Business, Economics and Management

Abstract: This study analyzes the short-term effects of financial development, consumption of renewable energy and carbon dioxide (CO₂) emissions in Ghana from 1990-2025. It uses the Autoregressive Distributed Lag (ARDL) method, utilizing yearly time series data; the short-term estimate of ARDL contains 33 observations. Renewable energy consumption has a negative and statistically significant effect on emissions. The estimated coefficient of -1.092 represents that as renewable energy consumption increases by 1%, CO₂ emissions decrease by approximately 1.092% if all other variables remain constant. Financial development does not have a statistically significant effect. Gross fixed capital formation and trade openness do not have a statistically significant effect. In the short run, while current GDP growth does not significantly affect emissions, the prior period's income growth is associated with a reduction in CO₂ emissions, suggesting a delayed efficiency effect.The ADF and Zivot-Andrews tests do not find stationarity for the logged variables at the level, therefore first-difference tests need to be conducted to verify integration orders and the appropriateness of ARDL bounds testing. Diagnostic tests performed on residuals did not indicate any statistically significant evidence of serial correlation, heteroskedasticity or functional form misspecification at traditional levels. These results indicate that priority should be given to deployment of renewable energy because it replaces carbon intensive generation. Financial and investment policies should be designed to encourage low carbon generation and their impact monitored. These results are conditional short-term effects and do not represent causation or long-term effects.

Abstract: Open government data (OGD) lowers the cost of accessing public-sector data, but firms differ widely in their capacity to turn such access into productivity gains. This study examines how the firm-level digital capability gap—the distance between a firm's digital transformation level and the industry–year digitalization frontier—shapes the productivity effects of OGD. We develop a production model in which the effective cost of data depends on digital capabilities and test its predictions with a staggered difference-in-differences design that exploits the rollout of city-level open data platforms, using 31,238 firm-year observations of Chinese A-share listed firms from 2011 to 2024. OGD significantly raises firm total factor productivity (TFP), but the gains shrink as the digital capability gap widens: the estimated gain for a firm one standard deviation above the mean gap is less than one-fifth of that for a firm one standard deviation below it. Mechanism analyses suggest that the gap weakens the effects of OGD on transaction costs, technological innovation, and the information environment. These results imply that the economic returns to OGD depend on firms' complementary digital capabilities, highlighting the importance of combining open-data provision with capability-building policies to support more broadly shared productivity gains.

Abstract: The debate over whether renewable energy can sustain AI growth relies on demand figures whose origin is rarely examined. We compare open, facility-level records with agency estimates for China, Japan, South Korea and the United States, using the Epoch AI GPU-cluster register (338 clusters), the International Energy Agency, Lawrence Berkeley National Laboratory, South Korea's 11th Basic Plan for Electricity Supply and Demand, and Ember generation data. In 2024, visible load covers 3.8–6.3% of agency-estimated data-centre demand in the United States, 1.4–2.3% in China, at least 0.8–1.3% in Japan and at most 2.6% in South Korea. Data-centre growth absorbs 4–34% of observed wind and solar additions under agency estimates but only 0.13–1.0% under visible load, a ratio of 31 to 53. Reference estimates for China diverge by a factor of 2.6 (100 versus 260 TWh in 2024). The verdict on whether clean power keeps pace with AI therefore depends on what can be observed: while 92–99% of the load remains invisible in open registers, no stable answer is possible. We propose a minimum reporting standard for data-centre electricity.

Abstract: Electric vehicles (EVs) can provide flexibility in peer-to-peer (P2P) markets and vehicle-to-grid (V2G) services, but participation must respect mobility needs and cover owner costs. This study compares a private EV and a taxi in an hourly model of an EV owner, prosumer, and distribution system operator. It evaluates grid-only charging, P2P smart charging, and combined P2P/V2G participation; Nash bargaining links P2P prices to wholesale conditions. The model assesses participation against an outside option, V2G compensation, cooperative allocations, fuzzy membership, and social welfare. Feasible P2P purchase prices exceed wholesale prices but remain below modeled grid-buy prices, yielding savings of €0.055/kWh for the private EV and €0.071/kWh for the taxi. P2P buying alone fails the private EV’s participation condition, whereas the combined mode passes; neither taxi mode meets its outside option. The V2G service margin is positive for the private EV but negative for the taxi. Fuzzy individual rationality holds only for the private EV at full membership and fails for the taxi throughout. Mobility-value sensitivity shifts welfare levels but not mode rankings; participation improves social welfare for the private EV but not the taxi. Therefore, P2P price advantages alone do not ensure participation; design must reflect mobility, costs, and outside options.

