Sustainability

This study investigates the biosorption of heavy metal ions (Pb, Fe, Cu, Cd, Zn, and Mn) from wastewater using the powdered biomass of Phragmites australis (common reed) under varying conditions, including temperature, pH, retention time, plant powder size, and biosorbent weight. The results showed that plant powder size significantly influenced the biosorption efficiency, with the 0.5 mm diameter powder yielding the highest removal rates for the heavy metal ions. The optimal temperature for biosorption was found to be between 30 and 50 °C, achieving up to 99.94% removal for Pb. The ideal pH for the biosorption of all metals was seven, and the best retention time for ion removal was 30 min, with a mean biosorption rate of 99.82% for Fe. A biosorbent weight of 10 g/L was also identified as the most effective for metal ion removal. Furthermore, two forms of P. australis, dry pieces and powdered biomass, were tested, with the powdered biomass exhibiting a superior biosorption performance. FTIR analysis revealed the involvement of carboxyl and hydroxyl functional groups in the biosorption process, while SEM imaging confirmed the surface interactions between metal ions and the plant material. The adsorption of heavy metals onto P. australis was effectively described by both Langmuir and Freundlich isotherm models, indicating a mix of monolayer coverage and heterogeneous interactions. The Langmuir model showed the highest adsorption capacities for Mn²⁺ (6.29 mg/g) and Cd²⁺ (5.10 mg/g), with strong affinities for Pb²⁺ (K_L = 0.0122 L/mg), Fe²⁺ (K_L = 0.0137 L/mg), and Cu²⁺ (K_L = 0.0130 L/mg). Similarly, the Freundlich model indicated favorable adsorption (n > 1) for all ions. Cu²⁺ and Fe²⁺ had the highest adsorption intensities (n = 2.06), with the strongest capacities being observed for Fe²⁺ (K_f = 0.231) and Cu²⁺ (K_f = 0.222). These findings confirm the high potential of P. australis as a sustainable and eco-friendly biosorbent. Full article

This study explores the evolution of academic entrepreneurship, emphasizing the crucial role of universities in fostering innovation and economic development. Through a systematic review guided by the PRISMA methodology, the research identifies six critical dimensions in academic entrepreneurship: university entrepreneurial ecosystems, organizational structures, capacity building, impact evaluation, contextual influences, and sustainability. The review highlights the integration of sustainability principles, digital transformation, and innovative financing models as central themes driving contemporary university entrepreneurship. Additionally, it underscores the necessity for adaptive governance frameworks and interdisciplinary collaborations to address diverse socioeconomic contexts. The findings offer theoretical insights and practical recommendations for policymakers and university administrators, with the aim of enhancing the design and implementation of effective entrepreneurial ecosystems. This work contributes to a deeper understanding of the mechanisms and strategies that enable universities to act as catalysts for innovation and sustainable economic growth. Full article

Renewable energy, especially wind power, is required to reduce greenhouse gas emissions and fossil fuel use. Variable wind patterns and weather make wind energy integration into modern grids difficult. Energy trading, resource planning, and grid stability demand accurate forecasting. This study proposes a hybrid deep learning framework that improves forecasting accuracy and interpretability by combining advanced deep learning (DL) architectures, explainable artificial intelligence (XAI), and metaheuristic optimization. The intricate temporal relationships in wind speed data were captured by training Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), LSTM-GRU hybrid, and Bidirectional LSTM-GRU following data preprocessing and normalization. To enhance transparency, Local Interpretable Model-Agnostic Explanations (LIMEs) were applied, revealing key time-step contributions across three urban datasets (Los Angeles, San Francisco, and San Diego). The framework further incorporates the Snake Optimizer Algorithm (SOA) to optimize hyperparameters such as LSTM units, dropout rate, learning rate, and batch size, ensuring improved training efficiency and reduced forecast error. The model predicted 2020–2040 wind speeds using rolling forecasting; the SOA-optimized LSTM model outperformed baseline and hybrid models, achieving low MSE, RMSE, and MAE and high R² scores. This proves its accuracy, stability, and adaptability across climates, supporting wind energy prediction and sustainable energy planning. Full article

