Search Results (734)

The digital economy has become an emerging driver of rural industrial revitalization. Based on an input-output model and a production-network framework, this study first constructs time-series input-output tables for the digital economy and urban-rural industries from 2002 to 2021. It then identifies key recipient nodes, urban-rural disparity paths, and priority optimization paths of digital value flows. The results show that urban-rural disparities in digital empowerment have narrowed, but the digital divide between urban and rural industries remains substantial. The direct integration of the digital economy into rural industries is still limited, whereas urban-rural industrial integration plays an important mediating role. At the same time, the urban-rural disparity paths in digitally enabled rural industrial revitalization are mainly concentrated in rural capital allocation, asset services, circulation systems, basic agricultural production, and agricultural science and technology services. The counterfactual simulations show that prioritizing the direct embedding of the digital economy into rural manufacturing, agricultural value chains, and public-service sectors, while improving coordinated transmission between urban and rural industries, can strengthen the overall empowerment effect. These findings provide empirical support for more precise and targeted policies to promote rural industrial revitalization through the digital economy. Full article

Hydrogen is increasingly recognized as a key energy carrier for decarbonizing hard-to-electrify sectors, yet more than 95% of current global production remains fossil-derived. Biological hydrogen (biohydrogen) produced by dark fermentation (DF), photo-fermentation (PF), or microbial electrolysis cells (MEC) offers the dual advantage of valorizing organic wastes while delivering low-carbon H₂; however, none of these standalone technologies mobilizes more than 25–33% (DF), 40–70% (PF), or 40–60% (MEC) of feedstock organic carbon through H₂-producing oxidation pathways. Most existing reviews compare these pathways on hydrogen yield alone, a metric that conceals where the majority of feedstock carbon and electrons are actually lost and obscures the quantitative rationale for system integration. This review reframes the comparison around carbon and electron flow, explicitly tracking how much input carbon is mobilized through H₂-producing oxidation pathways, how much is retained in volatile fatty acids (VFAs), biomass, or unlinked CO₂, and what happens to the associated electrons. Stoichiometric, mechanistic, and reactor-level evidence is synthesized to show that DF channels only 25–33% of input organic carbon through H₂-yielding decarboxylation on real heterogeneous substrates, with 40–60% retained as residual VFAs and unhydrolyzed solids; PF can recover 60–80% of VFA carbon but is constrained by photon economics and nitrogenase sensitivity; and MEC achieves >85% COD removal only when coupled to an upstream acidogenic stage. Two-stage (DF–PF, DF–MEC) and three-stage (DF–PF–MEC, DF–MEC–AD) configurations are critically evaluated, with theoretical yields separated from experimentally demonstrated performance on real wastes and hidden energy inputs (pretreatment, inter-stage transfer, gas separation, and compression) explicitly accounted for. DF–MEC coupling is identified as the most near-term tractable configuration, achieving 55–70% H₂-pathway carbon mobilization and 80–92% COD removal at an electrical input of 0.9–1.5 kWh/m³ H₂, with levelized hydrogen costs of US$3–5.5/kg under favorable waste-tipping-fee conditions. Multi-stage systems push carbon recovery above 70% but carry unresolved capital, methanogenesis control, and scale-up penalties. This review closes by proposing a standardized ten-descriptor reporting framework including H₂-pathway carbon mobilization (%), cathodic hydrogen recovery (rCAT), net energy recovery (NEB), and LCA carbon intensity under both attributional and consequential boundaries, and demonstrates its backward compatibility by retrospective application to seven studies already in the literature. Research priorities tractable on a 5–10 year horizon are identified, centered on methanogen suppression at pilot scale, real-waste MEC performance, and renewable-electricity coupling. Full article

The paper investigates the evolution of earnings management across corporate life-cycle stages and evaluates the moderating role of leverage within an emerging market context. Utilising a dataset of 273 non-financial firms listed on Vietnamese stock exchanges over the 2012–2022 period (3003 firm-year observations), we delineate life-cycle phases—introduction, growth, maturity, and decline—using net cash flow patterns. Earnings quality is proxied via diverse discretionary accrual models. Methodologically, the study employs fixed-effects regressions with firm-clustered standard errors, incorporating interaction terms to capture stage-specific leverage dynamics. The empirical evidence reveals a non-linear and stage-dependent trajectory of earnings management, with introduction- and decline-stage firms exhibiting higher discretionary accruals compared to benchmarks. Crucially, the institutional impact of debt financing is contingent upon corporate maturity; while leverage exhibits a baseline positive association with earnings management, this relationship diminishes or reverses during the introduction and decline phases. These insights withstand rigorous robustness checks, including different discretionary accrual models and alternative life-cycle classifications. This study advances current literature by integrating capital structure into the corporate life-cycle framework, demonstrating that leverage effects are dynamic and shaped by shifting financial constraints and monitoring environments. Ultimately, the findings offer valuable insights into financial reporting incentives in emerging markets characterised by concentrated ownership and transitional corporate governance, yielding critical implications for regulators, investors, and auditors. Full article

