Search Results (142)

This study investigates the factors influencing school trip mode choice among senior high school students in the Chiang Rai urban area, Chiang Rai, Thailand, under normal and adverse weather conditions. Utilizing data from 472 students across six extra-large urban schools, a Multinomial Logit (MNL) regression model was applied to examine the effects of socio-demographic attributes, household vehicle ownership, travel distance, and spatial variables on mode selection. The results revealed notable modal shifts during adverse weather, with motorcycle usage decreasing and private vehicle reliance increasing, while school bus usage remained stable, highlighting its role as a resilient transport option. Car ownership emerged as a strong enabler of modal flexibility, whereas students with limited access to private transport demonstrated reduced adaptability. Additionally, increased waiting and travel times during adverse conditions underscored infrastructure and service vulnerabilities, particularly for mid-distance travelers. The findings suggest an urgent need for transport policies that promote inclusive and climate-resilient mobility systems, particularly in the context of Chiang Rai, including expanded school bus services, improved first-mile connectivity, and enhanced pedestrian infrastructure. This study contributes to the literature by addressing environmental variability in school travel behavior and offers actionable insights for sustainable transport planning in secondary cities and border regions. Full article

As climate change intensified water scarcity in Southern Europe, tourism-dependent regions such as Portugal’s Algarve faced growing pressure to adapt their water management systems. This study investigated how hotel groups in the Algarve have adopted and communicated water reuse technologies—specifically desalination and greywater recycling—under environmental, institutional, and reputational constraints. A comparative qualitative case study was conducted involving three hotel groups—Vila Vita Parc, Pestana Group, and Vila Galé—selected through purposive sampling based on organizational capacity and technology adoption stage. The analysis was supported by a supplementary mini-case from Mallorca, Spain. Publicly accessible documents, including sustainability reports, media coverage, and policy frameworks, were thematically coded using organizational environmental behavior theory and the OECD Principles on Water Governance. The results demonstrated that (1) higher organizational capacity was associated with greater maturity in water reuse implementation; (2) communication transparency increased alongside technological advancement; and (3) early-stage adopters encountered stronger financial, regulatory, and operational barriers. These findings culminated in the development of the Maturity–Communication–Governance (MCG) Framework, which elucidates how internal resources, stakeholder signaling, and institutional alignment influence sustainable infrastructure uptake. This research offered policy recommendations to scale water reuse in tourism through financial incentives, regulatory simplification, and public–private partnerships. The study contributed to the literature on sustainable tourism and decentralized climate adaptation, aligning with UN Sustainable Development Goals 6.4, 12.6, and 13. Full article

The behavior of floor-raised chickens is closely linked to their health status and environmental comfort. As a type of broiler chicken with special behaviors, understanding the daily actions of yellow-feathered chickens is crucial for accurately checking their health and improving breeding practices. Addressing the challenges of high computational complexity and insufficient detection accuracy in existing floor-raised chicken behavior recognition models, a lightweight behavior recognition model was proposed for floor-raised yellow-feathered chickens, based on a Dual-Backbone Heterogeneous YOLO Network. Firstly, DualHet-YOLO enhances the feature extraction capability of floor-raised chicken images through a dual-path feature map extraction architecture and optimizes the localization and classification of multi-scale targets using a TriAxis Unified Detection Head. Secondly, a Proportional Scale IoU loss function is introduced that improves regression accuracy. Finally, a lightweight structure Eff-HetKConv was designed, significantly reducing model parameters and computational complexity. Experiments on a private floor-raised chicken behavior dataset show that, compared with the baseline YOLOv11 model, the DualHet-YOLO model increases the mAP for recognizing five behaviors—pecking, resting, walking, dead, and inactive—from 77.5% to 84.1%. Meanwhile, it reduces model parameters by 14.6% and computational complexity by 29.2%, achieving a synergistic optimization of accuracy and efficiency. This approach provides an effective solution for lightweight object detection in poultry behavior recognition. Full article