Abstract: Financial stability may support investment and employment, yet environmental and social progress may respond differently. This study examines how bank capital adequacy, loan portfolio quality and financial market stress relate to renewable energy, per-capita greenhouse gas emissions and employment across European Union countries. Using unbalanced panels for 2010–2024 and 2015–2024, we estimate models with country and year fixed effects; common-sample comparisons and a composite sustain-ability index are exploratory. In the primary 26-country financial-stress panel, a 0.1-point higher stress index was associated with a 0.305 percentage-point smaller annual change in the employment rate. Still, the association was not statistically significant after adjustment for three outcomes. Environmental estimates and primary bank-capital estimates were uncertain, and inference methods disagreed for installed wind capacity. Exploratory models with outcome-specific controls retained a negative stress–employment association, although its statistical significance depended on the scope of multiple-testing adjustment. The composite index reflected this pattern mainly through employment. These findings highlight a recurring association between financial stress and employment and show why environmental and social outcomes should be assessed separately.

Abstract: The twin transformation—the coordinated pursuit of smart (digital) and green (sustainable) manufacturing—has become a central agenda in manufacturing research and policy. However, existing studies operate almost exclusively at the firm level: how smart and green transformations are coordinated at the industry-chain level lacks a theoretical account, and the convergence (“ronghehua”) dimension prominent in Chinese industrial policy discourse has not been conceptualized. This article develops a conceptual framework of chain-leader-orchestrated twin transformation. It argues that chain-leader firms act as organizational intermediaries that supply chain-level public goods through four mechanisms—capability spillover, standard transmission, scenario orchestration, and factor orchestration—and that convergence, the integrative capacity spanning actors, chain stages, and chains, constitutes the organizational condition and amplifier of smart–green synergy. Three theoretical propositions are derived. Four publicly documented cases from Xi'an's manufacturing sector provide illustrative evidence. The framework extends twin transformation research from the firm to the industry-chain level and draws policy implications for inland central cities that organize industrial transformation around chain leaders and new factor endowments. Empirical testing of the propositions constitutes the agenda for future research.

Abstract: Trade unions’ capacity to engage in sustainability-related activities varies across European countries, yet comparative quantitative measures of these sustainability affordances remain limited. This data descriptor presents a dataset on the institutional, social and environmental determinants of trade union sustainability affordances in 20 European countries. The dataset was compiled from the Institutional Characteristics of Trade Unions, Wage Setting, State Intervention and Social Pacts (ICTWSS) Database and the International Social Survey Programme (ISSP) Environment modules (2010 and 2020), complemented by Organisation for Economic Co-operation and Development (OECD) data on trade union density and collective bargaining coverage. It comprises 29 indicators on collective bargaining structures, membership demographics and the environmental attitudes and behaviours of trade union members, which were normalised and aggregated into three subindices and a composite index grounded in affordance theory. The repository provides raw, processed and analysed data together with R scripts that allow the calculations to be replicated. The institutional and environmental subindices show good internal consistency (Cronbach’s alpha of 0.866 and 0.873). The dataset supports cross-country comparisons, research on organised labour in sustainability transitions and the evaluation of just transition policies.