The Yellow River Basin (YRB) is an important ecological security barrier in China, playing an irreplaceable role in soil and water conservation, climate regulation, and biodiversity maintenance, and it is related to the stability and security of the ecosystem. Exploring the spatial correlation networks and factors influencing ecological security in the YRB can provide new ideas for cross-domain collaborative governance, promote efficient cooperation among regions, and optimize resource allocation. Using a quantitative approach to assess the YRB’s ecological security, we employed an adjusted gravity model, social network analysis, and quadratic assignment procedure analysis to understand the spatial connection dynamics. The results indicate the following: (1) Ecological security in the YRB continued to improve from 2005 to 2019, but the overall level was low. The degree of the dispersion of the ecological security status among cities constantly increased, and there were significant regional differences in the level of ecological security in the YRB. (2) From 2005 to 2019, the number and density of network connections among cities within the YRB increased significantly, and the ecological security links gradually strengthened. The Shandong Peninsula city cluster and the Hubao–Eyu City cluster are not only located at the core of the network but also play the role of “bridge intermediary”, exhibiting strong control. (3) Among all variables, economic development and geographic proximity increased significantly in terms of their correlation with the YRB’s ecological security. The study of spatial connectivity networks and their influencing factors in the YRB provides new ideas for inter-regional collaborative governance. 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

Sustainable Development (SD) involves multiple factors and different perspectives that are critical to individuals, organizations, regions, countries, and the world. Even though relationships among Global Competitiveness, the Macroeconomic Environment, and SD dimensions, encompassing 17 Sustainable Development Goals (SDGs), are critical, for national and global policymaking, many of these relationships have not been studied systematically nor at different aggregation levels. Therefore, this study examines the relationships among the Global Competitiveness pillars (e.g., Institutions, Infrastructure, Education, Technology, Business Sophistication, and Innovation) and the Macroeconomic Environment and the SD dimensions (Social, Economic, and Environmental) using various models. Additionally, this study examined three country clusters (very-competitive, competitive, and less competitive). The PLS-SEM analysis used 11-year data from 128 countries. The results showed variability in the relationships studied as well as differences between country clusters and countries. The findings may be applicable for policymakers in reflecting and acting on the specificity of national SD, determining SD priorities for the future, as well as reflecting and acting on integrating national SD into global SD. Full article

The private healthcare sector in Romania, led by prominent players such as Medlife, Regina Maria, Medicover and Sanador, has become a cornerstone of the country’s healthcare system. However, achieving sustainability in this sector remains a challenge. This study evaluates sustainability practices in Romania’s private medical sector using the Triple Bottom Line (TBL) framework, comparing them to those of the EU, USA and Japan. Using statistical methods and benchmarking, we identify correlations between healthcare expenditures, financing schemes and sustainability metrics. A bibliographic review highlights global trends in sustainable healthcare management, including environmental, social and economic strategies and provides insights into the cost-effectiveness of green initiatives. Special focus is given to the role of technology in driving sustainability through innovations in telemedicine, digital health records and operational optimization. Using statistical methods (Pearson and Spearman correlation coefficients), we have performed an analysis of health expenditure data for EU countries, the USA and Japan. The dataset was extracted from the Organisation for Economic Co-operation and Development (OECD) data portal and included various health expenditure indicators, financing schemes and administrative data for all EU countries, the USA and Japan for the period 2018–2023. We have performed a structured analysis that explores correlations between these indicators, with a focus on financial schemes, expenditures and management sustainability. The analysis shows strong correlations between healthcare expenditures, financing schemes and administrative costs. Countries with efficient governance, balanced financing and proactive population health strategies (e.g., Japan and Nordic countries) demonstrate better management sustainability. However, countries like the USA and Eastern EU nations face challenges due to high administrative costs and inefficient financing models, respectively. Addressing these issues is critical to sustaining healthcare systems in the long term. The findings reveal that while Romanian providers excel in patient satisfaction and technological innovation, they lag behind their European counterparts in environmental sustainability and equitable access. Recommendations are proposed to address these gaps, drawing on successful strategies implemented in other European healthcare systems. This study fills a gap in the literature by providing a structured analysis of sustainability practices in Romania’s private healthcare sector, contextualized within a global comparative framework. Full article

Rapid advancements in artificial intelligence (AI) have led to a substantial increase in energy consumption, particularly during the training phase of AI models. As AI adoption continues to grow, its environmental impact presents a significant challenge to the achievement of the United Nations’ Sustainable Development Goals (SDGs). This study examines how three key training configuration parameters—early-stopping epochs, training data size, and batch size—can be optimized to balance model accuracy and energy efficiency. Through a series of experimental simulations, we analyze the impact of each parameter on both energy consumption and model performance, offering insights that contribute to the development of environmental policies that are aligned with the SDGs. The results demonstrate strong potential for reducing energy usage without compromising model reliability. The results highlight three lessons: promoting early-stopping epochs as an energy-efficient practice, limiting training data size to enhance energy efficiency, and developing standardized guidelines for batch size optimization. The practical applicability of these three lessons is illustrated through the implementation of a smart building attendance system using facial recognition technology within an Ecocampus environment. This real-world application highlights how energy-conscious AI training configurations support sustainable urban innovation and contribute to climate action and environmentally responsible AI development. Full article

