Search Results (213)

Quantum technology, a critical 21st-century strategic frontier science, has been a key technological competition between China and the U.S. This study employs natural language processing (NLP) techniques and a technology analytical framework to analyze the quantum technology policies of both countries. While the U.S. emphasized free-market innovation and global technological leadership on quantum technology from 2018 to 2024, China prioritized government-led development and socioeconomic stability. Moreover, the Chinese government adopts a systematic top-down approach characterized by government planning and direct intervention. However, the U.S. fosters innovation through market mechanisms and industry-academia collaboration. U.S. policies have gradually shifted from pure technological innovation to national security considerations. On the other hand, China has moved from breakthrough research to industrial deployment and application. These policy differences reflect distinct political systems and governance models, which may also resonate with their respective cultural traditions and philosophical foundations. Our findings fill a critical gap in comparative quantum technology policy research, offering significant insights for policymakers, researchers, and international stakeholders. Full article

Over-the-Air updates have emerged as a critical competitive frontier in the Software-Defined Vehicle era. While offering value creation opportunities, automakers face strategic uncertainty regarding pricing models (e.g., subscription vs. one-time purchase). To clarify these dynamics, this study develops an evolutionary game model of duopolistic pricing competition. Unlike traditional studies with exogenous payoff assumptions, we innovatively employ the Hotelling model to endogenously derive firm profit functions based on consumer utility maximization. The highlights of this study include: (1) We establish an integrated “static–dynamic” framework connecting micro-level consumer choice with macro-level strategy evolution; (2) We identify that product differentiation is the decisive variable governing market stability; (3) We demonstrate that under moderate differentiation, the market exhibits a robust self-correcting tendency towards “Tacit Collusion” (mutual high pricing). However, simulation results also warn that an asymmetric disruptive strategy by a market leader can override this robustness, forcing the market into a low-profit equilibrium. These findings provide theoretical guidance for automakers to optimize pricing strategies and avoid value-destroying price wars. Full article

Vietnam’s wooden forest products industry is an important export sector, contributing to industrial growth and employment. However, it is facing increasing pressures related to challenges such as forest and export sustainability. Despite its potential, Vietnam’s export performance remains uneven across destination markets, related to the presence of significant unrealized trade potential. This study examines the determinants of export efficiency in Vietnam’s wooden forest products sector by moving beyond traditional gravity variables to incorporate institutional and cultural dimensions. Using a panel of 70 trading partners between 2004 and 2023, covering more than 93% of Vietnam’s total wood exports, this study employs an instrumental-variable single-stage stochastic frontier gravity model (IV-SFGM) to estimate trade potential. The results show that economic size, favorable exchange rates, and shared borders significantly enhance export performance. Furthermore, geographical distance and land enclosure remain persistent structural barriers, particularly relevant for bulky and logistics-intensive wood products. Institutional and cultural distance constitute substantial non-tariff barriers, significantly reducing export efficiency across markets. Conversely, regional trade agreements, trade freedom, and foreign direct investment play a critical role in mitigating inefficiencies and facilitating market penetration. Export efficiency in Vietnam’s wooden forest products sector indicates considerable improvement, rising from approximately 25% in the mid-2000s to over 55% in recent years, indicating notable progress in the market and highlighting considerable untapped potential. So, integrating institutional and cultural factors into a frontier-based gravity framework, this study offers novel empirical evidence from an emerging, biodiversity-rich economy with evolving governance institutions. The findings provide important policy implications for aligning export growth with institutional reform and trade liberalization, thereby contributing to the achievement of SDGs such as Decent Work and Economic Growth. Full article

Tea production in Europe represents an emerging segment of the specialty tea market, but a structured comparative analysis remains unexplored. This study employs a standardized approach to systematically characterize hot brews from black and green teas across five European gardens. Antioxidant capacity, total polyphenolic content (TPC), total flavonoid content (TFC), and metabolomic profiling by ultra-high performance liquid chromatography–mass spectrometry were evaluated, and for the first time, sensory profiling of these teas was conducted. Green teas consistently exhibited higher TPC, TFC, and antioxidant capacity compared to black teas, confirming the influence of processing methods. Metabolomic analysis revealed variability in caffeine linked to geographical origin and propagation method (cuttings vs. seeds). Importantly, sensory evaluation suggested a negative correlation between high TPC and overall consumer appreciation. The two most highly appreciated teas often showed lower TPC. These reliable findings advance knowledge in European tea research, providing valuable data for growers to enhance cultivar selection and marketing strategies in alignment with consumer preferences. Full article

