Search Results (17,410)

Love wave surface acoustic wave (LSAW) sensors are crystal resonators known for their high potential for biosensing applications due to their high sensitivity, real-time detection, and compatibility with microfluidic systems. Commercial LSAW devices are costly, and manufacturing them is even more expensive, making accessibility a significant challenge. Additionally, their use requires specialized systems, and with only a few manufacturers dominating the market, most available solutions are proprietary, limiting customization and adaptability for specific research needs. In this work, a low-cost open-source LSAW biosensing system prototype was developed based on a commercially acquired resonator. The development integrates microfluidics through a polydimethylsiloxane (PDMS) chip, low-cost electronics, and both 3D printed ultraviolet (UV) resin and polylactic acid (PLA) parts. The instrument used for measurements was a vector network analyzer (VNA) that features open-source software. The code was customized for this study to enable real-time, label-free biosensing. Experimental validation consisted of evaluating the sensitivity and repeatability of the system, from the setup to its use with different fluids. Results demonstrated that the development is able to advance to more complex applications. Full article

This article examines the significant contributions of Helga de Alvear as a gallerist, collector, and patron, a pivotal figure in the evolution of the Spanish and international contemporary art market. Her legacy is particularly notable through the establishment of the Helga de Alvear Museum in the city of Cáceres, intended to share her vast collection of over 3000 works and foster exhibition, research, conservation, and education. The study analyzes her art collection, highlighting its substantial international minimalist art component, contextualizing its development with her personal and professional journey. Furthermore, it explores the institutionalization of her legacy, from the Helga de Alvear Foundation to the creation and evolution of the museum, its innovative architecture and museography, and its impact on Cáceres’s urban landscape. Full article

Supply chains are increasingly exposed to sudden disruptive events (SDEs) such as natural disasters and trade wars. We develop a multi-stage game-theoretical model to investigate a novel coping mechanism: when a firm is forced to exit the market because of SDEs, the firm can regain profits by licensing its proprietary production tech to a competitor. We find that, compared with the scenario before SDEs, such events can even increase the profit of each manufacturer under certain conditions. Under certain conditions, the cooperative strategy (i.e., supply chain reshaping) yields a higher supply chain system profit than the non-cooperative strategy. After SDEs, the common manufacturer may either accept or reject cooperation, depending on the customer transfer rate and the cooperation cost. Notably, under the cooperation strategy, the high-tech manufacturer extracts part of the common manufacturer’s profit through patent licensing, and the existence of cooperation cost further contributes to a misalignment between the common manufacturer’s optimal decision and the supply chain system optimum. These findings contribute to the literature by identifying a novel supply chain reshaping mechanism driven by patent licensing and offer strategic guidance for firms and policymakers navigating SDE-induced market exits. Full article

This study examines the impact of personal remittances on housing prices in European Union (EU) countries, while also accounting for a broader set of macroeconomic, demographic, and structural variables. Using annual data for 27 EU countries from 2007 to 2022, we employ a comprehensive panel econometric approach, including cross-sectional dependence tests, second-generation unit root tests, pooled mean group–autoregressive distributed lag (PMG-ARDL) estimation, and panel causality tests, to capture both short- and long-term dynamics. Our findings confirm that remittances significantly and positively influence long-term housing price levels, underscoring their relevance as a demand-side driver. Other key variables such as net migration, GDP, travel credit to GDP, economic freedom, and real effective exchange rates also contribute to housing price movements, while supply-side indicators, including production in construction and building permits, exert moderating effects. Moreover, real interest rates are shown to have a significant long-term negative effect on property prices. The analysis reveals key causal links from remittances, FDI, and net migration to housing prices, highlighting their structural and predictive roles. Bidirectional causality between economic freedom, housing output, and prices indicates reinforcing feedback effects. These findings position remittances as both a development tool and a key indicator of real estate dynamics. The study highlights complex interactions between international financial flows, demographic pressures, and domestic economic conditions and the need for policymakers to consider remittances and migrant investments in real estate strategies. These findings offer important implications for policymakers seeking to balance housing affordability, investment, and economic resilience in the EU context and key insights into the complexity of economic factors and real estate prices. Importantly, the analysis identifies several causal relationships, notably from remittances, FDI, and net migration toward housing prices, underscoring their predictive and structural importance. Bidirectional causality between economic freedom and house prices, as well as between housing output and pricing, reflects feedback mechanisms that further reinforce market dynamics. These results position remittances not only as a developmental instrument but also as a key signal for real estate market performance in recipient economies. Full article