Abstract: The prevailing perception is that the transition to renewable energy will lead to a decrease in demand for hydrocarbons and petrochemicals. The present work empirically demonstrates that this common sense may be more imaginary than real: it finds evidence that renewable energy deployment may have a positive impact on hydrocarbons through its growing demand for petrochemicals. To obtain rigorous results, we employ state-of-the-art panel time-series methods that account for the main issues in panel data (e.g., cross-sectional dependence, non-stationarity, and heterogeneity) and provide insights for individual countries. Our key finding that renewables have a positive impact on petrochemical import demand is robust across various model specifications considered in the empirical analysis. Using the polymer intensities of the renewable energy systems and the estimated elasticities of demand for petrochemical imports, the global petrochemical polymer demand to meet projected renewable energy system penetration in a net-zero emissions scenario by 2050 was quantified to be in the range of 155 to 223 million metric tons (which translates to a growth in equivalent crude oil demand of 0.80 to 1.13 million barrels per day between 2025 and 2050), depending on the energy system design preferences. Import demand, which is an opportunity for petrochemical exporters, arising mainly from growth in the economies of India and China, accounts for between 67 and 96 million metric tons of polymer materials. The insights into policymaking in the petrochemical-importing economies are that their renewable transition will require more petrochemicals to be imported. The development of manufacturing capabilities for renewable energy technologies and high domestic petrochemical prices would further boost this import. Policymaking in petrochemical-exporting economies should consider that the findings may suggest opportunities to expand petrochemicals and related sectors, such as hydrocarbons.

Abstract: This paper presents a theoretical extension and empirical validation demonstrating how the allocation of direct, liquid micro-financial incentives—unified under the digital unit of account PECO (Peso Ecológico)—modifies individual agents' utility functions, achieving the large-scale internalization of negative macroeconomic externalities. In contrast to traditional environmental policies based on punitive fiscal coercion (Pigouvian taxes) or the classical assumption of civil action driven by "moral duty"—which historically generates high rates of cognitive friction and apathy—this study models a decentralized, closed, and collaborative market mechanism that operates through a Software as a Service (SaaS) architecture integrated with mass-consumption interfaces (WhatsApp and QR codes).Utilizing a 15-year empirical dataset of continuous field traction across an average of 3,000 families, which was formally audited by The Economist Intelligence Unit (EIU), we demonstrate that an economic nudge directly indexed to the physical mass of clean inorganic waste separated at the source alters the aggregate municipal recycling rate in a directly proportional manner, positioning urban mass efficiency above the continental average. This study mathematically models the intrinsic maturity mismatch of industrial operations, where wholesale processing and stockpiling require a 21-to-28-day cash conversion cycle, necessitating a minimum working capital reserve of USD $50,000 to prevent liquidity fractures when demand outstrips installed capacity.Finally, using mass balance coefficients from SEMARNAT, we show that the aggregation of these domestic micro-decisions optimizes the macroeconomic aggregates of planetary survival. This translates into strict reductions in virgin resource extraction, greenhouse gas mitigation, and the systemic preservation of finite hydrological basins. The model concludes by demonstrating the viability of expanding this protocol globally through flexible multi-currency denominations tied to local purchasing power parity, establishing a resilient institutional governance framework that proves ecological efficiency simultaneously generates private profitability and social welfare.

Abstract: The Low-Income Housing Tax Credit (LIHTC) is the main federal tool for producing affordable rental housing in the United States. Because its units are fixed in place for decades, each siting decision shapes the neighborhoods available to many successive low-income households. This review connects three bodies of research that are usually read separately: studies of where LIHTC developments are located, studies of how neighborhoods affect the long-run outcomes of the people who live in them, and studies of how LIHTC projects change the neighborhoods that receive them. We first describe how the program's design builds location choices into every allocation, and then organize the evidence around four questions: where projects go, why they go there, what location means for tenants, and what it means for existing residents. LIHTC properties remain clustered in higher-poverty, higher-minority areas. That clustering reflects land and construction markets, zoning, local opposition, and allocation rules as much as tenant demand. Neighborhood exposure has large effects on children's adult outcomes, yet LIHTC investment can also raise property values, reduce crime, and improve conditions in distressed neighborhoods, while its effects in higher-income areas are neutral or negative. The result is a genuine trade-off between expanding tenants' access to opportunity and reinvesting in disinvested places, and its terms vary with local context. We close by mapping policy levers to each part of the siting decision and by setting out a research agenda centered on causal identification, tenant-level outcomes, and within-city variation.