Forecasting foreign exchange rates over long time periods depends on economic fundamentals. Short-term predictions, by contrast, depend largely on emotions, governmental announcements, the flow of capital, and media commentary. This paper proposes a suite of methods, collectively referred to as ForExAI, to predict foreign exchange rates based on time series analysis and news article analysis. The time series analysis is based on classical statistical time series techniques, such as ARIMA, as well as machine learning methods using neural networks. Separately, ForExAI uses Large Language Models to analyze news articles based on two kinds of prompts: (i) expert-written based on econometric considerations, (ii) existing prompts documented in the literature. Our findings on time series of exchange rates indicate that there are signals in the time series that can be captured even by simple methods like ARIMA(1,1,1), as well as novel machine learning methods on the time series of foreign exchange rate trades. Further, an adaptation of the Kelly criterion can increase cumulative profits. Finally, an ensemble approach often delivers slightly lower profit, but also lower volatility, leading to a higher Sharpe ratio. Regarding news article analysis, shorter prompts yield far better results than complex ones derived from expert knowledge. This work shows a method for hyperparameter tuning a collection of models that forecast complex time series, as well as the relative virtues of different versions of the Kelly criterion. The results make a pragmatic contribution as well. Because we measure profits ignoring transaction costs, our work is not directly actionable by traders, but the insights could be useful. In addition, our results point to further areas of research for traders. Full article

The construction sector continues to experience elevated levels of insolvency, driven by an interplay of structural vulnerabilities and macroeconomic pressures, including supply chain disruptions and cost inflation. These challenges have been particularly prominent in Australia, especially among micro and small construction firms, which account for over 90% of reported insolvency cases. In 2024, the Australian construction sector contributed nearly one-quarter of all company insolvencies nationally. This study undertakes a comprehensive review of construction insolvency research, synthesising key themes, causes, early warning indicators, and mitigation strategies, while contextualising global insights using empirical evidence from the Australian construction sector. The methodology integrated systematic literature screening, scientometric analysis, and critical thematic synthesis with a descriptive and selective statistical examination of the Australian Securities and Investments Commission (ASIC) data, complemented by practice-informed insights. The review identified dominant research trajectories, centred on financial risk management, insolvency prediction models, project-level cost and governance risks, and emerging data-driven approaches. Empirical analysis revealed that inadequate cash flow (~16–20%), poor strategic management (~12–18%), and weak financial controls (~11–15%) consistently rank among the leading causes of construction firm failure over the last decade. Indicators such as non-payment of statutory obligations and deteriorating working capital are observed in over half of insolvency cases, highlighting persistent structural fragility. Although global strategic focus areas emphasised financial monitoring and early warning systems, practice-informed findings indicated that effective mitigation requires their operationalisation through capability development, early intervention tools, regulatory oversight, and stakeholder-informed support mechanisms. The study shows how global insolvency risk concepts align with Australian regulatory evidence and highlights the need to translate early-warning approaches into accessible tools and support mechanisms for micro and small construction firms. Full article

Thorium (Th) is increasingly considered a promising fertile material for sustainable nuclear energy—which is not fissile itself, but convertible to fissile ²³³U—particularly as a by-product of rare earth element (REE) processing. This study develops a parametric techno-economic assessment (TEA) framework synthesizing published data from China, Russia, the USA, India, and Europe to establish the methodological foundation for evaluating thorium recovery economics from monazite ores and REE tailings under Central Asian conditions. Monazite typically contains 4–12% ThO₂, while tailings contain 0.1–3%, making secondary resources attractive for future recovery strategies. Particular attention is given to integration with uranium tailings and the application of advanced materials such as nanocomposite sorbents and carbon-based electrodes. Reported production costs of ThO₂ range from 50 to 500 USD/kg depending on process scale, feedstock quality, and co-production of REEs. The reviewed studies consistently show that coupling thorium recovery with REE processing improves economic feasibility. Modern approaches, including hybrid technologies and electrosorption systems, may reduce operational costs and improve process efficiency. Despite challenges related to capital investment, market uncertainty, and radioactive waste management, thorium continues to attract growing interest as a potential component of future nuclear fuel cycles and advanced reactor systems, including small modular reactors. To the best of the authors’ knowledge, this is the first parametric TEA framework structured around Central Asian conditions, combining literature-derived regional data, scenario-based process economics, and Monte Carlo sensitivity analysis within a single discounted cash flow structure. Full article