In the current context, where environmental concerns are gaining increased attention, the transition toward sustainable urban mobility stands out as a necessary and responsible step. Technological advancements over the past decade have brought private autonomous vehicles, particularly those defined by the Society of Automotive Engineers Levels 4 and 5, into focus as promising solutions for mitigating road congestion and reducing greenhouse gas emissions. However, the extent to which Autonomous Vehicles can fulfill this potential depends largely on user acceptance, patterns of use, and their integration within broader green energy and sustainability policies. The present paper aims to develop an integrated conceptual model that links behavioral determinants to environmental outcomes, assessing how individuals’ intention to adopt private autonomous vehicles can contribute to sustainable urban mobility. The model integrates five psychosocial determinants—perceived usefulness, trust in technology, social influence, environmental concern, and perceived behavioral control—with contextual variables such as energy source, infrastructure availability, and public policy. These components interact to predict users’ intention to adopt AVs and their perceived contribution to urban sustainability. Methodologically, the study builds on a narrative synthesis of the literature and proposes a framework applicable to empirical validation through structural equation modeling (SEM). The model draws on established frameworks such as Technology Acceptance Model (TAM), Theory of Planned Behavior, and Unified Theory of Acceptance and Use of Technology, incorporating constructs including perceived usefulness, trust in technology, social influence, environmental concern, and perceived behavioral control, constructs later to be examined in relation to key contextual variables, including the energy source powering Autonomous Vehicles—such as electricity from mixed or renewable grids, hydrogen, or hybrid systems—and the broader policy environment (regulatory frameworks, infrastructure investment, fiscal incentives, and alignment with climate and mobility strategies and others). The research provides relevant directions for public policy and behavioral interventions in support of the development of clean and smart urban transport in the age of automation. Full article

Addressing climate change requires deeper insight into the psychological drivers of pro-environmental behavior. This study investigates how personality traits, climate-related emotions, and demographic factors can predict sustainable consumption and climate action participation using a Bayesian regression approach. Drawing from the HEXACO personality model and key emotional predictors—Climate Change Worry (CCW) and environmental empathy (EE)—we analyzed data from 604 adults in Greece to assess both private and public climate-related behaviors. This research is novel in its integrative approach, combining dispositional traits and affective states within a Bayesian analytical framework to simultaneously predict both sustainable consumption and climate action. Bayesian model testing highlighted education as the most powerful and reliable predictor of sustainable consumption, with increasing levels—namely Doctoral education—linked to more environmentally responsible action. CCW produced small but reliable effects, supporting hypotheses that moderate emotional concern will lead to sustainable behavior when linked to efficacy belief. The majority of HEXACO traits, e.g., Honesty–Humility and Conscientiousness, produced limited predictive power. This indicates in this case that structural and emotional considerations were stronger than dispositional personality traits. For climate action involvement, Bayesian logistic models found no considerable evidence of any predictor, corroborating the perspective that public participation in high effort action is most likely to rely on contextual enablers instead of internal sentiments or attributes. A significant interaction effect between education and gender also indicated that the sustainability effect of education is moderated by sociocultural identity. Methodologically, this research demonstrates the strengths of Bayesian analysis in sustainability science to make sensitive inference and model comparison possible. The results highlight the importance of affect-related structural variables in behavioral models and have applied implications for theory-informed and targeted climate education and communication interventions to enable different populations to act sustainably. Full article

