Search

The breakthrough potentials of research papers can be explained by their boundary-spanning qualities. Here, for the first time, we apply the structural variation analysis (SVA) model and its affiliated metrics to investigate the extent to which such qualities characterize a group of Nobel Prize winning papers. We find that these papers share remarkable boundary-spanning traits, marked by exceptional abilities to connect disparate and topically-diverse clusters of research papers. Further, their publications exert structural variations on a scale that significantly alters the betweenness centrality distributions in existing intellectual space. Overall, SVA not only provides a set of leading indicators for describing future Nobel Prize winning papers, but also broadens our understanding of similar prize-winning properties that may have been overlooked among other regular publications. [ABSTRACT FROM AUTHOR]

The development of human society and the production and operation activities of enterprises have brought about global warming, resulting in frequent natural disasters. It has become the consensus of all countries in the world to develop a green and low-carbon economy. Under this background, enterprises, as the main body of economic activities, especially energy industry enterprises, should optimize and upgrade the traditional production and operation mode with high pollution, high consumption, and low output to a high-efficiency and low-pollution mode, and pay attention to the co-ordinated development of economic benefits, social benefits, and ecological benefits. Financial performance evaluation indicators have become the main basis for senior leaders of energy industry enterprises to make decisions and evaluate the low-carbon economic benefits of enterprises. This paper constructs a set of financial evaluation index systems of energy industry enterprises under the background of a low-carbon economy from four dimensions: profitability, asset quality, debt risk, and business growth. The analytic hierarchy process (AHP) is used to measure the comprehensive contribution of financial indicators of low-carbon production and operation. The purpose of this study is to provide scientific financial management decisions for energy enterprises to reduce costs and increase the efficiency and low-carbon operation under the background of a low-carbon economy. The research results show that the comprehensive evaluation index system after the traditional financial evaluation index of energy industry enterprises is integrated with the evaluation index of a low-carbon economy can help enterprises make more correct and effective financial decisions in the process of survival, development, and growth, and, at the same time, the financial evaluation index of a low-carbon economy should pay more attention to the indicators with a higher comprehensive contribution, so as to effectively promote the low-carbon operation efficiency of enterprise production, management, and sales. Compared with other research results, this paper innovatively constructs a financial management decision-making index system for measuring the low-carbon operation of energy enterprises in theory, which has important value in guiding energy enterprises to reduce costs and increase the efficiency and low-carbon operation in practice. [ABSTRACT FROM AUTHOR]

Cost estimating in the construction industry is challenging due to the high uncertainty associated with the supply chain, especially after the COVID-19 pandemic. Some research studies have addressed such problems by developing models that predict material cost. In fact, all material can be interconnected and interrelated with lead-lag relationships such that any inflation in one material's price can be associated with inflation in other materials' prices, referred to as transmission of inflation. Despite the latter, none of the existing studies have investigated inflation transmission among all construction materials. This paper fills this knowledge gap. The authors used a multistep research methodology. First, Producer Price Index (PPI) data for 16 construction materials were collected and sorted. Second, the vector autoregression technique was used to model the relationships between each pair of material and subsequently validate the associations using the Granger causality test. Third, network analysis was performed to identify the inflation transmission capacity (out-degree centrality), inflation susceptibility (in-degree centrality), and inflation intermediatory capacity (betweenness centrality) for each material. Finally, modularity-based clustering was conducted to categorize the materials based on their price indices' interconnections and examine inflation transmission path among different sectors of construction-related material. The results show that metals and plastic products are generally the highest transmitters of inflation to other construction material including "Fabricated structural metal products" and "Plastic construction products." Furthermore, the results show that "Concrete products," "Flat glass," "Brick and structural clay tile," and "Architectural coatings" are also high transmitters of inflation and thus can be key indicators of increase in the overall construction cost. This paper provides the industry stakeholders with leading indicators and early warning signs for the inflated material prices. Contractors and owners can utilize those warning signs to enhance their procurement plans and budgeting decisions. [ABSTRACT FROM AUTHOR]