Climate change and low-carbon transition policies affect sustainable development by changing firms’ financing costs and investors’ capital allocation. This paper investigates whether and how climate-related information is priced in China’s equity market, focusing on firm-level carbon intensity and exposure to climate policy uncertainty (CPU). First, univariate-sorted portfolio tests confirm the existence of a carbon premium, as firms with high carbon intensity earn significantly higher average returns. However, the unconditional relation between CPU exposure and stock returns is insignificant. Bivariate-sorted portfolios reveal a strong interaction between the carbon premium and the CPU premium. The carbon premium is higher for firms with high exposure to CPU, whereas a significant and negative CPU premium appears among low-carbon firms and, in sector-level tests, is concentrated in non-energy firms. Further analysis demonstrates clear differences between energy and non-energy sectors, which may be attributable to cash flow risks and uncertainty in growth options. The findings contribute to climate-related asset pricing and sustainable finance research by showing that transition-risk pricing depends on the interaction between carbon exposure and policy uncertainty. Full article

Corporate balance sheets report aggregate equity and liability totals but conceal the internal allocation of financing sources across asset categories—an identification problem that conventional econometric methods cannot resolve without additional parametric assumptions. This paper develops a maximum entropy (ME) panel estimator to recover two latent scalar parameters: x ∈ (0,1), the share of equity capital directed toward long-term asset financing, and y ∈ (0,1), the corresponding debt allocation share. Grounded in maximum entropy principle, the estimator selects the unique parameter vector that satisfies the mean-level balance-sheet constraint while maximising joint Shannon entropy—the least-biassed solution consistent with observable data. The closed-form logistic representation yields a scalar Lagrange multiplier λ*, interpreted as a financing pressure index, recoverable via bisection in at most 21 iterations at tolerance ε = 10⁻⁵. Building on the ME estimates, we introduce a continuous matching alignment index M* = x* − y* that measures the degree of compliance with the financial matching principle along a continuous spectrum rather than as a binary categorisation. Applied to a ten-firm, cross-sectoral panel spanning Technology, Finance, Energy, and Automotive sectors over an observation window spanning 2001 to 2025 (with firm-specific subperiods reflecting differences in IPO dates and data availability), the framework reveals substantial heterogeneity in latent financing flows: equity allocation shares range from 30.1% (NVIDIA) to 75.1% (ExxonMobil), while debt allocation shares span 37.1% to 77.5%. Across the panel, only Meta exhibits substantial positive matching alignment, while Microsoft, ExxonMobil, Apple, and Tesla show only very slight differences that fall within the neutral band, and the remaining firms show varying degrees of structural departure from the matching benchmark; the thresholds used to summarise these descriptive labels are interpretive aids rather than re-imposed binary criteria, and the substantive ranking of firms along M* does not depend on the specific threshold values adopted. The ME solution’s entropy H(x*, y*) and the normalised diversification index D(x*, y*) describe allocation balance under the estimator’s information–theoretic criterion rather than independently observed firm complexity; in the present sample, the cross-firm ordering of these values is not recovered by firm size, leverage, or sector classification alone. These findings, based on a ten-firm case-study panel with time-invariant allocation parameters, should be interpreted as descriptive patterns of the present sample rather than statistically validated regularities. They provide a theoretically rigorous and computationally tractable identification of unobservable corporate financing flows, with potential implications for capital structure theory, financial risk assessment, and balance sheet analysis that would benefit from validation on larger and more representative samples in future work. Full article

Traditional olive groves are widely recognised as providers of landscape, environmental and cultural public goods in Mediterranean rural areas, but their long-term economic viability remains uncertain. This study assesses the income gap between traditional, intensive and super-high-density (SHD) olive-growing systems in a representative hill olive-growing area in Tuscany (central Italy), characterised by physical and structural conditions typical of traditional Mediterranean systems. Using a discounted cash-flow framework, the analysis compares long-term financial performance through standard investment appraisal indicators and uses the Equivalent Annual Value (EAV) as a policy-relevant benchmark for calibrating support. The results reveal a clear structural divergence: while intensive and SHD systems achieve higher profitability and faster capital recovery, the traditional system exhibits a persistent income disadvantage under market conditions. The estimated EAV gap amounts to approximately 950 €/ha relative to the intensive system and 3104 €/ha relative to the SHD system—values that represent the additional annual support required to preserve traditional olive groves and prevent abandonment. These values can also be interpreted as the annual private opportunity cost of maintaining traditional olive landscapes rather than converting them to more financially competitive systems. Break-even analysis further shows that the traditional system requires an oil price of at least 9.6 €/kg to achieve economic viability without public support, compared to 6.97 €/kg and 4.13 €/kg for the intensive and SHD systems, respectively. The findings highlight a structural misalignment between private profitability and social value, suggesting that the conservation of traditional olive landscapes cannot rely on market mechanisms alone and requires targeted, evidence-based policy instruments. Full article