Large Language Models (LLMs) are reshaping recommendation systems through enhanced language understanding, reasoning, and integration with structured data. This systematic review analyzes 88 studies published between 2023 and 2025, categorized into three thematic areas: data processing, technical identification, and LLM-based recommendation architectures. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the review highlights key trends such as the use of knowledge graphs, Retrieval-Augmented Generation (RAG), domain-specific fine-tuning, and robustness improvements. Findings reveal that while LLMs significantly advance semantic reasoning and personalization, challenges remain in hallucination mitigation, fairness, and domain adaptation. Technical innovations, including graph-augmented retrieval methods and human-in-the-loop validation, show promise in addressing these limitations. The review also considers the broader macroeconomic implications associated with the deployment of LLM-based systems, particularly as they relate to scalability, labor dynamics, and resource-intensive implementation in real-world recommendation contexts, emphasizing both productivity gains and potential labor market shifts. This work provides a structured overview of current methods and outlines future directions for developing reliable and efficient LLM-based recommendation systems. Full article

Economic systems face critical challenges, including widening income inequality, unemployment driven by automation, mounting public debt, and environmental degradation. This study introduces Economocracy as a transformative framework aimed at addressing these systemic issues by integrating democratic principles into economic decision-making to achieve social equity, economic efficiency, and environmental sustainability. The research focuses on two core mechanisms: Economic Productive Resets (EPRs) and Economic Periodic Injections (EPIs). EPRs facilitate proportional redistribution of resources to reduce income disparities, while EPIs target investments to stimulate job creation, mitigate automion-related job displacement, and support sustainable development. The study employs a theoretical and analytical methodology, developing mathematical models to quantify the impact of EPRs and EPIs on key economic indicators, including the Gini coefficient for inequality, unemployment rates, average wages, and job displacement due to automation. Hypothetical scenarios simulate baseline conditions, EPR implementation, and the combined application of EPRs and EPIs. The methodology is threefold: (1) a mathematical–theoretical validation of the Cycle of Money framework, establishing internal consistency; (2) an econometric analysis using global historical data (2000–2023) to evaluate the correlation between GNI per capita, Gini coefficient, and average wages; and (3) scenario simulations and Difference-in-Differences (DiD) estimates to test the systemic impact of implementing EPR/EPI policies on inequality and labor outcomes. The models are further strengthened through tools such as OLS regression, and Impulse results to assess causality and dynamic interactions. Empirical results confirm that EPR/EPI can substantially reduce income inequality and unemployment, while increasing wage levels, findings supported by both the theoretical architecture and data-driven outcomes. Results demonstrate that Economocracy can significantly lower income inequality, reduce unemployment, increase wages, and mitigate automation’s effects on the labor market. These findings highlight Economocracy’s potential as a viable alternative to traditional economic systems, offering a sustainable pathway that harmonizes growth, social justice, and environmental stewardship in the global economy. Economocracy demonstrates potential to reduce debt per capita by increasing the efficiency of public resource allocation and enhancing average income levels. As EPIs stimulate employment and productivity while EPRs moderate inequality, the resulting economic growth expands the tax base and alleviates fiscal pressures. These dynamics lead to lower per capita debt burdens over time. The analysis is situated within the broader discourse of institutional economics to demonstrate that Economocracy is not merely a policy correction but a new economic system akin to democracy in political life. Full article