Urban climate resilience is shaped by both direct exposure to environmental risks and cognitive, socioeconomic and institutional factors. This study investigates climate change risk perception (CCRP), psychological distance (PD) and adaptive capacity (AC) across five districts of Istanbul: Beşiktaş, Kadıköy, Kağıthane, Şişli and Üsküdar, using a structured survey (sample size = 500) and advanced multivariate statistical modeling to explore the factors influencing adaptive behavior. To evaluate perceptual and behavioral responses to climate threats, the study constructs both equal-weighted indices and indices derived through principal component analysis (PCA). ANOVA and chi-square tests reveal significant district-level differences in risk perception and adaptation engagement. PCA results validate the internal structure of the indices by identifying latent dimensions such as institutional confidence, emotional proximity and self-efficacy. Correlation and regression analyses confirm that CCRP and PD significantly predict AC in theoretically meaningful patterns. Structural equation modeling (SEM) demonstrates both direct and indirect pathways linking climate risk perception to adaptive capacity, highlighting the complex interplay of these variables. Mediation analysis shows that PD partially mediates the CCRP–AC relationship, accounting for 39.7% of the total effect. Cluster analysis identifies distinct cognitive profiles where proactive adaptation behaviors are more common in affluent districts while disengagement is more prevalent in low-income areas. These findings underscore the importance of localized communication efforts, institutional credibility and financial equity in shaping effective climate adaptation. By integrating perceptual and structural dimensions, the study advances a multidimensional understanding of urban climate readiness and offers empirical guidance for socially equitable resilience policy design. Full article

Against global carbon neutrality goals and China’s “dual carbon” strategy, this study examines how green technology innovation shapes corporate carbon performance through a dual-path mechanism—improving enterprises’ resource utilization efficiency and environmental governance capabilities. Leveraging data from Chinese A-share listed firms (2007–2022) and methods including fixed effects, instrumental variables, and Heckman two-stage models, key findings include: (1) Green technology innovation significantly improves carbon performance. (2) This effect operates through two pathways: enhancing total factor productivity (TFP) and strengthening environmental governance. (3) Green media and investor attention amplify the positive impact of green innovation on carbon performance. (4) The effect remains significant but shows diminishing marginal returns over 1–4 future periods. (5) Non-state-owned enterprises and non-high-carbon industries exhibit more pronounced improvements. This research provides micro-level evidence for “technology-driven low-carbon transformation”, offering theoretical support for policy differentiation and corporate green technology strategies, with practical implications for achieving China’s “dual carbon” objectives. Full article

Food waste in Australia’s horticulture sector poses significant economic, environmental, and social challenges, with approximately 1.3 million tonnes of waste generated annually. This waste, particularly prevalent in fruits and vegetables, arises across various supply chain stages, driven by factors such as overproduction, cosmetic standards, inadequate redistribution networks, and limited technological infrastructure. Addressing these issues is critical to achieving national sustainability goals, including halving food waste by 2030 as outlined in the United Nations Sustainable Development Goals (SDG 12.3). This paper explores the development of an action plan to systematically reduce food waste across the horticulture supply chain through an extensive research and consultation process. Using a review-plan-do sector action plan methodology, the study combined insights from a literature review, stakeholder interviews, and workshops to identify and validate waste hotspots, root causes, and actionable strategies. Key findings from the research informed the development of nine prioritized strategies categorized into enabling, preventive, and repurposing actions. These strategies include implementing standardized waste measurement systems, enhancing redistribution infrastructure, expanding processing facilities for value-added products, and promoting flexible cosmetic standards. Under these strategies, the plan also outlines short-, medium-, and long-term actions to achieve a 50% reduction in food waste by 2030. This sector-wide action plan serves as a practical model for addressing food waste challenges and fostering sustainability in horticulture and similar industries globally. Full article

