The increasing complexity, disruption, and sustainability pressures affecting global supply chains have intensified interest in blockchain technology as a mechanism for improving transparency, traceability, and coordination among supply chain actors. This study addresses the need to better understand the evolution and future research trends of blockchain applications in supply chain management (SCM). The objective is to map the intellectual structure, thematic evolution, and emerging dynamics of this rapidly expanding research field. The analysis is based on a corpus of 2101 articles published between 2017 and 2024 and extracted from the Scopus database. Following the PRISMA protocol for data selection, VOSviewer and Harzing’s Publish or Perish tools were employed to conduct performance analyses (publications and citations) and scientific mapping analyses (co-citation, keyword co-occurrence, and collaboration networks). The findings reveal exponential growth in scientific production, accelerated by the COVID-19 pandemic. Research in this field is structured around four major thematic areas: supply chain performance, technological foundations, sustainability, and traceability, particularly within the agri-food sector. The analysis also highlights significant geographical polarization, dominated by China, India, and the United States, as well as a strong editorial concentration around technology- and sustainability-oriented journals. Foundational works by Saberi et al. (2019) and Dutta et al. (2020) play a central role in structuring the intellectual foundations of the field. This study contributes to the literature by providing an updated and comprehensive mapping of blockchain research in SCM while identifying persistent gaps related to empirical validation, disciplinary fragmentation, and the underrepresentation of developing countries. Beyond descriptive mapping, the findings suggest that blockchain research in SCM is progressively evolving from a technology-centered perspective toward a governance-, resilience-, and sustainability-oriented paradigm. Based on these findings, the study proposes a structured research agenda to guide future interdisciplinary, empirical, and collaborative investigations.
This study aims to analyze the dynamic relationship between inflation and Brazil’s basic interest rate (SELIC) from 2000 to 2025 within the country’s inflation-targeting framework. Grounded in monetary policy theory and inflation dynamics and explores how the Central Bank’s interest rate adjustments respond to inflationary pressures and other macroeconomic variables. The theoretical framework integrates models of inflation persistence and monetary policy transmission, emphasizing the role of credibility in inflation targeting. Methodologically, the study employs advanced econometric techniques, including Vector Autoregressive (VAR) models, Error Correction Models (ECM), and Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) models, to capture both short-term monetary reactions and long-term equilibrium relationships. Controls such as GDP growth, exchange rate volatility, fiscal shocks, and credit market responses are incorporated to ensure practical results. Findings reveal a statistically significant positive correlation between inflation and the SELIC rate, with an average policy response lag of nine months. Over the study period, inflation persistence has declined, indicating increased policy credibility and effectiveness of the inflation-targeting regime.Episodes of heightened financial volatility, notably the 2008 global crisis and recent fiscal challenges, substantially influence monetary policy stance and inflation outcomes. The research provides empirical evidence on Brazil’s monetary policy transmission mechanism, contributing to a understanding of how macroeconomic stability is maintained through coordinated policy actions. Its originality lies in combining long-span data with sophisticated econometric models and a set of macro and micro controls, updating and extending prior findings such in renowned past studies and data of institutions as the Central Bank of Brazil
Conventional methods of time series forecasting often strive in capturing many dynamics patterns that are existing in large real-world time series data. Consequently, Machine learning techniques are gaining popularity especially in forecasting enormous data, thereby making research interests in the economic and finance fields to be more attractive. This paper uses time series prediction techniques to forecast the prices of two World most popular crude oils namely; WTI and Brent by examining the market volatility. The features of GARCH, SVR, and LSTM are combined to capture many dynamics patterns in the WTI and Brent crude oils. Specifically, we use GARCH to model volatility clustering, SVR to improve short-term price prediction, and LSTM to forecast long-term price trends. The results show that the GARCH model can effectively capture volatility patterns, making it ideal for analyzing risk and market shocks. However, SVR performs in short-term price predictions under stable market conditions. LSTM, on the other hand, proved valuable for long-term forecasting, particularly in volatile periods.
This research note examines the Granger-causal relationship between the stock of active registered enterprises and real export performance in Çanakkale province, Turkey, over the period 2013–2023 (n = 11 annual observations). We apply the Toda–Yamamoto (1995) augmented VAR procedure — a commonly used procedure when integration and cointegration properties are uncertain in short samples — and obtain an initial result of unidirectional Granger-predictive precedence from enterprise stock to real exports (χ²(1) = 7.63, p = 0.031). We then subject this finding to systematic leave-one-out (LOO) sensitivity testing and find that the result disappears when any of three individual years (2016, 2019, or 2020) are excluded from the sample. We report this fragility transparently, argue that it is a direct consequence of the minimum effective sample of n = 9 observations after VAR lags, and interpret the initial result as motivation for a multi-province panel analysis rather than a policy-ready conclusion. We also discuss the conceptual limitations of using the total enterprise stock as a proxy for entrepreneurial activity and outline the exact data and methodological requirements for a confirmatory study.
