Search Results (5,872)

Artificial intelligence (AI) serves as a vanguard technology in the modern epoch, playing an essential part in fostering ecological and sustainable progress. By utilizing longitudinal data from Chinese A-share corporations between 2014 and 2023, this inquiry empirically explores how AI integration affects the green innovation bubbles of firms along with the governing mechanisms. Our evidence reveals that AI adoption exerts a significant inhibitory effect on such bubbles; for every one-standard-deviation uptick in AI utilization, there is a corresponding decline in green innovation bubbles of approximately 0.108 standard deviations. This finding remains robust across multiple robustness checks. Mechanism analysis shows that AI mitigates green innovation bubbles by enhancing green total factor productivity and reducing excessive managerial expenses. Furthermore, the expansion of the digital financial landscape and the exploitation of information assets bolster the repressive influence of artificial intelligence. Analytical tests for heterogeneity demonstrate that this influence is more significant for state-controlled corporations, businesses operating in non-polluting industries, and those headquartered within the eastern regions of China. Overall, the findings provide robust empirical evidence that AI adoption contributes to the governance of inefficient and inflated green innovation activities, while the causal interpretation of the results should remain cautious given the observational nature of the data and the limitations of the identification strategy. Full article

Social enterprises (SEs) in Malaysia face persistent challenges in achieving financial sustainability and scalable impact despite increasing policy support and stakeholder involvement. This study examines how internal drivers (digitalization and earned-income generation) and external drivers (government support and stakeholder engagement) influence SE performance, with social innovation acting as a mediating mechanism. A sequential mixed-method approach was employed, combining focus group discussions with 155 accredited SEs and quantitative analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that digitalization and stakeholder engagement have significant positive effects on SE performance, while earned-income generation demonstrates a negative direct relationship. Social innovation emerges as the strongest predictor of performance and significantly mediates the relationships between key organizational drivers and performance. In contrast, government support does not exhibit a significant direct or indirect effect. These findings highlight the critical role of social innovation as a capability that transforms resources into performance outcomes. This study contributes to the literature by advancing a capability-based explanation of SE performance in emerging economies and provides practical insights for strengthening innovation-driven strategies among social enterprises. Full article

A recurring challenge in the development of information systems (ISs) across complex organizational domains is the lack of integration and alignment between strategic, tactical, and operational levels, resulting in methodological fragmentation that constrains traceability, innovation, and organizational value generation. This study proposes and applies to the Integrated Innovation Framework for Information System Development (IIF-ISD) to overcome this gap. The research was structured through a systematic literature review, following the PRISMA and ROSES protocols, and validated through an exploratory single-case study involving the development of an IS supporting the Selo Casa Azul (SCA) environmental certification process in a Brazilian construction company, a context chosen for its multi-level organizational complexity and ESG compliance requirements, representative of broader certification IS development challenges. The framework integrates DSRM, agile methodologies, Design Thinking, and Lean Startup through three governing principles—Hierarchical Embedding, Functional Complementarity, and Traceability by Design—achieving cross-level alignment between strategic objectives, tactical performance monitoring, and operational execution. Empirical evaluation (n = 9; 14 weeks) yielded SUS scores of 76.8–82.1/100, a 76% reduction in data entry error rates, and a 78% stakeholder engagement rate, providing initial support for the framework’s practical effectiveness. Full article

