, with an RMSE of 0.04 m, indicating its higher accuracy. The Cloth Simulation Filter (CSF) ground point classification method achieved the lowest roughness (1.5%), mean error (0.147 m), and RMSE (0.174 m), proving its effectiveness for flat terrain. Additionally, the assisted seed point individual tree segmentation method extracted tree height with high accuracy (R² = 0.84, RMSE = 1.01 m). This study predicts an average tree growth rate of 0.248 m/year over the next five years, identifying a new tree barrier at the coordinates 30°15′16.64″ N, 119°43′16.01″ E. This method enhances the efficiency and accuracy of transmission line inspections, supporting both power line safety and sustainable forest management. Its findings provide a robust technical approach to improving power line operations and forest resource utilization. Full article

Background: Increasing evidence shows that the COVID-19 pandemic has disproportionately impacted certain populations, particularly those facing structural marginalization, such as immigrants and refugees. Additionally, research highlights that structurally marginalized populations living with chronic conditions, such as cancer and/or mental health and addiction (MH&A) disorders, are more vulnerable to the adverse effects of COVID-19. These individuals face higher susceptibility to infection and worse health outcomes, including increased rates of hospitalization, severe illness, and death. To better understand the challenges faced by people living at the intersection of social and clinical disadvantages, we organized a series of Think Tank sessions to engage stakeholders in exploring barriers and identifying community-based solutions for immigrants and refugees living with cancer and/or MH&A disorders during the current and future pandemics. Objectives: Our main objectives were to gauge how earlier findings resonated with stakeholders, to identify any gaps in the work, and to co-develop actionable solutions to safeguard health and well-being during COVID-19 and future crises. Methods: Two virtual Think Tank sessions were held in September 2023 as integrative knowledge exchange forums. The Cancer Think Tank was attended by 40 participants, while the MH&A disorders Think Tank included 41 participants. Each group comprised immigrants and refugees living with or affected by cancer (in the Cancer Think Tank) or MH&A disorders (in the MH&A disorders Think Tank), alongside service providers, policymakers, and researchers from Ontario. This paper presents the key discussions and outcomes of these sessions. Results: Participants identified and prioritized actionable strategies during the Think Tank sessions. In the Cancer Think Tank, participants emphasized the importance of leveraging foreign-trained healthcare providers to address workforce shortages, creating clinical health ambassadors to bridge gaps in care, and connecting immigrants with healthcare providers immediately upon their arrival in Canada. In the MH&A disorders Think Tank, participants highlighted the need to remove silos by fostering intersectoral collaboration, empowering communities and building capacity to support mental health, and moving away from one-size-fits-all approaches to develop tailored interventions that better address diverse needs. Conclusions: The Think Tank sessions enhanced our understanding of how the COVID-19 pandemic has impacted immigrants and refugees living with cancer and/or MH&A disorders. The insights gained informed a series of actionable recommendations to address the unique needs of these populations during the current pandemic and in future public health crises. Full article

Mangrove ecosystems rank among the most productive on Earth. Conducting research on the biomass prediction model of mangroves, as well as achieving simple and efficient estimations of the biomass of mangrove plant organs and the overall biomass, is of utmost significance for evaluating the productivity of the mangrove ecosystem and offering guidance for the future planning, restoration, and management of mangroves. This study examines the biomass distribution characteristics of Kandelia obovata at the northern edge of its range in China and develops models for estimating the biomass of its various components and individual trees. The findings provide valuable references for accurately assessing the biomass of Kandelia obovata plantations in Zhejiang Province. We measured the biomass of different components (branches, leaves, roots) using the harvest method and employed independent variables, including basal diameter (D), tree height (H), diameter squared (D²), the product of diameter squared and height (D²H), and the product of basal diameter and height (DH). Dependent variables included the leaf, branch, root, and total biomass. We developed linear, quadratic, and power function regression equations, selecting the optimal models based on the coefficient of determination (R²), significance of regression, root mean square error (RMSE), and Akaike Information Criterion (AIC). The total biomass ranged from 0.100 to 0.925 Mg ha⁻¹, while the carbon stocks ranged from 0.038 to 0.377 Mg C ha⁻¹. Results indicated that branch biomass accounted for the highest proportion (47.44%~68.35%), while leaf biomass (8.61%~27.83%) and root biomass (23.04%~25.64%) were relatively lower. Similarly, branch carbon storage constituted the highest proportion (52.68%~77.79%), with leaf (8.70%~29.36%) and root carbon storage (13.51%~20.55%) being lower. The optimal model exhibited R² values ranging from 0.594 to 0.921 and significant F-tests (p < 0.001). Single variables D, D², and combined variables D²H and DH provided the best fits. Basal diameter (D) and tree height (H) effectively predict the biomass of Kandelia obovata across different ages, with combined variables DH and D²H enhancing model accuracy. The biomass estimation model for total biomass is: W_Total = 0.0584(DH)^1.3918 (R² = 0.908, F = 2459.87, RMSE = 0.448). This model serves as a reliable tool for estimating the biomass of Kandelia obovata mangroves at the northern edge of its distribution in China. Full article

The COVID-19 pandemic, caused by SARS-CoV-2, disrupted work and life patterns worldwide, underscoring the urgency of addressing climate change. Despite contributing minimally to global greenhouse gas (GHG) emissions, Africa faces disproportionate vulnerability to the impacts of climate change. This commentary explores the benefits of blended work models (remote and in-office work) and the readiness of African cities to adopt them. Notably, the shift to working from home (WFH) during the pandemic improved individual well-being and reduced office energy consumption and commuting-related emissions. Robust digital infrastructure and organizational and sustainable policies are essential to fully leverage blended work for urban sustainability. The unexpected opportunities that arose during the pandemic could help African cities address climate change through careful planning and investment. Full article