Although the transition to electric vehicles (EVs) is well underway and expected to continue in global car markets, most vehicles on the world’s roads will be powered by internal combustion engine vehicles (ICEVs) and fossil fuels for the foreseeable future, possibly well past 2050. Thus, good environmental performance and effective emission control of ICE vehicles will continue to be of paramount importance if the world is to achieve the stated air and climate pollution reduction goals. In this study, we review 228 publications and identify four main issues confronting these objectives: (1) cheating by vehicle manufacturers, (2) tampering by vehicle owners, (3) malfunctioning emission control systems, and (4) inadequate in-service emission programs. With progressively more stringent vehicle emission and fuel quality standards being implemented in all major markets, engine designs and emission control systems have become increasingly complex and sophisticated, creating opportunities for cheating and tampering. This is not a new phenomenon, with the first cases reported in the 1970s and continuing to happen today. Cheating appears not to be restricted to specific manufacturers or vehicle types. Suspicious real-world emissions behavior suggests that the use of defeat devices may be widespread. Defeat devices are primarily a concern with diesel vehicles, where emission control deactivation in real-world driving can lower manufacturing costs, improve fuel economy, reduce engine noise, improve vehicle performance, and extend refill intervals for diesel exhaust fluid, if present. Despite the financial penalties, undesired global attention, damage to brand reputation, a temporary drop in sales and stock value, and forced recalls, cheating may continue. Private vehicle owners resort to tampering to (1) improve performance and fuel efficiency; (2) avoid operating costs, including repairs; (3) increase the resale value of the vehicle (i.e., odometer tampering); or (4) simply to rebel against established norms. Tampering and cheating in the commercial freight sector also mean undercutting law-abiding operators, gaining unfair economic advantage, and posing excess harm to the environment and public health. At the individual vehicle level, the impacts of cheating, tampering, or malfunctioning emission control systems can be substantial. The removal or deactivation of emission control systems increases emissions—for instance, typically 70% (NO_x and EGR), a factor of 3 or more (NO_x and SCR), and a factor of 25–100 (PM and DPF). Our analysis shows significant uncertainty and (geographic) variability regarding the occurrence of cheating and tampering by vehicle owners. The available evidence suggests that fleet-wide impacts of cheating and tampering on emissions are undeniable, substantial, and cannot be ignored. The presence of a relatively small fraction of high-emitters, due to either cheating, tampering, or malfunctioning, causes excess pollution that must be tackled by environmental authorities around the world, in particular in emerging economies, where millions of used ICE vehicles from the US and EU end up. Modernized in-service emission programs designed to efficiently identify and fix large faults are needed to ensure that the benefits of modern vehicle technologies are not lost. Effective programs should address malfunctions, engine problems, incorrect repairs, a lack of servicing and maintenance, poorly retrofitted fuel and emission control systems, the use of improper or low-quality fuels and tampering. Periodic Test and Repair (PTR) is a common in-service program. We estimate that PTR generally reduces emissions by 11% (8–14%), 11% (7–15%), and 4% (−1–10%) for carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NO_x), respectively. This is based on the grand mean effect and the associated 95% confidence interval. PTR effectiveness could be significantly higher, but we find that it critically depends on various design factors, including (1) comprehensive fleet coverage, (2) a suitable test procedure, (3) compliance and enforcement, (4) proper technician training, (5) quality control and quality assurance, (6) periodic program evaluation, and (7) minimization of waivers and exemptions. Now that both particulate matter (PM, i.e., DPF) and NO_x (i.e., SCR) emission controls are common in all modern new diesel vehicles, and commonly the focus of cheating and tampering, robust measurement approaches for assessing in-use emissions performance are urgently needed to modernize PTR programs. To increase (cost) effectiveness, a modern approach could include screening methods, such as remote sensing and plume chasing. We conclude this study with recommendations and suggestions for future improvements and research, listing a range of potential solutions for the issues identified in new and in-service vehicles. Full article

The global school uniform industry, primarily driven by linear production models, significantly contributes to textile waste and environmental degradation. In Australia, over 2000 tons of school uniforms are discarded annually, highlighting the urgent need for sustainable alternatives. This study explores the integration of Circular Economy (CE) principles into school uniform systems through a case study of a private school in Victoria. Using a thematic approach, the research involved a parent survey with 106 participants and a focus group with 6 parents. The study identified financial, logistical, and socio-cultural factors influencing uniform consumption and disposal behaviors. Affordability emerged as the primary motivator for adopting second-hand uniforms (86%). However, barriers such as limited sizing, hygiene concerns, quality, and social stigma hinder wider adoption. Parents also expressed dissatisfaction with the current uniform design, material breathability, and durability, particularly in warmer climates. Despite increased awareness of sustainability (61% cited environmental concerns), actionable engagement remains low due to a lack of transparency and infrastructure. The study proposes a replicable circular uniform framework based on stakeholder co-design, reverse logistics, and curriculum-based sustainability education. These findings offer practical implications for policymakers, educators, and manufacturers aiming to reduce textile waste and promote CE adoption within the education sector. Full article