Background: Microbiome-oriented therapies, including fecal microbiota transplantation (FMT), phage therapy, and live biotherapeutic products (LBPs), represent a promising direction in modern biomedicine for addressing antimicrobial resistance (AMR), recurrent Clostridioides difficile infection (rCDI), and dysbiosis-associated conditions. Despite encouraging clinical outcomes, their integration into routine clinical practice remains limited due to regulatory heterogeneity and unresolved ethical challenges. Objective: This review aims to analyze international regulatory approaches to microbiome-based therapies and to identify key bioethical issues associated with their clinical application. Main content: The paper summarizes current scientific evidence and regulatory frameworks governing microbiome therapies in the United States, the European Union, Ukraine, and selected Asia-Pacific countries. Particular attention is given to differences in classification, approval pathways, and safety requirements. The review also examines major ethical concerns, including informed consent, donor screening, biosafety, data protection, and equitable access to innovative treatments. Conclusions: The analysis demonstrates that microbiome therapies have significant potential for improving clinical outcomes and supporting antimicrobial stewardship. However, their broader implementation requires the harmonization of regulatory frameworks, strengthening of biosafety standards, and development of clear ethical guidelines. International cooperation and accumulation of clinical evidence are essential for the safe and effective integration of microbiome-based interventions into healthcare systems. Full article

Government data governance has become an important institutional mechanism for reducing information frictions, improving data-resource allocation, and supporting firm innovation in the digital economy. However, whether government data governance can promote firms’ technological catch-up remains insufficiently understood. Based on the quasi-natural experiment of the establishment of Big Data Administrations, this study constructs a multi-period difference-in-differences model to examine the impact of government data governance on firms’ technological catch-up. Using panel data from Chinese A-share listed firms from 2011 to 2021, the DID estimates indicate that the establishment of Big Data Administrations significantly improves firms’ technological catch-up. This estimated effect remains robust across placebo tests, specifications controlling for differential trends associated with pre-treatment city characteristics, and double/debiased machine learning estimation. Mechanism analyses provide evidence consistent with three channels: technology stimulation, digital-ecosystem optimization, and competition strengthening. Heterogeneity analyses further show that the effect is evident among non-state-owned enterprises, firms with higher information asymmetry, and larger firms. Additional spatial analyses suggest that neighboring cities’ data governance capacity does not generate stable positive spillovers; instead, it may be associated with negative spatial externalities, potentially reflecting siphoning or competitive crowding-out pressures. These findings highlight government data governance as an institutional driver of firm technological progress and provide policy implications for improving digital governance capacity, optimizing digital ecosystems, and promoting high-quality development. Full article

The transition towards sustainable, resilient and digitally integrated port ecosystems has increased the need for collaborative innovation approaches capable of supporting broader sustainability transitions. In this context, open and sustainable innovation (OSI) offers a strategic mechanism for integrating economic, environmental and social objectives within complex maritime ecosystems. Although previous studies have explored technological innovation and isolated sustainability initiatives in ports, limited empirical attention has been given to how stakeholders perceive OSI and how its implementation is operationalised across a national port system. This study addresses this gap by investigating the central research question: how do key stakeholders perceive and implement OSI practices within the Portuguese port system? Specifically, it analyses organisational culture, governance structures, stakeholder engagement mechanisms, institutional barriers and sustainability-oriented innovation practices. The research adopts a qualitative approach based on ten semi-structured interviews with representatives of five Portuguese port authorities occupying senior management and strategic positions. The findings show that OSI is widely recognised as important for competitiveness, sustainability performance and alignment with transition agendas, but its implementation remains uneven across ports. Organisational resistance, fragmented governance, regulatory complexity and limited monitoring mechanisms constrain the institutionalisation of OSI practices. Nevertheless, collaborative initiatives involving universities, innovation networks, public–private partnerships and digital platforms indicate a gradual shift towards more integrated and participatory governance models. The study concludes that OSI can support sustainability transitions in port ecosystems when enabled by coordinated governance, stakeholder collaboration and organisational capabilities. Full article