In situ resource utilization (ISRU) activities are receiving increasing attention, both from space agencies and among the international science and industrial community. Prominent examples of ongoing ISRU space programs are the NASA Artemis program and the Terrae Novae program run by the European Space Agency. In technical sciences, there are at least three groups of activities related to ISRU: prospecting bodies in the context of space missions, technological investigations related to surface infrastructure and operations, and conceptual analyses of future mining activities. The present paper belongs to the third group and brings new insights into a potential open pit mine operating on the Moon. There are several novel contributions: the definition of the objectives of the mine, based on economic indicators; a conceptual description of a pit architecture dedicated to excavating ilmenite-rich feedstock; and a qualitative and quantitative description of the chosen processes and the mine's topology. In the paper, there are also added links to other papers connected with ISRU activities. [ABSTRACT FROM AUTHOR]

Livestock's live body dimensions are a pivotal indicator of economic output. Manual measurement is labor-intensive and time-consuming, often eliciting stress responses in the livestock. With the advancement of computer technology, the techniques for livestock live body dimension measurement have progressed rapidly, yielding significant research achievements. This paper presents a comprehensive review of the recent advancements in livestock live body dimension measurement, emphasizing the crucial role of computer-vision-based sensors. The discussion covers three main aspects: sensing data acquisition, sensing data processing, and sensing data analysis. The common techniques and measurement procedures in, and the current research status of, live body dimension measurement are introduced, along with a comparative analysis of their respective merits and drawbacks. Livestock data acquisition is the initial phase of live body dimension measurement, where sensors are employed as data collection equipment to obtain information conducive to precise measurements. Subsequently, the acquired data undergo processing, leveraging techniques such as 3D vision technology, computer graphics, image processing, and deep learning to calculate the measurements accurately. Lastly, this paper addresses the existing challenges within the domain of livestock live body dimension measurement in the livestock industry, highlighting the potential contributions of computer-vision-based sensors. Moreover, it predicts the potential development trends in the realm of high-throughput live body dimension measurement techniques for livestock. [ABSTRACT FROM AUTHOR]

Since the power generation structures and load characteristics in each province in China are quite different, the distribution of peak regulating resources and demands are extremely imbalance. Restricted by a low power marketization degree, peak regulating resource shortages, and transmission channel blocks, the efficient utilization of new energy is facing greater pressures. In order to improve the mutual aid in regional power grids and to obtain more precise simulation results, this paper proposes a two-layer optimization dispatching model, considering the mutual aid of peak regulation resources between each province. It determines the optimal startup mode and the units' power output in each province and obtains the power output arrangements for all the units and the technical and economic indicators. The model and the solution method are original and innovative. And it effectively solved the unequal distribution problem between the peak regulating demands and resources of each provincial power grid. Finally, taking an actual regional power grid in China as an example, the simulation results show that the proposed model can significantly improve the utilization rate of new energy, which verifies the effectiveness and feasibility of the proposed model and methods presented in this paper. [ABSTRACT FROM AUTHOR]

In the current knowledge-based economy, the abilities of the national research system are a key driver of the country's competitiveness and socio-economic development. This paper compares the scientific standing of the OECD countries and eight other relevant economies. We use a bibliometric indicator of research performance, applied first at the individual level. This approach avoids the distortions of the aggregate-level analyses extant in literature and practice, which overlook the different publication intensities across research fields. We find a strong correlation between research performance and the economic competitiveness of nations and a moderate but significant correlation between research performance and the propensity to spend on research. [ABSTRACT FROM AUTHOR]

This paper discusses the financial determinants of the efforts of local government units (LGUs) to invest in the area of energy transition (ET). The main objective is to verify the links between the scale, directions, and funding sources of LGUs' investments in ET and their budgetary situation described by the level of income independence, budget result, and debt level. The general research hypothesis assumes that the ET investment activity of LGUs is associated with their financial situation. The analysis covers the period 2019–2022 and uses data from the questionnaire-based survey conducted in 2023 among 181 LGUs in the Podkarpackie region in southern Poland. Non-parametric tests were employed to verify the association between the LGUs' ET investment activity and their financial situation: the Chi2 test, the Mann–Whitney U test, the Kruskal–Wallis test, and the Kendall's Tau correlation. Financial aspects were shown to influence the scale of municipal ET investments, as well as the type of projects implemented. Among the analysed financial indicators, the debt level was the most important constraint for LGUs to make their own ET investments. The debt level not only determined the scale of municipal ET investment, but also influenced decisions on the type of investments. [ABSTRACT FROM AUTHOR]