E-commerce has reshaped short-term financial management by altering transaction speed, payment structures, and supply chain coordination. This study examines how large publicly listed e-commerce firms, viewed as complex digital business systems, adjusted their working capital policies during and after the COVID-19 shock. The sample is based on the 100 largest e-commerce companies worldwide by market capitalization, as reported by CompaniesMarketCap (February 2026), and is reduced to 76 firms from 23 countries due to data availability, yielding 802 firm-year observations. Firm-level data are obtained from LSEG Datastream, while macroeconomic variables are sourced from the World Bank. The analysis distinguishes between two dimensions of working capital: flow-based operational adjustment, measured by the cash conversion cycle (CCC), and stock-based balance-sheet adjustment, captured by net working capital relative to total assets (WC/TA). Fixed-effects models with firm-clustered standard errors are employed. The results indicate a substantial contraction of the CCC during the pandemic, followed by partial persistence of that contraction rather than a return to pre-pandemic norms. In contrast, WC/TA remains broadly stable during the crisis but declines in the post-pandemic period, suggesting a delayed balance-sheet adjustment. Business-model heterogeneity is not statistically significant, which may reflect a common system-level response across e-commerce firm types. Leverage and supply-chain pressures are associated with working capital intensity (WC/TA), while inflation shapes operate cycle duration (CCC). The findings are consistent with a two-stage adaptive response to systemic disruption. Full article

Decarbonizing heavy-duty road transport requires comparing zero-emission options to guide infrastructure investments along strategic corridors. This study develops a scenario-based techno-economic model to evaluate hydrogen fuel cell trucks (HFCTs) and battery electric trucks supported by dynamic wireless power transfer (DWPT) on a 100 km segment of Italy’s A4 motorway in 2030 and 2050 scenarios. The framework integrates traffic flows, vehicle archetypes, infrastructure sizing, and end-to-end energy chains (power-to-hydrogen-to-wheel for hydrogen and grid-to-wheel for WPT) to estimate capital and operating costs, efficiencies, and energy demand. Results show that hydrogen refueling infrastructure requires lower initial investment (approximately €60 million CAPEX and €20 million annual OPEX) than wireless charging systems (€80 million CAPEX and €15 million OPEX). However, WPT achieves significantly higher grid-to-wheel efficiency (96% vs. 62%) and lower per-vehicle energy demand (18 MWh/year vs. 25 MWh/year). These findings highlight a fundamental trade-off: hydrogen solutions offer operational flexibility and are better suited to long-haul or low-density contexts, while WPT systems are more efficient and become increasingly competitive in high-traffic corridors with high infrastructure utilization. Overall, the results suggest that no single technology universally dominates and that optimal deployment depends on traffic density, infrastructure usage, and system integration. A combined implementation of hydrogen and wireless charging technologies may provide the most effective pathway to balance efficiency, flexibility, and cost in future heavy-duty transport systems. Full article

Recirculating organic byproducts like food waste, wastewater and manure efficiently and at scale in a circular bioeconomy will be critical to ensuring future food security, energy security, climate resilience, water security and environmental health. Ultimately, we will not be able to live within the safe operating space of our planetary boundaries if we do not stop our wasteful and inefficient habits. Our food, waste, energy and water sectors are starting to transform towards circularity, driven by a diverse range of drivers, from net zero emissions targets, to food waste policies, and to rising fertiliser prices and geopolitical risks. However, these sectors are often not transforming in a coordinated manner, risking unintended consequences like competition between end-uses, technology lock-in, the prevention of scalability, or failure to achieve key sustainability targets, causing rebound effects. For example, society’s organic waste is being earmarked for the production of bioenergy, sustainable aviation fuels, biomaterials, and biofertilisers; however, it is not clear if there will be a sufficient supply of organic waste to meet these diverse demands. Phosphorus flow analyses indicate that we will need to secure almost all of the nutrients in organic waste as fertiliser raw material to produce food. There are some existing pockets of innovation within sectors related to food waste, water and wastewater, fertilisers and agriculture, and bioenergy. However, many initiatives are being driven by short-term challenges, are not operating at scale, or are not sufficiently integrated across sectors. In this paper, we provide examples of innovations and challenges from around the world, including Italy, Australia, Sri Lanka, the UK, Japan, and Malawi. This paper identifies a pathway to navigate tensions to achieve co-existing sustainability goals, including key enablers and barriers, ranging from overcoming regulatory fragmentation to a lack of capital investments. Creating a truly viable circular economy for organic byproducts requires the integration of policies, markets, technologies and people. This means engaging diverse stakeholders, from local councils and private waste contractors, farmers, and fertiliser companies to energy retailers and wastewater utilities, NGOs, informal collectors, and environmental regulators and policy-makers. Full article