Abstract: The study investigates hidden costs of green trade, focusing on environmental regulation, market access, and unequal value capture in West African cocoa supply chains. Environmental due diligence increases the commercial importance of verified origin information, reshaping supplier relationships and the distribution of compliance burdens. Focusing on Côte d’Ivoire, with Ghana and five additional West African producers providing regional context, the analysis combines 2016–2024 cocoa export destinations with 2024 trader-level procurement disclosures. An exposure–visibility decomposition measures European market dependence and public sourcing traceability, while sharp allocation bounds and an aggregate adding-up constraint examine indirect procurement among six major trading groups. In 2024, 66.16% of Ivorian cocoa exports were directed to the European Union, and EU-bound indirect sourcing together with undisclosed-origin trade represented 31.70% of national exports. Despite incomplete company-level cross-tabulations, eight pairwise comparisons identify guaranteed differences in EU-bound indirect procurement volumes. A disclosure-priority measure identifies where additional transaction information could reduce uncertainty effectively. The study advances the literature by connecting identifiable trade-network structures to the economic governance of traceability and by specifying how disclosure requirements can address consequential information gaps. A complementary framework examines producer adaptation costs, buyer screening, record portability, and bargaining opportunities as channels shaping inclusive market participation and value capture. Policy implications concern targeted data disclosure, interoperable verification systems, and safeguards for supplier mobility. The trade-based evidence identifies sourcing exposure and asymmetries in public disclosure; producer-level distributional outcomes and environmental effects require linked farm, buyer, and ecological records. Across countries, institutional differences warrant cautious interpretation of regional comparisons.

Abstract: Becoming a scam victim requires two events: an offender must reach a person, and that person must pay. Using Global Findex 2025 microdata on 61,467 mobile-phone owners in 72 economies, we separate exposure (an unsolicited request for money from a stranger by call or text) from conversion (sending the money). Of these respondents, 21.7% were exposed and 8.4% of those exposed paid. Within economies, internet use, education, workforce participation and account ownership raise exposure, whereas only account ownership raises conversion; formal tests reject equality of the coefficients across stages for internet use, education and income. Across countries, a 0.10-point higher IMF AI Preparedness Index score is associated with conversion odds about half as large (odds ratio 0.53), robust to controls for income, institutions, digital penetration and cybersecurity. The association disappears within world regions (odds ratio 0.83, 95% CI 0.53–1.29), does not replicate with the Oxford Insights Government AI Readiness Index, and extends to a falsification outcome that involves no payment. National AI preparedness shows no robust association with scam outcomes. For fraud-risk management, the results point to network-level controls against contact and account-level safeguards against payment, and caution against reading AI-readiness indices as measures of consumer protection.

Abstract: This study examines the asymmetric effect of the EU’s green transition on carbon emissions across 27 member states from 2000 to 2025 (675 observations), integrating several theoretical perspectives, including environmental economics, ecological economics, green growth, the Porter hypothesis, ecological modernization, the circular economy, eco-innovation, and sustainability transition theory, to fill gaps in earlier research. Using a PMG-NARDL model, it finds that a slowdown in renewable energy growth raises emissions far more (coefficient 2.030) than an acceleration reduces them (1.287), a difference confirmed by the Wald test (p = 0.000). GDP is the main long-run driver of emissions (β = 0.223), energy consumption has a smaller effect (β = 0.077), and the significant error correction term (-0.097) confirms a long-run relationship, with an adjusted R² of 0.8587. Descriptively, a 1% rise in green spending increases GDP by 0.42%, environmental jobs grew 123% between 2000 and 2022, and renewables reached 27.5% of final consumption in 2024, just 2.5 points below the 2030 target. The study concludes that sustaining the green transition’s momentum matters more than accelerating it, since the harm of a slowdown outweighs the benefit of speeding up, so EU policymakers should ensure continuous green investment and address institutional differences among member states.