This paper examines the socio-economic factors influencing the closure of bank branches in Spanish municipalities between 2015 and 2022. This period was characterised by a significant reduction in the number of branches following the restructuring of the financial sector after the 2008 financial crisis. Using panel data econometrics and spatial analysis, the study identifies territorial patterns of closures and assesses the impact of local factors, including population density, demographic ageing, income levels and productive structure. Against the backdrop of growing financial exclusion, particularly in rural, ageing or economically disadvantaged areas, understanding these dynamics is crucial for identifying the most vulnerable territories and informing public policy to guarantee equitable access to basic financial services and foster territorial cohesion.
How much Official Development Assistance (ODA) ends in hands of the poor? This paper analyses the critical situation facing ODA since Donald Trump came to power and his drastic budget cuts to the aid’s Agency USAID, which have been followed by numerous other donors. It proposes several options for identifying aid truly targeted to the poor. One is a poverty marker registered by the OECD's Development Assistance Committee, similar to those already in place for other goals such as the Rio Declaration or gender. Another is to better capture aid channelled through Non Governmental Organizations or for sectors directly related to poverty, such as education, health, water and sanitation, and humanitarian aid. This can increase transparency, ownership, and accountability so that ODA does not become a residual variable that is dispensed in order to increase defence spending. Our estimate indicates that, at present, ODA targeted to the poor would represent roughly 20–35% of the total.
Rising greenhouse gas emissions have led to extreme weather events, which have become increasingly frequent in recent years. These have serious consequences for people's lives and the global economy. In 2023, the European Union was the fourth largest emitter of greenhouse gases in the world. It is against this background that the Union is proposing a European Green Deal, aiming for climate neutrality, resource efficiency and economic competitiveness by 2050. This paper studies the impact of the European LIFE program which is one of the funding mechanisms of the Green Deal on the reduction of greenhouse gas emissions, focusing on the case study of Romania and Spain. The main aim is to determine whether LIFE funding contributes significantly to emission reductions by using econometric modeling to analyze various factors influencing emissions in the two selected countries, taking into account their socio-economic differences. The results of such a comparison between an economically developed country in Western Europe and an emerging economy in Eastern Europe may provide valuable insights into the impact of the EU's efforts to transition to a green economy, as well as the factors that continue to influence emissions in these distinct economies.
Un movimiento mundial hacia la descarbonización está transformando el sector químico. Actualmente, la producción sostenible es un objetivo común en todo el ecosistema, que involucra a fabricantes de productos químicos, empresas de reciclaje, proveedores de tecnología e industrias transformadoras. Adoptar esta transición es esencial para promover un futuro bajo en carbono tanto para la industria química como para los mercados que sustenta. Nuestro objetivo es estudiar la situación actual y la evolución reciente del Complejo Químico de Huelva. Desde 1964, año en que el complejo químico inició sus operaciones, la región andaluza se ha convertido en un lugar muy atractivo para el sector industrial en general y el químico en particular. Hoy, 60 años después, sigue siendo uno de los principales centros industriales de España y cuenta con una veintena de empresas dedicadas a la producción de refino de petróleo, petroquímicos, biocombustibles, metalurgia, generación de electricidad (mediante ciclos combinados, biomasa, cogeneración y otros sistemas), tanto orgánica como inorgánica, y fertilizantes. Pero los retos que las áreas industriales deben afrontar hoy en día van más allá de las exigencias del crecimiento y las nuevas formas de producción. Los retos ambientales y sociales ocupan un lugar destacado en los requisitos del Pilar 2 de Horizonte Europa, la Política Industrial España 2030 (Componente 12 del Plan de Recuperación, Transformación y Resiliencia) y los Objetivos de Desarrollo Sostenible (ODS). En este artículo, queremos destacar cómo, a lo largo de los años, las empresas del Polo de Huelva se han comprometido a aumentar la producción mediante la innovación, adaptándose a los retos de la sostenibilidad ambiental. Por ello, muchos de sus proyectos innovadores se han orientado al respeto por el medio ambiente y al compromiso con la descarbonización.
This study proposes the construction of a composite Life Quality Index (LQI) for Spain’s autonomous communities and cities using a dynamic version of the DP2 distance, originally developed by Pena-Trapero (1977). This methodology offers several advantages: (1) it enables both cross-sectional and temporal comparisons across territorial units; (2) it applies an objective weighting criterion; and (3) it eliminates redundant information among indicators. The results reveal that the LQI displays significant cyclical sensitivity, highlighting substantial differences across dimensions in both levels and trends. Moreover, the study underscores the need to expand the informational basis for certain dimensions such as Education, Leisure and Social Relations, Governance and Fundamental Rights, and General Life Experience.