The rapid development of digital technology is reshaping the global economic landscape. However, its impact on firms’ capacity utilization rate (CUR), particularly through technological innovation, remains unclear. This study investigates this issue by developing an endogenous growth model that connects digital technology to CUR. The empirical analysis is based on data from Chinese A-share manufacturing firms. The methods employed include quantile regression, instrumental variable techniques, and various tests to explore underlying mechanisms. CUR is calculated using a special model that looks at random variations, and digital transformation is assessed using text analysis powered by machine learning. The findings indicate that digital transformation significantly enhances CUR, especially for firms with average capacity utilization levels, but has a limited effect on low- and high-end firms. Moreover, technological innovation mediates this relationship; however, factors like “double arbitrage” (involving policy and capital markets) and “herd effects” tend to prioritize quantity over quality, which constrains innovation potential. Improvements in CUR lead to enhanced firm performance and productivity, generating industry spillovers and demonstrating the broader economic externalities of digitalization. This study uniquely applies endogenous growth theory to examine the role of digital transformation in optimizing CUR. It introduces the “quantity-quality” technology innovation paradox as a crucial mechanism and highlights industry spillovers to address overcapacity while offering insights for fostering sustainable economic and social development in emerging markets. Full article

The goals of the European Union towards the energy transition imply profound changes in the energy field, so as to promote sustainable energy development while fostering economic growth. To achieve these changes, the incorporation of sustainable technologies supporting decentralisation, energy efficiency, renewable energy production, and demand flexibility is of vital importance. Blockchain has the potential to change energy services towards this direction. To optimally exploit blockchain, innovative business models need to be designed, identifying the opportunities emerging from unmet needs, while also considering potential risks so as to take action to overcome them. In this context, the scope of this paper is to examine the opportunities and the risks that emerge from the adoption of blockchain in four innovative business models, while also identifying mitigation strategies to support and accelerate the energy transition, thus proposing optimal approaches of exploitation of blockchain in energy services. The business models concern Energy Performance Contracting with P4P guarantees, improved self-consumption in energy cooperatives, energy efficiency and flexibility services for natural gas boilers, and smart energy management for EV chargers and HVAC appliances. Firstly, the value proposition of the business models is analysed and results in a comprehensive SWOT analysis. Based on the findings of the analysis and consultations with relevant market actors, in combination with the examination of the relevant literature, risks are identified and evaluated through a qualitative assessment approach. Subsequently, specific mitigation strategies are proposed to address the detected risks. This research demonstrates that blockchain integration into these business models can significantly improve energy efficiency, reduce operational costs, enhance security, and support a more decentralised energy system, providing actionable insights for stakeholders to implement blockchain solutions effectively. Furthermore, according to the results, technological and legal risks are the most significant, followed by political, economic, and social risks, while environmental risks of blockchain integration are not as important. Strategies to address risks relevant to blockchain exploitation include ensuring policy alignment, emphasising economic feasibility, facilitating social inclusion, prioritising security and interoperability, consulting with legal experts, and using consensus algorithms with low energy consumption. The findings offer clear guidance for energy service providers, policymakers, and technology developers, assisting in the design, deployment, and risk mitigation of blockchain-enabled business models to accelerate sustainable energy development. Full article