This article analyzes an electrical system based on the IEEE-57 bus case, which integrates thermal and wind generation to meet hourly demand. Using the previous day’s wind forecasts as firm market bids, the optimal Pareto frontier for thermal dispatch is calculated, balancing total cost and emissions. The system operator selects a dispatch point based on the desired cost–emissions ratio. To reflect real-world uncertainty, the study incorporates statistical deviations in actual wind production derived from historical data. For each deviation scenario, new optimal thermal dispatch curves are generated. This approach allows for preventive scheduling across the range of expected wind deviations and supports real-time adjustments through mechanisms such as redispatching, intraday markets, or secondary/tertiary regulation. Full article

This study examines how corporate social responsibility (CSR) influences sustainable finance outcomes (SFO) in the Ethiopian Insurance industry through environmental, social, and governance (ESG) practices and institutional challenges (IC). Using covariance-based structural equation modelling (CB-SEM) with data collected from a primary survey, the results show that CSR has both a direct and an indirect positive effect on SFO through ESG. However, the adoption of ESG practices also tends to increase institutional challenges, which in turn negatively influences SFO. This interaction produces a competitive partial mediation effect. The serial mediation path CSR–ESG–IC–SFO is found to be negative, suggesting that enabling and constraining forces operate simultaneously. From a theoretical point of view, the study combines stakeholder, legitimacy, and institutional theories to explain this competitive mediation within a less-studied Sub-Saharan African (SSA) frontier market. On the practical side, the findings highlight the importance of establishing ESG disclosure standards, investing in capacity building, and strengthening governance systems to reduce institutional frictions and make CSR a stronger driver of sustainable finance. Full article

As global production networks become increasingly regionalized, diversified, and resilience-oriented, metropolitan areas (MAs) have emerged as important spatial platforms for industrial development. This study examines whether China’s national-level metropolitan area integration policies promote urban industrial structure upgrading and, if so, through which channels. We first develop a set of conceptual mechanisms and hypotheses, and then test them using panel data for 281 prefecture-level cities in China from 2012 to 2022. A staggered difference-in-differences (DID) model, complemented by a series of robustness checks, is employed to identify the policy effects. The baseline estimates indicate that the industrial structure of MA member cities is, on average, about 2.43 percentage points more advanced than that of non-MA cities. Mechanism analysis shows that the policies foster urban industrial upgrading through unified market formation, technological improvement, and optimization of factor endowments. However, the policies have only a very limited impact on breakthroughs in cutting-edge or frontier technologies. Based on these findings, we propose targeted policy recommendations to address the identified shortcomings. Full article

Exchange-traded funds (ETFs) provide low-cost, liquid access to broad equity and fixed-income exposures, including rapidly growing Asian and Asia-focused markets. Yet the academic evidence on Asian ETF portfolio construction remains fragmented, often limited to narrow country samples and centered on mean–variance trade-offs and standard performance statistics, with comparatively less emphasis on downside tail risk and on implementable long-only versus long–short designs under leverage constraints. This study examines the performance and risk characteristics of 29 Asian and Asia-focused ETFs over 2014–2025 and evaluates whether optimization using variance-based and tail-sensitive risk measures improves portfolio outcomes relative to a simple, implementable benchmark. We construct Markowitz mean–variance and conditional value-at-risk (CVaR) efficient frontiers and implement six optimized portfolios at the 95% and 99% tail levels under long-only and long–short configurations with leverage up to 30%. Performance is evaluated relative to an equally weighted Asian ETF benchmark using the Sharpe ratio and tail-sensitive measures, including the Rachev ratio and the stable tail adjusted return (STARR), complemented by fat-tail diagnostics based on the Hill tail-index estimator. The empirical results show that optimization improves efficiency relative to equal weighting in risk-adjusted terms and that moderate leverage can increase returns but typically amplifies volatility, dispersion, and drawdowns. Taken together, the evidence indicates that risk-measure choice materially affects portfolio composition and realized outcomes, with tail-based optimization generally producing more robust allocations than mean–variance approaches when downside risk is a primary concern. Full article