Vehicle congestion and the environmental problems associated with the increasing vehicle fleet have led stakeholders to create solutions to these problems. Park-and-Ride (P&R) facilities are provided as a solution for public transportation to avoid increasing vehicular flow and using private vehicles. However, the optimal location of these facilities is still a challenge to be considered. Therefore, this article aims to present a systematic review of the mathematical models applied for P&R localization, using the PRISMA protocol to ensure a comprehensive analysis. A total of 44 articles between 2002 and 2025 were identified into four categories: decision support models, econometric models, optimization models, and other models. The review also examines the term distribution of urban contexts where the mathematical models are applied, distinguishing between Global North versus Global South urban contexts. The results showed the efficiency of mathematical models within the decision support models category due to their integration with multiple criteria. The econometric models analyze factors influencing user behavior, while the optimization models improve and optimize the efficiency of transport networks despite facing computational challenges. Finally, other models, such as multilevel programming and fuzzy logic, offer adaptive solutions for highly variable urban environments. The primary contribution of this study is its comprehensive application of the mathematical models used for the location of P&R facilities. This offers a systematic approach for anticipating future urban situations, developing supporting policies, and analyzing their effects. Full article

This paper suggests a method of private internalization of externalities via the bundling of new fossil fuel automobile purchases. The bundle encourages and pursues a new quality of life entailing planting trees, a healthy body and mind, and efficient use of new energy usages for the joining of a grassroots environmental club. The work was motivated by the classic economics article by Ronald Coase, The Problem of Social Cost (1960). Marketing plays an important role in this internalization endeavor. Indeed, modern behavioral economics and psychology help inform how creative bundles of a new automobile purchase with sustainable lifestyle elements can effectively formulate some promotional propositions. The pragmatism we are demonstrating in this piece is to show the linkage between theories and marketable directions that can be experimented with via trial-and-error, as in many bundling exercises. Full article

Cities’ role as major hubs of human activity and economic development is essential in attaining sustainable development, fostering a balance between economic, social, and environmental development, especially in light of the growing concern over Anthropocene-induced environmental issues like global warming and climate change. The United Nations Sustainable Development Goals (SDGs) represent a historic call for coordinated international action in this area, with SDG 11 specifically identifying “Sustainable Cities and Communities” as a primary objective. Therefore, it is clear that a paradigm shift in our approach to these challenges in terms of our thinking, sensibility, behavior, and responses is necessary. Implicitly, in view of their pivotal role in environmental sustainability, development of “smart” cities as healthy, citizen-friendly, economically viable, and sustainable cities for our future generations in today’s globally integrated world, as predominant centers of human settlement and activity with multinational enterprises driving economic growth, gains the immediate attention of researchers. In this light, this study aims to identify and thereafter prioritize key indicators of a smart city using the structured and consistency-focused best–worst multi-criteria decision-making (BWM) method, suitable for expert-driven decision-making with limited comparisons. While the UN’s SDG 11 promotes safe and resilient cities, our findings suggest a disparity in how local officials prioritize certain dimensions such as safety or recreation. This disconnect warrants closer examination of localized policy drivers. The findings of this study indicate that according to experts, among others, the priority themes are, in order, water and sanitation, wastewater, health, the environment, and the economy. Thus, these represent a key take-away for multinational enterprises for identifying and assessing significant thrust domains and areas of opportunity for intervention and contribution to the UN SDGs. It also enables a replicable framework for synergy between the public and private sectors towards contrastive intervention in other cities across the globe. Full article

This study intends to ascertain the correlation between green banking practices and the sustainable environmental performance of private banks. It further investigates the mediating role of employee green behavior and motivation. This study used a quantitative research method to test the study hypotheses. A standardized questionnaire with a 5-point Likert scale was utilized to collect data for the survey. The sample size consisted of 376 respondents who were conveniently selected. Data were analyzed using PLS software (Version 4.0). The main finding is that employees’ green motivation mediated the link between employee-related and customer-related green practices and a bank’s environmental performance. Equally, employee green behavior mediated the link between employee-related, operation-related, and customer-related green practices and a bank’s environmental performance. This study is one of few in Bangladesh’s banking sector that provide a comprehensive overview of green banking practices, employee green motivation and behavior, and their connections to banks’ sustainable environmental performance. Full article