Artificial Intelligence (AI) adoption has emerged as a critical priority for governments globally, driven by its transformative potential in improving public service delivery, governance efficiency, and innovation ecosystems. Despite this, substantial disparities exist in AI readiness and adoption levels across countries, necessitating an in-depth exploration of the factors influencing AI adoption. This study leverages data from the Oxford Insights Government AI Readiness Index to model cross-country patterns of government AI readiness through clustering, regression, classification, and explainable machine learning. A Random Forest regression model was first used to estimate the 2024 AI Government Readiness score using lagged 2023 indicators. However, because the dependent variable is a composite index constructed from conceptually related dimensions, this model is interpreted as a lagged score-approximation and benchmarking exercise rather than as an independent forecasting model. The main analytical contribution lies in the clustering-classification framework, which identifies four country-level AI readiness profiles and evaluates the indicators that most strongly distinguish countries across low, moderate-low, intermediate, and high readiness groups. SHAP and permutation-based interpretation methods are used to examine feature contributions, while recognizing that these results indicate model contribution rather than causal effects. The findings underscore the multifaceted nature of AI readiness, emphasizing the interplay between governance, digital infrastructure, and technological investment. Full article

The integration of environmental sustainability (ES) into strategic planning (SP) has become more vital in the tourism and hospitality (T&H) sector, due to its significant reliance on natural resources and environmental quality. This study seeks to analyze how ES is systematically integrated into strategic planning processes, identify critical dimensions and challenges, and evaluate the degree of organizational awareness and strategic focus on sustainability. A systematic literature review was conducted using the Scopus and Web of Science databases, covering global studies published between 2024 and 2025, resulting in a final sample of 43 articles. A hybrid deductive–inductive methodology was employed to integrate the data. The findings indicate that ES integration is a complex and iterative process involving governance and leadership, strategic development, resource and environmental management, stakeholder involvement, performance assessment, and the application of analytical and technological instruments. The results also emphasize emergent aspects such as digital innovation and adaptive planning. Despite this advancement, implementation is inconsistent due to capacity limitations, fragmented governance, data deficiencies, and environmental–economic trade-offs. The study illustrates a distinct convergence between ES and SP, signifying a transition towards integrated, evidence-based, and adaptable strategic systems. The study enhances the literature by delivering a thorough synthesis of integration mechanisms and presents practical insights for promoting sustainable strategic planning in the T&H sector. Full article

The primary objective of this article is to examine the organizational, economic, and sustainability-related implications of implementing artificial intelligence (AI) systems in small and medium-sized enterprises (SMEs) in Poland. The study combines a survey of 112 SMEs in the Kuyavian–Pomeranian region, including 70 AI-using firms, with 13 in-depth interviews with managers. The quantitative analysis applies logit models to identify determinants of perceived AI effects on internal processes: working time and workload reduction, automation, cost effects, and creativity. The qualitative component explains how AI is adopted and embedded in business practice. The results show that AI adoption in SMEs is increasingly common but remains uneven and mostly operational. The strongest effects concern workload reduction and time efficiency, particularly in service firms and where AI is used intensively. Advanced AI adoption increases the probability of perceiving workload and cost-related effects. However, these effects should not be interpreted simply as direct cost reduction. Rather, AI improves productivity and work capacity while creating new costs related to paid tools, data preparation, integration, output verification, and governance. The interviews show that AI implementation follows a staged path: from curiosity-driven experimentation, through cognitive work augmentation, to workflow integration and, in selected cases, AI-enabled business model innovation. The transition from ad hoc use to strategic implementation depends less on firm size alone and more on process maturity, capabilities, and data readiness. Barriers also change with maturity: early-stage firms face a lack of knowledge, time, and clear use cases, whereas advanced users encounter data quality, hallucinations, security, integration, and governance problems. The study finds that sustainability considerations, particularly environmental impacts and ESG-related implications of AI, remain largely unperceived in SME decision-making. Entrepreneurs primarily interpret sustainability through the lenses of organizational resilience, long-term competitiveness, adaptability, and responsible digital transformation rather than through formal environmental metrics. The findings suggest that SME managers should implement AI gradually, link adoption to measurable process-level outcomes, and invest in AI literacy and governance. They should also integrate responsible AI principles into organizational strategy to support sustainable digital transformation. The study contributes to the literature by showing that AI adoption in SMEs should be understood not only as a productivity-enhancing process but also as a broader organizational transition shaping long-term sustainability and resilience. Full article