Recently, sustainable economic performance (SEP) has been the foremost requirement due to uncertainty of the economy and environment. This issue needs best practices and governance and also needs researchers' focus. Thereby, the paper aims to assess green supply chain (SC) practices, green SC governance and their role in the achievement of SEP in the manufacturing sector of China. The paper also attempts to explore the moderating effect of organizational support in proposed framework. PLS-SEM model was employed to test model's reliability and validity. The very same method has applied to test the linkage among outlined constructs. Obtained results confirms the moderating impact of organizational support among traditional governance, relational governance and the achievement of SEP in the manufacturing industry in China. This article provides guidelines to the regulators in developing policies related to the achievement of SEP using green SC practices and governance. [ABSTRACT FROM AUTHOR]

The production of plum and cherry, as stone fruit species, occupy a significant place in the plant agricultural activity of the Republic of Serbia. In this paper, on the basis of data from selected family holdings in the southern part of Serbia, the production results and evaluation of the economic justification of these two fruit species were investigated. Data collected through a survey were used for the research, and the economic evaluation was performed using static calculative methods. The most important economic indicators determined were: cost price, net profit (average amount), accumulativeness expressed through the rate and time period of investment capital. When producing plums, the average annual financial result is from 503,490 RSD/ha to 594,340 RSD/ha. The analysis determined that by investing RSD 100/ha in production of plum, 40 RSD is accumulated, and the average annual net profit is 425,313 RSD/ha. From the average amounts of net profit, investments made in raising plum trees plantations (1,080,000 RSD/ha) can be recovered during the third year of its exploitation. Although the yield of cherry per unit area is lower compared to the yield of plum, better economic results in the amount of 535,800 RSD/ha to 682,920 RSD/ha are achieved due to a much more favorable selling price per unit measure. For every RSD 100 invested in cherry production, 48 RSD of accumulation is achieved. The average net profit amounts to 492,099 RSD/ha, and the investments made in raising plantations of cherry trees (1,020,000 RSD/ha) can be recovered in the third year of its exploitation. In recent years, cherry have been very profitable fruit species in Serbia, due to the high demand and favorable selling price. With permanent education of fruit producers, as well as with various support measures at the state and local level, it is possible to contribute to the improvement of the existing business and improve the profitability of plums and cherry production. [ABSTRACT FROM AUTHOR]

Research background: The corporate debt situation can be considered a crucial factor influencing the future development of the financial performance of the firm. It is essential for every business entity to know its financial health, its strengths and weaknesses, and how its business has been affected by the COVID-19 pandemic and all the changes it has brought. Purpose of the article: The main aim of this paper is to explain and quantify the consequences of the COVID-19 pandemic, analyze changes in the growth of crucial determinants, and identify new trends in Slovak enterprises throughout the monitored period of 2018-2021. Methods: Hence, a statistically significant difference between the individual indicators due to the period in which the firms achieved these values was determined using the Friedman test. It determined whether the average values of the financial indicators remained constant over the period under review (the years 2018 and 2019 are considered pre-COVID-19 years, while 2020 and 2021 are years when the globe was already being impacted by the outbreak of the COVID-19 pandemic) or whether the individual values of the indicators differed significantly. Findings & value added: Considering that there are statistically significant differences in the indicators of self-financing ratio, current indebtedness ratio, and equity leverage ratio in all monitored periods except for the years 2020 and 2021, where the average values of these debt indicators are the same, the results indicate that the COVID-19 pandemic also negatively impacted the indebtedness of Slovak enterprises. Although this research paper, focusing on the financial performance of the firms in the post-pandemic period, is pioneering in Slovakia, the biggest contribution of the study is the application of the latest information, which could help in more precise monitoring of corporate financial stability and debt policy during the current challenging period. The obtained results provide important universal guidelines for building financial strategies improving long-term financial resilience of enterprises. [ABSTRACT FROM AUTHOR]

Early papers found empirical support for a natural resource curse—the notion that exporting natural resources is detrimental to economic growth. Later papers, using reportedly improved econometric models and data, largely reversed these early findings by estimating that natural resources improve economic performance. However, this changing coefficient on natural resource dependence over time may not only be a function of model or data quality. Masked by this evolution in the economics literature is the possibility that the fundamental relationship between natural resources and economic performance has changed over the past several decades. This paper sheds a new perspective on the substantial resource curse literature by repeatedly estimating a single econometric model on data that evolve over time. The coefficient on natural resource dependence is estimated to steadily increases with the passage of time from a value that is negative and significant (for 1970, the basis for much of the early literature) to a positive and significant value a few decades later. Whatever natural resource estimated initially with data from 1970 seems to have evolved into a resource blessing over time. [ABSTRACT FROM AUTHOR]