Risk-taking is a critical driver of sustainable development and financial performance for firms, especially under environmental degradation constraints. Despite the increasing implementation of green credit policies, their impact on corporate risk-taking remains underexplored in the existing literature. This study investigates the effects and underlying mechanisms of green credit policies on risk-taking behaviors among Chinese listed companies from 2009 to 2019. Utilizing econometric methodologies, including Difference-in-Differences, mediation analysis, and moderation analysis, the findings reveal that green credit policies significantly enhance the risk-taking activities of polluting enterprises. These results are robust across various sensitivity tests. Additionally, the relationship between green credit policies and corporate risk-taking is mediated by debt maturity mismatch and moderated by ESG and executive compensation. Subgroup analyses indicate that large and state-owned polluting enterprises experience greater increases in risk-taking compared to their small, medium-sized, and private counterparts. Furthermore, executive remuneration notably amplifies risk-taking in private firms. This research provides essential micro-level insights to optimize the effectiveness of green credit policies in promoting corporate risk-taking and advancing sustainable development. Full article

This article presents the role of environmental attitudes and self-efficacy in shaping the behavioral expectations of business students in Southeast Europe regarding extreme climate events. Conducted across twelve public and private business schools in five countries, the study provides a baseline for comparison with similar empirical research. Using multiple linear regression, we analyze the relationship between the pro-environmental attitudes and environmental self-efficacy to the students’ climate change expectations. Our results indicate that pro-environmental attitudes significantly predict the students’ expectations of extreme climate events, while environmental self-efficacy plays a secondary but statistically significant role. These findings extend the extant literature by focusing on the role of sustainability in business school curricula and the potential positive outcomes of experiential learning methods and approaches. Full article

In response to the increasing global emphasis on environmental accountability, the issue of greenwashing requires urgent resolution. This research investigates how state ownership affects greenwashing behaviors in Chinese A-share private companies over the period from 2010 to 2021, utilizing resource support and supervisory governance as analytical frameworks. Empirical analysis reveals that state-owned shareholder holdings significantly inhibit greenwashing practices in private enterprises, with this result remaining robust across various sensitivity tests. Furthermore, it is demonstrated that these holdings reduce greenwashing through both resource support and supervisory governance pathways. This study enhances the scholarly understanding of how state capital impacts private firms and underscores the distinctive roles and benefits that state-owned shareholders bring to the mixed-ownership reform process. The results suggest new pathways for fostering the sustainable development of private enterprises and offer crucial insights for policymakers focused on advancing mixed-ownership reforms and ensuring corporate accountability. Full article

Promoting pro-environmental behaviors among individuals in the community is crucial to increase community resilience and to address environmental challenges. However, a persistent intention–behavior gap often exists, particularly in separate private or public spheres. Historically, addressing this gap has involved focusing on single moderating variables such as environmental knowledge or environmental risk perception. Yet, few studies have examined it in both spheres under the combined moderating influence of two variables. Our research plans to bridge this gap by exploring pro-environmental behaviors in the private and public spheres using conditional process models under the joint moderating effects of EK and environmental risk perception. Our findings reveal a larger intention–behavior gap in the public sphere compared to the private sphere, which highlights the greater challenges in translating environmental intentions into collective actions within the community. In private sphere behaviors, we observe the most significant positive moderating effect on intention–behavior alignment when individuals possess high environmental knowledge coupled with low environmental risk perception. This combination facilitates the bridging of the intention–behavior gap, fostering individual actions that can contribute to community resilience. Conversely, in public sphere behaviors, optimal alignment occurs when both environmental knowledge and risk perception are high, facilitating the translation of intentions into actions. These insights offer targeted policy recommendations for governments and policymakers, contributing to a deeper understanding of increasing community resilience. Full article