This paper presents general data on the evolution of employment demand in Spain over recent years. This information could improve knowledge of certain important economic aspects of the labor market in these country regions. In the first step, we present a descriptive analysis of the employment structure, by branch of activity, at the level of all the autonomous communities between 2011 and 2022. In the second step, we study regional professional specialization during the same period. This will allow us to know how much the Spanish economy has changed over the last decade by examining the effect of areas on occupations in demand. In the third step, the descriptive analysis is complemented by advanced econometric techniques, particularly panel data models, to capture the dynamics of the Spanish labor market at both the sectoral and regional levels. Thus, this work shows some significant regional differences in the employment structure during the period under consideration and increased demand for qualifications and professional specialization. To conduct this research, we used data provided by the Labour Force Survey (EPA).
This study explores the effect of financial literacy on financial inclusion in 12 local government areas in Niger State of Nigeria using the Probit regression model. The estimation results indicate that higher levels of financial literacy positively and significantly influence financial inclusion in both urban and rural regions. The results also confirm that educational status, employment, informality, social security, poverty, gender, and age are important determinants of financial inclusion. The policy implications of the study include the need for all tiers of government to implement robust financial education strategies to amplify the positive effects of financial literacy on financial inclusion and to mitigate the adverse effects of financial illiteracy. Efforts to achieve higher levels of financial inclusion through improved financial literacy must be complemented by policies which focus on improving job creation opportunities, reducing poverty, promoting gender inclusivity, and fostering an enabling business environment.
Inferir soluciones a las necesidades y potencialidades de la coordinación de las redes de comunicación transeuropeas, transnacionales y multi regionales ibéricas justifica la necesidad e interés de agrupar unidades socioeconómicas en la economía espacial. Comparamos agrupamientos a partir de los métodos de clasificación jerárquica y de un procedimiento de redes neuronales con un modelo ideal construido para una base de datos de veinte años (2000-2019) de las unidades estadísticas espaciales NUTS 3 ibéricas. Los modelos más concordantes con el ideal son, en primer lugar, el de Redes Neuronales y, en segundo lugar, el método de Ward.
Se entiende por Ecosistema de Salud (EdS) al conjunto de elementos (humanos, sociales y culturales, materiales y ambientales, tecnológicos, organizativos y regulativos) que conjuntamente proporcionan soluciones personalizadas a los pacientes y determinan las políticas públicas en el ámbito de la salud. Fruto del rápido desarrollo de las tecnologías de la información y de la comunicación acaecido en las últimas décadas –en particular los recientes desarrollos de la Inteligencia Artificial–, la evolución de este ecosistema está sufriendo un cambio radical. En el actual contexto, conocido como Sociedad del Conocimiento e Inteligencias Artificiales, el reto esencial del EdS es incorporar la inteligencia humana, junto a la social y las artificiales para dar una respuesta efectiva, eficaz y eficiente, tanto a las demandas de los pacientes como a las necesidades futuras de la sociedad en el ámbito de la salud. En concreto, este trabajo se centra en la adecuación a los nuevos tiempos de uno de los subsistemas del EdS: las entidades financieras y aseguradoras.
The aim of this study was to analyze the economic determinants of Brazilian chicken feet exports to China, in the period from 2015 to 2024, using the Vector Error Correction (VEC) model. The long-term results indicated that Chinese income and export prices have positive and significant impacts on chicken feet exports, while the exchange rate did not prove to be relevant in explaining the trade flow of the commodity. In the short term, the impulse response function highlights the positive effects of external income and export prices of chicken feet. External income increases Chinese demand for the Brazilian commodity, while product prices stimulate production growth for export. These findings reinforce the importance of Chinese demand and pricing as key vectors in the export dynamics.
Los cambios paradigmáticos con respecto a las personas con discapacidad intelectual han supuesto una transformación en las respuestas sociales y en las políticas urbanas para este colectivo. El desarrollo autónomo y la procura de su bienestar son pilares fundamentales que se ven materializadas tanto en áreas de vivienda como de educación. Estos cambios en las estructuras convivenciales y el acceso cada vez más significativo de personas con discapacidad intelectual en las universidades hacen necesaria una respuesta multidisciplinar. Desde esta realidad y atendiendo al contexto de la vivienda actual, en respuesta a su creciente acceso a las instituciones educativas universitarias que buscan fomentar la autonomía e integrar sus demandas, se presenta un modelo de viviendas amables para estudiantes universitarios/as con discapacidad. Se exponen factores que deben considerarse, tanto referentes a las propias viviendas denominados “Inside” como al entorno de las mismas, que son los “Outside”. Su desarrollo contribuirá hacia un nuevo modelo de viviendas más sostenible e inclusivo, el cual posibilitará el desempeño autónomo del estudiantado con discapacidad intelectual en las distintas esferas de su vida.