The sustainability of the natural gas-to-methanol (NGTM) and methanol-to-gasoline (MTG) processes are assessed in this systematic review as a potential substitute in the global energy transition. Methanol offers itself as a versatile and less carbon-intensive substitute for conventional gasoline in light of growing environmental concerns and the demand for cleaner fuels. This review’s rationale is to assess MTG’s ability to lessen environmental impact while preserving compatibility with current fuel infrastructure. The goal is to examine methanol and gasoline’s effects on the environment, society, and economy throughout their life cycles. This review used a two-phase systematic literature review methodology, filtering and evaluating studies that were indexed by Scopus using bibliometric and thematic analysis. A total of 25 documents were reviewed, in which 22 documents analyzed part of this study, and 68% employed LCA or techno-economic analysis, with the U.S. contributing 35% of the overall publications. A comparative analysis of the reviewed literature indicates that methanol-based fuels offer significantly lower greenhouse gas (GHG) emissions and life cycle environmental impacts than gasoline, particularly when combined with carbon capture and renewable feedstocks. This review also highlights benefits, such as improved safety and energy security, while acknowledging challenges, including high production costs, infrastructure adaptation, and toxicity concerns. Several drawbacks are high manufacturing costs, the necessity to adjust infrastructure, and toxicity issues. The report suggests investing in renewable methanol production, AI-driven process optimization, and robust legislative frameworks for integrating green fuels. The life cycle sustainability assessment (LCSA) of NGTM and MTG systems should be investigated in future studies, particularly in light of different feedstock and regional circumstances. The findings emphasize NGTM and MTG’s strategic role in aligning with several UN Sustainable Development Goals (SDGs) and add to the worldwide conversation on sustainable fuels. A strong transition necessitates multi-stakeholder cooperation, innovation, and supporting policies to fully realize the sustainability promise of cleaner fuels like methanol. Full article

The enhancements of tax policies and their coordination have emerged as a significant way to promote corporate sustainability, especially in developing economies worldwide. Using panel data from Chinese non-financial A-share listed companies from 2009 to 2022, this study empirically explores the promoting effects of corporate income tax (CIT) incentives and environmental protection tax (EPT) levies on corporate ESG performance. We find that the CIT incentive has a notable positive impact on firms’ ESG behavior, acting on the micro-mechanisms of increasing corporate cash flow and reducing agency costs, and its promoting effect is more salient with regard to the social and governance dimensions. This study also traces the interactive effects between the EPT levy and CIT incentive policies, which boost corporate ESG behavior synergistically. Heterogeneity analyses reveal that these effects are more noticeable in manufacturing firms and non-state-owned firms with severe financing constraints. Environmental tests show that CIT incentive policies have positive effects on green technological innovation, and Chinese enterprises are still experiencing relatively serious negative impacts. The conclusions of this study are conducive to providing theoretical support and policy suggestions for encouraging the sustainable development of companies through the policy combination of environmental regulation and tax incentives. Full article

Concrete production contributes nearly 8% of the global CO₂ emissions, making carbon capture in construction materials a critical environmental priority. While microbial self-healing concrete has shown promise in repairing structural cracks, its potential to serve as a carbon-negative material through atmospheric CO₂ sequestration remains underutilized. This interdisciplinary review—designed for materials scientists, civil engineers, and environmental technologists—systematically evaluates bacterial candidates for their application in self-healing, carbon-capturing concrete. Bacteria are ranked according to their efficiency in capturing CO₂ through both direct mechanisms (e.g., photosynthetic fixation by cyanobacteria) and indirect pathways (e.g., ureolysis-driven calcium carbonate precipitation). The assessment also considers microbial survivability in high-alkalinity concrete environments, the effectiveness of encapsulation strategies in enhancing bacterial viability and function over time, and sustainability metrics such as those derived from life cycle assessment (LCA) analyses. The findings highlight Bacillus sphaericus and Sporosarcina pasteurii as high-performing species in terms of rapid mineralization and durability, while encapsulation significantly improves the long-term viability for species like Paenibacillus mucilaginosus and Synechococcus. Notably, Bacillus sphaericus and Sporosarcina pasteurii exhibit carbonate precipitation rates of 75–100 mg CaCO₃/g biomass and enable crack closure of up to 0.97 mm within 8 weeks. The proposed bacterial ranking framework, paired with performance data and environmental modeling, provides a foundation for the advancement of scalable, carbon-negative concrete solutions. Full article

Enhancing residents’ green consumption is essential to fostering high-quality economic advancement. This study constructs an indicator system for residents’ green consumption based on three subsystems: green manufacturing processes, sustainable lifestyles, and environmental ecosystems. A regression model analyzes how public environmental concern affects residents’ green consumption, using panel data from 30 provinces and cities in China over the period 2011–2023. Additionally, analyses of mechanisms and heterogeneity are carried out. The study results are presented below: First, public environmental concern (PEC) can significantly enhance residents’ green consumption (RGC), with an increase of 1% in PEC leading to a 0.261% rise in RGC. Second, green technological innovation (GTI) and market-based incentive environmental regulation (MER) mediate the relationship between PEC and RGC. However, the role of command-and-control environmental regulation (CER) as a mediator is insignificant. Third, there is heterogeneity in RGC based on region, pollution emissions, and innovation foundations. The impact of PEC is notably greater in central-western regions, areas with higher pollution emissions, and regions with better innovation foundations. Therefore, this study proposes policy recommendations from three aspects: improving public environmental concern, strengthening green technological innovation in enterprises, and formulating region-specific industrial upgrading paths to promote residents’ green consumption. Full article