Abstract: This paper documents how financial depth and banking-system stability evolved together in China between 2000 and 2021. Using 22 annual observations from the World Bank Global Financial Development Database, it examines private credit by deposit money banks to GDP, deposit money banks' assets to GDP, and China's banking-system Z-score. Private credit rose from 111.01% to 178.13% of GDP and bank assets from 118.39% to 214.23% of GDP, while the Z-score increased from 19.24 to 25.02. In levels, both depth indicators are positively correlated with the Z-score (0.671 and 0.670). Simple robustness checks, however, show that this association is fragile: year-to-year changes in depth and stability are essentially uncorrelated, and within 2006–2014, a period with a consistent data source, the correlation is close to zero. The full-period correlation is driven mainly by long-run trends and by two level shifts in the Z-score, in 2006 and in 2015, the latter coinciding with a change in the underlying data source. The results are descriptive and do not identify a causal effect; they point to bank-level panel data as the next step.

Abstract: The sustainable transition of rail transit is central to sustainable mobility under China's dual-carbon goals, yet energy use and carbon emissions from operations keep rising as networks expand, and most of the evidence is city- or line-level, with little known about what operators' own green practices deliver. Using a 2017–2025 panel of eight A-share listed rail transit operators, this study applies a two-way fixed-effects difference-in-differences specification to compare changes in estimated carbon intensity and financial performance around firms' green practices — an exploratory descriptive comparison, since identification rests on a single treated firm — and then simulates four pathways for 2026–2030 — business as usual, green electricity and technology, inclusion in carbon trading, and their combination — calibrated on Shentong Metro's 2025 operating data, and extrapolates the results to industry level. Existing green practices remain marginal: green electricity purchased by Beijing–Shanghai High-Speed Railway in 2025 covered about 1% of its estimated electricity use, and the comparison detects no statistically significant change in carbon intensity (β = 0.225, p = 0.421) or on financial performance. The green-technology pathway cuts carbon intensity by 41.6% below the baseline by 2030, with cumulative abatement of about 39.8 kt CO2 and a cumulative net profit gain of 9.15 million CNY over five years; the combined pathway delivers the same abatement with stronger cost resilience under tightening quotas. Raising the green-electricity share of China's urban rail transit to 40% would abate about 6.46 Mt CO2 per year. By quantifying and monitoring the sustainability performance of rail operators at the firm level, this study provides reproducible measurement tools and evidence-based references for sustainability policy and corporate sustainable strategy in the transport sector.

Abstract: This study examines the relationship between sustainable development, insecurity, policy uncertainty, institutional quality, and agricultural development in Nigeria and Niger State from 2000 to 2024. Using the Autoregressive Distributed Lag (ARDL) model, it analyzes how these factors influence sustainable economic performance. Correlation analysis shows significant relationships among the variables at the 1% level, highlighting their interconnectedness. The ARDL results reveal differences between Nigeria and Niger State: in Nigeria, policy uncertainty positively impacts sustainable development (GDP), while insecurity notably reduces economic performance by weakening investment confidence, productivity, and stability. Conversely, the rule of law fosters growth by enhancing institutional effectiveness. In Niger State, policy uncertainty and insecurity negatively impact sustainable development (GDP), while the rule of law and overall development positively influence economic performance. Based on the CRS Cobb–Douglas production framework, the study underscores that strong institutions enhance productivity and economic resilience, whereas insecurity and uncertainty reduce total factor productivity. By integrating insecurity, policy uncertainty, and agricultural development into a single framework, the study builds on existing research and stresses the importance of institutional reforms, stronger security measures, and predictable policies to achieve sustainable and inclusive economic growth.

Abstract: Link predictors that support decisions, such as suggesting a director to a startup, must explain why a link is or is not recommended. We propose the Multiplicative View-Gated GNN (MG-GNN), which scores a pair as the weighted product of gates, each restricted to one view of the evidence: attributes, structural position, neighbourhood overlap and proximity. Its attributions are exact, and a single failing view caps the score, which certifies robustness to the manipulation of any one view. We prove that, under a conjunctive mechanism, each gate recovers its true condition, whereas additive attributions are not identified. We also prove that disjoint view inputs stop one view from absorbing the vetoes of the others, at a measurable cost. An out-of-sample Vuong test tells the analyst whether the conjunctive reading is warranted, and it identifies the mechanism in all ten synthetic graphs. On six benchmarks, a heterogeneous graph and a new national graph of 13,765 Italian innovative firms and 25,918 directors, MG-GNN matches strong GNN baselines. Its explanations reach 0.97–0.99 of oracle fidelity and are far more stable than Shapley values. In the case study, MG-GNN predicts the 2025–2026 appointments from 2024 data and outperforms the platform’s hand-crafted index.