In modern financial markets, decision-makers increasingly rely on quantitative methods to navigate complex trade-offs among multiple, often conflicting objectives. This paper addresses constrained multi-objective optimization (MOO) with an application to portfolio optimization for minimizing risk and maximizing return. To this end, and to address existing gaps, we propose a novel reinforcement learning (RL)-guided non-dominated sorting genetic algorithm II (NSGA-II) enhanced with gray relational coefficients (GRC), termed RL-NSGA-II-GRC, which combines an RL agent controller and GRC-based selection to improve the convergence and diversity of the Pareto-optimal fronts. The agent adapts key evolutionary parameters online using population-level metrics of hypervolume, feasibility, and diversity, while the GRC-enhanced tournament operator ranks parents via a unified score simultaneously considering dominance rank, crowding distance, and geometric proximity to ideal reference. We evaluate the framework on the Kursawe and CONSTR benchmark problems and on a NASDAQ portfolio optimization application. On the benchmarks, RL-NSGA-II-GRC achieves convergence metric improvements of about 5.8% and 4.4% over the original NSGA-II, while preserving a well-distributed set of non-dominated solutions. In the portfolio application, the method produces a smooth and densely populated efficient frontier that supports the identification of the maximum Sharpe ratio portfolio (with annualized Sharpe ratio = 1.92), as well as utility-optimal portfolios for different risk-aversion levels. The main contributions of this work are three-fold: (1) we propose an RL-NSGA-II-GRC method that integrates an RL agent into the evolutionary framework to adaptively control key parameters using generational feedback; (2) we design a GRC-enhanced binary tournament selection operator that provides a comprehensive performance indicator to efficiently guide the search toward the Pareto-optimal front; (3) we demonstrate, on benchmark MOO problems and a NASDAQ portfolio case study, that the proposed method delivers improved convergence and well-populated efficient frontiers that support actionable investment insights. Full article

Enhancing forestry management efficiency is critical for global sustainable development goals, yet how institutional arrangements can effectively incentivize farmers’ performance requires deeper investigation. This study constructs an integrated framework to examine the effects of well-defined property rights and market certification on the output and technical efficiency of household bamboo management. Utilizing survey data from 1090 households in China, we employ stochastic frontier analysis (SFA), propensity score matching (PSM), and mediation models. The findings reveal a key divergence: (1) Forest tenure certificates significantly increased bamboo output but not technical efficiency. This “quantity-driven” effect stemmed from increased capital and land inputs. (2) Market certification enhanced both output and technical efficiency, operating via a “quality-driven” mechanism of standardized management. (3) Significant technical efficiency losses persist, indicating substantial potential for productivity gains through optimized practices. This study concludes that singular property rights institutions are insufficient to overcome the “output-without-efficiency” bottleneck. Complementary, market-based mechanisms are essential for a dual-pillar policy system. This research offers theoretical support for optimizing forestry policies and provides insights for other developing countries seeking sustainable resource management. Full article

This study investigates the efficiency of higher education systems across the 27 Member States of the European Union during the period 2017–2022, addressing increasing policy interest in data-driven decision support and optimization techniques for performance evaluation in education systems. Efficiency is assessed using Stochastic Frontier Analysis, an optimization-based econometric approach, applied to multiple output dimensions relevant to learning analytics: alignment between graduates’ skills and labour market requirements, scientific productivity measured by published articles, and the number of higher education graduates. The model incorporates key input variables, including the student–teacher ratio, public expenditure per student, research and development expenditure, and the number of academic staff, while controlling for real gross domestic product per capita. To support integrated efficiency measurement and information-based decision-making, multidimensional outcomes are aggregated into composite efficiency indices using entropy-based weighting. The results reveal substantial cross-country heterogeneity in efficiency across EU higher education systems, identifying a cluster of high-performing countries that consistently optimize scientific output and graduate production. Financial resources and academic staff availability emerge as significant drivers of efficiency, while skill matching to labour market demand remains a persistent structural challenge. By combining Stochastic Frontier Analysis with entropy-based aggregation, this study provides a robust data-driven decision support framework for efficiency assessment, offering valuable insights for education policy design, resource allocation, and learning-oriented system optimization. Full article

The present article reinterprets the history of polyglot lexicography and encyclopedic language projects in late imperial China from the Yuan and the Ming through the Qing periods by tracing a three-stage transformation. The Yuan period inaugurated a foundational regime of phonetic transcription anchored in the ’Phags-pa script (Ch. Basiba zi 八思巴字) while already experimenting with semantic pairing in the early Sino–Mongol glossary conventionally known as Zhiyuan yiyu (至元譯語). The Ming consolidated that legacy into a state curriculum centered on the Huayi yiyu (華夷譯語) corpus, together with frontier manuals such as Beilu yiyu (北虜譯語), which systematized domain-based vocabulary and coupled it with documentary templates for tribute, diplomacy, and administration. The Qing, finally, reconceived multilingual lexicography as a project of imperial integration, recentering Manchu as the pivot language in the Qing wen jian (清文鑒) series and culminating in the five-language Wuti Qing wen jian (五體清文鑒). Specialized compendia such as Xiyu tongwen zhi (西域同文志) normalized toponyms across scripts in newly incorporated territories. Complementing official compilations, market-facing handbooks—including Menggu zazi (蒙古雜字)—and the dialogic textbooks Nogeoldae (Ch. Lao qida 老乞大) and Bak Tongsa (Ch. Piao tongshi 朴通事) produced within Joseon’s translator-training institutions reveal a multi-sited ecosystem in which court, frontier, marketplace, and foreign language schools co-produced the infrastructure of interlingual governance. By following the shift from “how to read” (phonetic) to “what it means” (semantic) and ultimately to “what it governs” (administrative integration), this article argues that polyglot lexicons were not merely repositories of words but instruments that made a multilingual empire legible, speakable, and governable. Full article