This study examines the impact of technological innovation, digitalization, and information and communication technologies (ICTs) on trade-related carbon emissions (TAEs) and the role of economic growth in this relationship. Using data from the 15 countries with the highest carbon emissions in the world for the period 1997–2022, analyses were conducted with Panel-Corrected Standard Errors (PCSEs), Seemingly Unrelated Regression (SUR), and Driscoll–Kraay (D-K) estimators. TAEs provide a more comprehensive environmental assessment than traditional emission calculations by taking into account the impact of international trade on carbon emissions. The findings show that technological innovation, digitalization, and ICTs use increased trade-related carbon emissions, and economic growth further strengthens this effect. These results reveal that sustainable production models and green energy policies should be emphasized more in order to minimize the environmental impacts of technological developments and economic growth. The findings of this study provide important strategic information for policymakers, environmental regulators, and international trade institutions in developing sustainable technology and trade policies to reduce carbon emissions. Full article

In semi-arid regions, seasonally dry tropical forests are essential for regulating the surface energy balance, which can be analyzed by examining air heating processes and water availability control. The objective of this study was to evaluate the ability of the Brazilian Developments on the Regional Atmospheric Modelling System (BRAMS) model in simulating the seasonal variations of the energy balance components of the Caatinga biome. The surface measurements of meteorological variables, including air temperature and relative humidity, were also examined. To validate the model, we used data collected in situ using an eddy covariance system. In this work, we used the BRAMS model version 5.3 associated with the Joint UK Land Environment Simulator (JULES) version 3.0. The model satisfactorily represented the rainfall regime over the northeast region of Brazil (NEB) during the wet period. In the dry period, however, the coastal rainfall pattern over the NEB region was underestimated. In addition, the results showed that the surface fluxes linked to the energy balance in the Caatinga were impacted by the effects of rainfall seasonality in the region. The assessment of the BRAMS model’s performance demonstrated that it is a reliable tool for studying the dynamics of the dry forest in the region, providing valuable support for sustainable management and conservation efforts. Full article

Implementation of green supply chain management (GSCM) has gained increasing attention as businesses seek to balance economic, social, and environmental sustainability. However, its adoption remains uneven across countries, particularly in developing economies such as Indonesia. This study aims to identify the key factors influencing the implementation of GSCM in Indonesian logistics companies using a qualitative approach. Data were collected via structured interviews with 14 senior management professionals from various logistics and supply chain companies. The findings reveal that, while awareness of GSCM exists, its implementation is hindered by high costs, regulatory limitations, inadequate infrastructure, and a lack of shared understanding or strategic prioritization among stakeholders, which points to a deeper organizational and policy disconnect regarding sustainability goals. Conversely, cost efficiency, brand image enhancement, and compliance with emerging regulations are identified as primary drivers of GSCM adoption. The study highlights the need for stronger government policies, financial incentives, and industry-wide collaboration to accelerate the adoption of sustainable supply chain practices. These insights contribute to both theoretical discussions on sustainable supply chain management and practical strategies for improving GSCM implementation in developing economies. Full article

The sustainable development of autonomous vehicles (AVs) depends on effective collaboration among the government–industry–academia (GIA). Drawing on the Triple Helix theory, this study examines how the GIA interacts within emerging AV ecosystems at the local level. A qualitative research design was employed, including policy reviews and in-depth semi-structured interviews with key stakeholders in Suzhou’s AV ecosystem, to gain a detailed understanding of the collaborations. Our findings revealed three bottlenecks: (1) fragmented governance across administrative districts, which blurs responsibility for infrastructure investment and policy alignment; (2) short-term, project-based industry partnerships that limit knowledge spillovers and marginalize smaller local firms; and (3) limited academic engagement in R&D, despite a strong output in basic research. These factors lock the AV ecosystem into a hybrid configuration between government-led (Triple Helix I) and industry-driven (Triple Helix II) models, constraining sustained innovation. The study argues that to strengthen the AV ecosystem, it is essential to establish a cohesive policy framework, promote cross-sector collaboration, and involve academia more deeply in addressing social, ethical, and regulatory concerns. This paper contributes to the GIA and Triple Helix literature by offering insights into the complexity of collaboration within a rapidly developing AV sector and providing recommendations for enhancing the effectiveness of GIA collaborations to foster sustainable AV development. Full article