We investigate whether China’s Value-Added Tax (VAT) Credit Refund policy influences firms’ sustainable development capability (SDC), which reflects innovation-driven growth and green development. Exploiting the 2018 implementation of the VAT Credit Refund policy as a quasi-natural experiment, we employ a difference-in-differences (DID) approach and find causal evidence that the policy significantly enhances firms’ SDC. This suggests that fiscal instruments like VAT refunds are valued by firms as drivers of long-term sustainable and high-quality development. Our mediating analyses further reveal that the policy promotes firms’ SDC by strengthening artificial intelligence (AI) capabilities and facilitating intelligent transformation. This mechanism “AI Capability Building—Intelligent Transformation” aligns with the socio-technical systems theory (STST), highlighting the interactive evolution of technological and social subsystems in shaping firm capabilities. The heterogeneity analyses indicate that the positive effect of VAT Credit Refund policy on SDC is more pronounced among small-scale and non-high-tech firms, firms with lower perceived economic policy uncertainty, higher operational diversification, lower reputational capital, and those located in regions with a higher level of marketization. We also find that the policy has persistent long-term effects, with improved SDC associated with enhanced ESG performance and green innovation outcomes. Our findings have important implications for understanding the SDC through the lens of STST and offer policy insights for deepening VAT reform and promoting intelligent and green transformation in China’s enterprises. Full article

This paper selects 50 listed commercial banks in China from 2012 to 2023 as research samples, and employs the fixed effects model and Hansen’s threshold regression method to systematically examine the impact mechanism and non-linear characteristics of FinTech development on the profitability of commercial banks. The key findings are summarized as follows: (1) FinTech significantly undermines the overall profitability of commercial banks by reshaping the competitive landscape of the industry and intensifying the technology substitution effect. This is primarily reflected in the reduction in traditional interest income and the erosion of market share in intermediary business. (2) Heterogeneity analysis indicates that large state-owned banks and joint-stock banks experience more pronounced negative impacts compared to small and medium-sized banks. (3) Additional research findings reveal a significant single-threshold effect between FinTech and bank profitability, with a critical value of 4.169. When the development level of FinTech surpasses this threshold, its inhibitory effect diminishes substantially, suggesting that after achieving a certain degree of technological integration, commercial banks may partially alleviate external competitive pressures through synergistic effects. This study offers crucial empirical evidence and theoretical support for commercial banks to develop differentiated technology strategies and for regulatory authorities to design dynamically adaptable policy frameworks. Full article

Fan growth serves as a critical performance indicator for the sustainable development of livestreaming e-commerce (LSE). However, existing research has paid limited attention to this topic. This study investigates the unique interactive advantages of LSE over traditional e-commerce by examining how interactivity drives fan growth through the mediating role of user retention and the moderating role of anchors’ facial attractiveness. To conduct the analysis, real-time data were collected from 1472 livestreaming sessions on Douyin, China’s leading LSE platform, between January and March 2023, using Python-based (3.12.7) web scraping and third-party data sources. This study operationalizes key variables through text sentiment analysis and image recognition techniques. Empirical analyses are performed using ordinary least squares (OLS) regression with robust standard errors, propensity score matching (PSM), and sensitivity analysis to ensure robustness. The results reveal the following: (1) Interactivity has a significant positive effect on fan growth. (2) User retention partially mediates the relationship between interactivity and fan growth. (3) There is a substitution effect between anchors’ facial attractiveness and interactivity in enhancing user retention, highlighting the substitution relationship between anchors’ personal characteristics and livestreaming room attributes. This research advances the understanding of interactivity’s mechanisms in LSE and, notably, is among the first to explore the marketing implications of anchors’ facial attractiveness in this context. The findings offer valuable insights for both academic research and managerial practice in the evolving livestreaming commerce landscape. Full article

This longitudinal study examines how perceived brand globalness (PBG) influenced sustainable purchase intentions (SPI) between 2021 and 2024, incorporating factors such as perceived brand quality (PBQ), perceived brand prestige (PBP), brand–cause fit (BCF), and the moderating effect of consumer ethnocentrism (CE). Using survey responses from 415 participants, the study employed partial least squares structural equation modeling (PLS-SEM) via SmartPLS4. The findings reveal that CE emerged as significant in 2024, while PBP’s impact on SPI weakened—suggesting a growing consumer association of prestige with sustainability. Heightened post-pandemic ethical awareness further underscores the importance of brand values. Contrary to earlier research indicating low CE in developing markets, the 2024 results demonstrate an unexpected rise in CE, highlighting its evolving significance. Overall, the study emphasizes the necessity for global brands to adopt sustainable, locally attuned strategies to succeed in developing countries. Full article