Background: This study examines how national innovation performance shapes the diffusion of advanced diagnostic technologies across European healthcare systems. Strengthening technological capacity through innovation is increasingly essential for resilient and efficient health services. The analysis quantifies the influence of innovation capacity on the availability of medical imaging technologies in 26 EU Member States between 2018 and 2024. Methods: A balanced panel dataset was assembled from Eurostat, the European Innovation Scoreboard, and World Bank indicators. Dynamic relationships between innovation performance and the adoption of CT, MRI, gamma cameras, and PET scanners were estimated using a two-step approach combining General-to-Specific (GETS) outlier detection with Robust Least Squares regression to address heterogeneity and specification uncertainty. Results: Higher innovation scores significantly increase the diffusion of R&D-intensive technologies such as MRI and PET, while CT availability shows limited responsiveness due to market maturity. Public health expenditure supports frontier technologies when strategically targeted, whereas GDP growth has no significant effect. Population size consistently enhances technological capacity through scale and system-integration effects. Conclusions: The findings show that innovation ecosystems, rather than economic growth alone, drive the modernization of diagnostic infrastructure in the EU. Integrating innovation metrics into health-technology assessments offers a more accurate basis for designing innovation-oriented investment policies in European healthcare. Full article

Platform-enabled governance is reshaping destination management, yet subnational destinations still lack replicable dashboards that combine key performance indicators (KPIs) with efficiency analysis. This study examines whether a compact KPI stack coupled with longitudinal Data Envelopment Analysis (DEA) can provide actionable targets for destination development management and marketing organizations (DDMMOs). Using 2020–2024 administrative data for five regional units of the Peloponnese, an output-oriented CRS DEA model is specified with one input (room capacity) and two outputs (tourism revenue and overnight stays), complemented by a VRS specification that decomposes Overall Technical Efficiency into Pure Technical and Scale Efficiency. The results show a clear differentiation in trajectories: one regional unit remains consistently on the efficiency frontier, and others exhibit gradual convergence towards best practice, while at least one unit displays persistent underperformance that is driven primarily by scale rather than managerial inefficiency. These distances to frontier are transformed into proportional, output-specific targets and dynamically updated peer sets, which are integrated into a KPI dashboard to support a continuous measure–act–learn loop on pricing, promotion, and capacity allocation. Overall, the article proposes a transparent, reproducible template that links destination competitiveness frameworks with a multi-input, multi-output efficiency lens and embeds KPIs and dynamic DEA insights in a continuous governance loop for destination management. Full article

This study examines how sovereign risk shapes the financial performance of sustainable investments, using the MSCI Emerging Markets ESG Index as a reference. The analysis covers 24 emerging and frontier economies from Latin America, Asia, the Middle East, and Eastern Europe during 2016–2025, a period marked by major global disruptions such as the COVID-19 crisis and post-2022 financial tightening. Sovereign risk dimensions are extracted through Principal Component Analysis (PCA) applied to sovereign CDS spreads, identifying a systemic component linked to global shocks and a structural component associated with domestic fundamentals and governance quality. These factors are integrated into a quantile regression framework alongside control variables—oil prices, interest rates, and global equity indices—capturing key macro-financial transmission channels. Results show a nonlinear, quantile-dependent relationship: systemic risk intensifies ESG losses under adverse conditions, while structural improvements support gains in upper quantiles. Control variables behave as expected, confirming the macro-financial sensitivity of ESG performance. The findings reveal that ESG returns are state-dependent and strongly influenced by sovereign credit dynamics, especially in emerging markets where external shocks and institutional fragility intersect. Strengthening sovereign governance and integrating risk diagnostics into ESG assessments are essential steps to enhance resilience and credibility in sustainable finance. Full article