This study analyzes the impact of corruption on the performance of brazilian firms as they approach the technological frontier. To this end, it was developed a static model of endogenous growth in a Schumpeterian environment. Under the equilibrium conditions in the model, the appropriation mechanisms of innovative firms exert a dual effect on the rate of technical progress, known as the 'appropriability paradox'. This paradox linked to corruption reveals that a persistent demand for illicit practices, as an attempt to guarantee appropriation of gains and protection from fraudulent contracts, can lead the economy towards a non-convergence trap. Using a sample of 3,444 companies according to World Bank microdata and efficiency scores using the non-parametric technique of order-alpha, the results show that advances towards the frontier entail increasing costs with the presence of corruption. These facts were observed both for the total sample (Brazil) and for firms in the state of Ceará.
Travel cost method (TCM) is based on the demand theory and assumes that the demand for a recreational site is inversely related to the travel costs that a certain visitor must face to enjoy it. The Individual Travel Cost Model (ITCM) has been employed in the research. Thus, the main objective of this study is to estimate the Economic Value of Mount Arayat National Park as a recreational site using the individual travel cost model (ITCM). A researcher-made questionnaire checklist and online survey (google forms) data collection method are employed to obtain the primary data from 235 sample visitors using the purposive sampling technique. Visitors’ visitation records from the management of the park were also used as a secondary data in this study. Peak season (January to April which has an average of 1591 visitors) and the off-season months (May to December which has an average of about 886 visitors) was identified as well as the problems encountered by the visitors during their visitation. This study also suggested strategies that can improve the recreation services of the park. Poisson regression analysis has been conducted to estimate the basic TCM model. The finding for ITCM shows that the Consumer Surplus value per trip is PHP 1,466.60. It was concluded that the aggregate annual Recreational Value of the park is approximately PHP 18.4 million, calculated based on the entire visitors within year 2019.
La inclusión financiera se ha convertido en un componente esencial para el desarrollo económico de los países de ingresos medios y bajos. El objetivo de este estudio es investigar la relación entre la inclusión financiera y el crecimiento económico a nivel territorial en Ecuador para el periodo comprendido entre 2015 y 2020, así como la dependencia espacial entre los territorios. Se dispone de información financiera detallada de diferentes tipos de instituciones financieras (bancos privados y cooperativas de ahorro y crédito), así como de información sobre el valor agregado bruto de las diferentes provincias del país que representan las circunscripciones territoriales analizadas. El estudio aborda metodológicamente la construcción de un índice de inclusión financiera que incluye las dimensiones de acceso, uso y profundización financiera; adicionalmente se construyen dos modelos autorregresivos espaciales, SAR y SARAR, y un modelo MCO para el valor agregado bruto y la inclusión financiera. Los hallazgos derivados del análisis espacial reflejan dependencia espacial en las variables analizadas entre algunos grupos de provincias, actuando algunas provincias como nodos de desarrollo. Por otro lado, en el modelo SAR, los resultados arrojan que la inclusión financiera tiene impacto positivo, un aumento de 10% en el índice de inclusión financiera producirá un aumento de 1,34% en el valor agregado bruto; y, en el modelo SARAR un aumento del 10% en el índice de inclusión financiera produciría un crecimiento de 1,235% en el valor agregado bruto a nivel provincial.
Si bien el mundo tecnológico ha cambiado los requisitos en las contrataciones, no está por demás que los aspirantes tengan un talento que los haga atractivos para las empresas. Talento que ayudaría a los jóvenes a poner condiciones para laborar, considerando aspectos económicos y de responsabilidad social. Presentamos un modelo de teoría de juegos con información asimétrica, donde la asimetría recae en los jóvenes por desconocer la responsabilidad social de las empresas. Así, construimos un mecanismo para decidir si conviene contratarse, considerando la brecha salarial como medida de responsabilidad social y un modelo logit para detectar las creencias objetivas.
The urgency for transition to a low-carbon economy has intensified the need for most emerging economies, including Morocco, to adopt sustainable energy growth policies. However, Morocco faces significant challenges in this transition, as fossil fuels still account for 90% of its total energy mix. With a 37% proportion of renewable energy in its capacity, Morocco now is one of the top producers of clean energy in Africa and the MENA region. Thus, we investigated the effect of financial development, human capital, and technological innovations in scaling up the clean energy transition in Morocco using the Fourier Bootstrap Autoregressive Distributed Lag approach from 1990-2021. The analysis revealed that financial development has a positive impact on the clean energy transition, this implies an increase in the short run as well as in the long run in Morocco. Human capital was also found to decelerate the energy transition in the country; this can be attributed to the lack of social awareness coping with the new transition. Furthermore, Policymakers should prioritize the strengthening of financial institutions and human capital capacity to facilitate the transition to sustainable energy.