In the context of the global response to climate change and the active promotion of energy transformation, a number of low-carbon policies coupled with the development of synergies to help power system transformation is an important initiative. However, the insufficient articulation of the green power market, tradable green certificate (TGC) market, and carbon emission trading (CET) mechanism, and the ambiguous policy boundaries affect the trading decisions made by its market participants. Therefore, this paper systematically analyses the composition of the main players in the electricity-CET-TGC markets and their relationship with each other, and designs the synergistic mechanism of the electricity-CET-TGC markets, based on which, it constructs the optimal profit model of the thermal power plant operators, renewable energy manufacturers, power grid enterprises, power users and load aggregators under the electricity-CET-TGC markets synergy, and analyses the behavioural decision-making of the main players in the electricity-CET-TGC markets as well as the electric power system to optimise the trading strategy of each player. The results of the study show that: (1) The synergistic mechanism of electricity-CET-TGC markets can increase the proportion of green power grid-connected in the new type of power system. (2) In the selection of different environmental rights and benefits products, the direct participation of green power in the market-oriented trading is the main way, followed by applying for conversion of green power into China certified emission reduction (CCER). (3) The development of independent energy storage technology can produce greater economic and environmental benefits. This study provides policy support to promote the synergistic development of the electricity-CET-TGC markets and assist the low-carbon transformation of the power industry. Full article

This study examines the factors influencing the adoption of enterprise resource planning (ERP) systems within Romanian organizations. The objective is to develop a comprehensive framework for ERP adoption decisions, thereby advancing the field of knowledge and offering managerial insights. To accomplish this research goal, a questionnaire is envisioned, employing various research hypotheses, and distributed to a representative sample. Quantitative econometric regression analysis is employed, considering potential factors such as user training and education, competitive pressures, user involvement and participation, decentralized ERP features, top management support, data quality, the quality of the ERP system, cost and budget considerations, and business process reengineering. Of the 12 factors analyzed, 9 were found to be relevant in terms of influence on the decision to adopt ERP systems, in the context of the Romanian market. The other three factors were found to be irrelevant, thus obtaining results partially different from other areas of the world. By validating the hypotheses and answering the research questions, this work addresses a research gap regarding the lack of a comprehensive understanding of the influencing factors that shape the adoption process of ERP systems in Romania. Full article

In the context of the GCC, the adoption of integrated reporting (IR) remains limited, due in part to weak regulatory enforcement, a lack of awareness of the strategic benefits of IR, and a strong focus on short-term financial results. This limited reporting context presents a significant challenge for firms to credibly demonstrate their value to the market and attract potential investors, thus communicating long-term value. Given these limitations, this study considers how IR contributes to firm value, but also examines the mediating role that firm image (FI) plays in this relationship as a reputational construct representing stakeholder perspectives of a firm’s transparency and accountability. The research employs a quantitative methodology, analysing secondary data from corporate governance and integrated reports spanning 2017–2018 to 2022–2023. Findings indicate a positive and robust relationship between integrated reporting and the firm’s value, which was assessed using Tobin’s Q. The findings highlight the significant mediating role of firm image, illustrating how IR practices, via increased transparency, accountability, and sustainability, enhance firm value. This study provides significant insights for researchers, policymakers, and corporate managers, highlighting the strategic relevance of IR in the GCC region. The findings demonstrate that integrated reporting improves transparency, accountability, and sustainability, thereby assisting corporate managers in utilising IR to enhance firm image and facilitate value creation. Policymakers can utilise these insights to develop regulatory frameworks that promote integrated reporting practices, thereby enhancing transparency and sustainable growth within the corporate sector. Full article