Abstract: Automatic stabilizers dampen macroeconomic fluctuations without legislative action, but whether flat or progressive personal income tax (PIT) schedules stabilize more strongly over the business cycle remains open. We examine real gross domestic product (GDP) growth volatility in 11 Central and Eastern European economies over 1995–2024, combining rolling-window volatility measures, two-way fixed-effects regressions and direct estimates of the cyclical responsiveness of fiscal balances, revenue and expenditure ratios. Unconditionally, five-year output volatility is 1.16 percentage points higher under flat PIT regimes, but the difference does not survive country and year fixed effects and lagged covariates. Interacted with the 2008–2010 global financial crisis the differential widens by 2.42 percentage points, an effect that rests on the three Baltic economies, whereas the COVID-19 interaction is indistinguishable from zero. A one-percentage-point rise in real GDP growth improves the fiscal balance by 0.265 percentage points of GDP under progressive regimes and by 0.242 under flat regimes, a difference that is not significant. In levels, a weaker revenue response under flat regimes is largely offset by a stronger expenditure response. The results do not support a simple ranking: stabilization capacity depends on the whole tax–benefit system, fiscal institutions and the nature of the shock.

Abstract: The US goat industry has changed as consumer demand has increased, but little is known about how goat characteristics and market variables affect auction prices. This study examines the drivers of goat auction prices in the Maryland goat auction market using 2,416 observations from weekly USDA auction reports from November 2018 to September 2025. We use a hedonic pricing model to estimate the price relationships among goat weight, lot size, selection grade, class, and market timing variables. The findings suggest that observable goat characteristics play an essential role in price formation. Compared with Selection 3 goats, Selection 1, Selection 1–2, and Selection 2 goats had estimated price premiums of 93.47%, 73.90%, and 48.92%, respectively. Premiums for bucks, kids, wether kids, and wethers were 20.31%, 29.95%, 24.81%, and 25.04%, respectively, compared to nannies. The relationship between live weight and price per pound is nonlinear, with expected prices increasing with weight up to around 172.9 pounds and then decreasing. Market time also influences price fluctuations. Eid al-Adha and Ramadan festivals had a favorable impact on prices across different specifications. Prices are also higher during periods of relatively limited supply. The findings indicate that goat prices at the Maryland goat auction market are determined by a combination of observable goat characteristics, class, size, and market conditions. The study provides market-specific evidence to help producers and auction participants understand price differentials and make better marketing decisions, while also providing the foundation for future research on goat price formation in other US auction markets.

Abstract: Higher education institutions are increasingly expected to act as drivers of the bioeconomy, yet strategic planning in this field routinely produces action portfolios far larger than the resources available to implement them, and the choice of what to implement first is usually made implicitly rather than on a traceable basis. This paper applies the Analytic Hierarchy Process to the prioritisation of twenty-one bioeconomy research action plans at a private university in Serbia. Seven criteria and the candidate actions were generated in a Quadruple Helix expert workshop combined with SWOT and TOWS analysis; sixteen institutional respondents completed pairwise comparisons, which were aggregated by the geometric mean method and screened with the consistency ratio. At criterion level, priorities concentrate on sustainable biomass use and circularity integration (18.3%) and environmental and climate contribution (18.0%), while researcher career support ranks last (10.0%). At action level, the highest global priority belongs to an internal technology transfer and commercialization system (7.14%), which sits under the criterion ranked only fifth. Two robustness checks qualify that result: correcting for the unequal number of alternatives per criterion moves this action from first to ninth place, and a sensitivity analysis shows that the leading five actions change in half of the scenarios tested. Sustainability-oriented actions remain stable under both checks.