The transition towards carbon-neutral construction materials requires innovative solutions that combine reduced embodied energy, enhanced durability and improved building energy efficiency. This study investigates and compares two novel bioaerated low-density composites—BAAC and BIOAERMAC—developed through biologically driven aeration processes incorporating industrial byproducts. BAAC is produced using Saccharomyces cerevisiae and hydrogen peroxide, replacing conventional aluminum powder and improving safety while enabling the valorization of waste-derived yeast. BIOAERMAC is a gypsum-based composite incorporating synthetic anhydrite, microorganisms, peroxides, and recycled rubber from end-of-life tires. The materials were characterized in terms of hygrothermal behavior and dimensional stability, and compared with commercial autoclaved aerated concrete under equivalent mechanical strength conditions. The results highlight significant differences in moisture transport and shrinkage, primarily governed by pore structure and connectivity. BAAC exhibits behavior comparable to conventional AAC, whereas BIOAERMAC shows reduced capillary and hygroscopic absorption, indicating limited pore connectivity, but higher drying shrinkage. These findings demonstrate the effectiveness of bioaeration in tailoring pore structure and controlling the trade-off between moisture transport, durability, and dimensional stability, highlighting the potential of bioaerated composites for low-carbon and energy-efficient building applications. Full article

This article examines how artificial intelligence (AI), conceptualized as a general-purpose technology (GPT), shapes economic growth and structural transformation through a structured literature review covering the period from 2015 to 2025. The study adopts a structured, mechanism-oriented synthesis approach grounded in transparent search, screening, and thematic classification procedures rather than formal meta-analytic protocols. It develops an integrative innovation ecosystem framework that links three core transmission channels: (i) total factor productivity (TFP), (ii) task reallocation and labor-market restructuring, and (iii) innovation and knowledge-generation dynamics. The findings indicate that AI adoption does not generate uniform or automatic growth effects. Empirical evidence remains heterogeneous, and estimates of AI’s macroeconomic contribution vary across institutional and structural contexts. In most cases, outcomes depend less on the technology itself and more on complementary conditions—human capital formation, digital and data infrastructure, institutional coordination, and governance capacity—that enable effective diffusion. Interpreting task-based automation models alongside endogenous-growth and open-innovation frameworks clarifies why similar AI investments may lead to divergent structural outcomes. Rather than proposing a deterministic growth model, the study advances a conditional and ecosystem-centered interpretation of AI-led development. The study contributes by distinguishing foundational theoretical perspectives from the contemporary 2015–2025 evidence base, clarifying the relationship between task transformation and structural transformation, and emphasizing institutional complementarity as the key mechanism shaping AI-driven growth outcomes. Full article

The open sharing of data as a factor of production is an important institutional mechanism for promoting sustainable innovation in the digital economy. Using Chinese A-share listed firms as the research sample and exploiting the staggered rollout of government open data (GOD) platforms across prefecture-level cities as a quasi-natural experiment, this paper constructs a staggered difference-in-differences (DID) model to examine the effect of GOD on green collaborative innovation (GCI) and its underlying mechanisms. The results show that GOD significantly promotes GCI, indicating that open government data can help firms strengthen collaboration in green innovation and contribute to more sustainable development. Mechanism analysis shows that GOD promotes GCI through four channels: increasing government subsidies, reducing information asymmetry, raising public environmental awareness, and advancing corporate digital transformation. Heterogeneity analysis reveals that the innovation-promoting effect of GOD is more pronounced in large cities, non-resource-based cities, and southern cities, and is more salient among state-owned enterprises, capital-intensive firms, and mature firms. This paper provides empirical evidence on the microeconomic effects of market-oriented data allocation and highlights the role of GOD in supporting GCI, corporate sustainable transformation, and the sustainable development of the digital economy. Full article