The concept of virtual water is currently one of the most important issues in water resource management, especially in a context marked by structural water scarcity. Beyond the analysis of virtual water flows, which has been widely studied in the literature, this study aims to better understand the relationship between virtual water exports and economic growth. This paper analyzes the dynamic relationship between Morocco’s economic growth and agricultural virtual water exports to the European Union over the period of 1986–2023. An ARDL model was used based on annual data to test cointegration and estimate short- and long-term effects, controlling for gross fixed capital formation and agricultural value added. The bounds test confirms the existence of a stable long-term relationship between the variables. The results suggest that export specialization may be associated with foreign earnings and agricultural activity while also coinciding with greater pressure on resources and potential adaptation costs, especially for blue water resources. However, estimates indicate that in the long term, investment is positively and significantly associated with growth, while virtual water exports are associated with a negative effect on GDP, suggesting that export gains may be offset by increasing water constraints and sectoral trade-offs, and that agricultural value added mainly influences short-term dynamics. The results highlight the importance of integrating water footprint and virtual water trade concepts, as well as climate constraints, into agricultural and trade strategy planning while strengthening policies on water efficiency, innovation, and governance. Full article

Achieving carbon-neutral cities requires innovative strategies that integrate technological carbon capture, sustainable urban infrastructure, and proactive public engagement. While microalgae-based systems have shown promise for CO₂ sequestration and resource recovery, their scalability remains constrained by high costs and energy-intensive photobioreactor (PBR) designs. Here, we propose the retrofit of existing urban fountains into high-efficiency microalgae cultivation systems—microalgae-enhanced fountain landscapes—as an integrated solution that bridges ecological function and social outreach. This approach capitalizes on ubiquitous fountain infrastructure to minimize deployment costs, employs advanced fountain-style cultivation technology to enhance biomass productivity, and leverages strategic locations in high-footfall urban zones to actively elevate public carbon literacy and motivate low-carbon behavioral shifts through immersive engagement—a vital step toward city-wide participatory climate action. We critically analyze the feasibility of this system, highlighting its potential for multi-stakeholder value creation across developers, municipalities, and citizens. Furthermore, we synthesize recent advances in suspended microalgae cultivation, building-integrated PBRs, and microalgae-informed landscape design to contextualize the development pathway of fountain-based systems. By uniting technical efficiency with civic education, this work establishes a replicable framework for scalable urban deployment—simultaneously advancing carbon mitigation, public awareness, and circular resource flows in the transition toward climate-resilient cities. Full article

The transition to a circular economy (CE) represents a complex socio-technical evolution, requiring synchronized policy frameworks and strategic capital reallocation. Adopting a systems-thinking lens, this study combines bibliometric network mapping with exploratory econometric modelling, to examine the associations between five core policy instruments and tangible circular investments (INV_CE) across the EU-27. Bibliometric analysis identifies the “firm” and “supply chain” as central functional hubs within the CE knowledge system, acting as primary mediators for capital flows. Econometric results indicate that Tradable Permits (TPOs) and an integrated Policy Integration Index (PII), comprising subsidies and energy-based taxes, show the strongest statistical association with circular investment patterns (p ≤ 0.001). However, patterns of structural disparity emerge between OECD and non-OECD Member States (p = 0.014), where the latter often exhibit a more rigid, tax-centric approach. Spearman correlations point toward institutional maturity, specifically government effectiveness (r_s = 0.48) and eco-innovation capacity, as a potential systemic gateway for investment absorption. Furthermore, a structural decoupling appears between voluntary approaches (VAs) and governance capacity in emerging systems, suggesting that such instruments may be less effective without “institutional readiness.” The findings suggest that circular transition is path-dependent and congruent with the co-evolution of policy and institutional regimes. To bridge the investment gap, the study highlights the need for systemic interventions that move beyond “one-size-fits-all” regulations toward targeted strategies that strengthen the institutional and data reporting infrastructures of circular systems. Full article