Acid mine drainage (AMD) pollution from closed coal mines in karst regions represents a major environmental challenge in the global mining industry. The complexity of hydrogeological conditions in such regions leads to significant challenges in both predictability and controllability of pollution. Taking the Yudong River Basin in Guizhou Province, Southwest China, as the study area, and based on six years (2017–2023) of systematic remediation practices and monitoring data, this study systematically evaluates the effectiveness and applicable conditions of three types of treatment technologies: centralized treatment stations, source control combined with end-of-pipe treatment, and water-sealing ecological plugging. On this basis, governance models applicable to karst regions are distilled. The results show that after six years of remediation, the number of pollution points in the Yudong River Basin decreased from 27 to 12. At the outflow section, the total Fe reduction rate reached 88.3%, the total Mn reduction rate reached 62.3%, and the proportion of contaminated river length was reduced by 78.5%. Each of the three technologies has its own applicable conditions. Centralized treatment stations, characterized by mature technology but high operational costs, are suitable for emergency transition periods. Source control combined with end-of-pipe treatment addresses both symptoms and root causes, making it applicable to complex pollution points. Water-sealing ecological plugging, although cost-controllable, carries a risk of secondary pollution in karst-developed areas. The failure of water-sealing ecological plugging technology is mainly attributed to two mechanisms: bypass flow through karst conduits and overflow induced by water level rise. Based on the six-year remediation practice, this study proposes a source control model for karst conduits centered on the core concepts of “filling, isolating, plugging, intercepting, draining, and controlling”. The implementation process consists of four stages: detailed investigation, graded optimization, stepwise implementation, and long-term monitoring. The core innovation lies in the cross-disciplinary application of coal mine water control techniques to environmental remediation, achieving a shift from passive end-of-pipe treatment to active source control. This model can provide theoretical reference and practical guidance for karst mining areas in Southwest China and other regions with similar geological conditions. Full article

In order to promote the coordinated development of land use and energy equity, this study empirically examines the impact of land use on energy equity and its underlying mechanisms, using panel data from prefecture-level cities in China. The main findings are as follows: (1) An increase in land use intensity significantly hinders the development of energy equity. After a series of robustness checks and endogeneity treatments, this conclusion is still reliable. (2) Population agglomeration, energy consumption intensity, green innovation, and government intervention are the main pathways through which land use affects energy equity. (3) Small and medium-sized cities, resource-based cities, eastern China, and areas north of the Hu Line are where this negative effect is primarily concentrated. These results offer important policy recommendations for the coordinated governance of land use and energy equity. Full article

Lithium has become one of the key raw materials for the energy transition due to the central role of lithium-ion batteries in electromobility, energy storage, and the integration of renewable energy sources. However, the rapid increase in demand reveals growing environmental, social, geopolitical, and market tensions. The aim of the paper is a critical synthesis of global lithium utilization from the perspective of challenges, technological innovations, and integrative strategies supporting a more sustainable material–energy system. A broad, systematic literature review covering the entire value chain was applied: resources, extraction, processing, end-use applications, second life of batteries, recycling, and governance. The analysis shows that the strategic importance of lithium arises from the increasing demand pressure from electric vehicles and stationary storage, while the sustainability of the current model is constrained by supply concentration, uneven control over downstream stages, the water–carbon footprint of extraction and processing, social conflicts, and incomplete integration of secondary loops. At the same time, innovations such as direct lithium extraction (DLE), recovery from geothermal brines, design for recycling, second life, and battery passports can partially alleviate these tensions, but they do not eliminate the need for primary supply in the short term. The conclusion of the work is that sustainable global lithium utilization requires simultaneous diversification of sources, development of circular value chains, and multi-level governance integrating resource security, environmental efficiency, and social legitimacy. Full article