Agriculture plays a vital role in driving economic output and employment in SubSaharan African (SSA) countries. Despite some progress, agricultural productivity in SSA still lags behind other regions. Limited access to finance remains a significant impediment to improving agricultural productivity in Sub-Saharan Africa. This paper investigates the effect of financial proximity on agricultural productivity in Sub-Saharan African countries. The study primarily employs the system GMM estimator, chosen to address the endogeneity issue typical in macro panel data. This method is also wellsuited to our study because it accommodates a high number of cross-sections relative to the number of periods within each cross-section. Additionally, the IV-2SLS method is employed to check the robustness of the findings. The study uses an unbalanced panel for the 36 African countries with data for the period 2004-2019. Our findings show that increasing the financial proximity favors agricultural productivity in SSA countries. Specifically, the number of commercial bank branches (CBB) and the number of automated teller machines (ATM) per 100 000 adults, as indicators of financial proximity, have positive and significant effects on agricultural value added per worker in SSA. Additionally, our findings show that rainfall, arable land, and institutional quality are robust determinants of agricultural productivity. The positive effects of the number of CBB and the number of ATM are even more pronounced on agricultural productivity when coupled with strong institutional quality. Our findings suggest that improving financial services' accessibility in rural areas, coupled with enhanced institutional quality, regular rainfall, ample arable land, and increased access to water and land, are pivotal steps for achieving sustainable enhancements in labor productivity. This, in turn, leads to increased returns through value-added growth and expanded employment in the agricultural sector. [ABSTRACT FROM AUTHOR]

This paper discusses some comparative analysis between the pattern of economic performances in Asia and Western Europe during 1950s-2020s through political economies perspective. The Asian and Western European economic performances are investigated through some stylized facts in the sense of economic factors. Three analyses are used to explain the general pattern of these regions. First, this study examines the pattern of GDP growth per capita during the 1950s-2020s, focusing on several countries in this region. Second, the analysis captures the pattern of linkages of economic variables in this region related to the principle of Circular and Cumulative causation (CCC) and contradiction. Third, the analysis employs a historical perspective underpinned by the results in the second analysis. This third analysis is crucial to appreciating Asia's global economic performance and also the process of Western deterioration phenomenon through long wave, including the occurrence recession and financial crises. The institutions of globalization and neoliberalism that put the power of capital promoted a financial crisis several times during the decades of 1980s-2020. The financial crisis is depicted by contradictions in the structural linkages among economic factors in Western Europe over the period. [ABSTRACT FROM AUTHOR]

Recently, the economy in Guangdong province has ranked first in the country, maintaining a good growth momentum. The prediction of Gross Domestic Product (GDP) for Guangdong province is an important issue. Through predicting the GDP, it is possible to analyze whether the economy in Guangdong province can maintain high-quality growth. Hence, to accurately forecast the economy in Guangdong, this paper proposed an Elman neural network combining with wavelet function. The wavelet function not only stimulates the forecast ability of Elman neural network, but also improves the convergence speed of Elman neural network. Experimental results indicate that our model has good forecast ability of regional economy, and the forecast accuracy reach 0.971. In terms of forecast precision and errors, our model defeats the competitors. Moreover, our model gains advanced forecast results to both individual economic indicator and multiple economic indicators. This means that our model is independently of specific scenarios in regional economic forecast. We also find that the investment in education has a major positive impact on regional economic development in Guangdong province, and the both surges positive correlation. Experimental results also show that our model does not exhibit exponential training time with the augmenting of data volume. Consequently, we propose that our model is suitable for the prediction of large-scale datasets. Additionally, we demonstrate that using wavelet function gains more profits than using complex network architectures in forecast accuracy and training cost. Moreover, using wavelet function can simplify the designs of complexity network architectures, reducing the training parameter of neural networks. [ABSTRACT FROM AUTHOR]

The African Growth Opportunity Act (AGOA) has been a crucial trade and development initiative, offering preferential access to qualified Sub-Saharan African (SSA) countries to the United States market since its enactment in 2000. This paper presents a comprehensive review of scholarly articles and policy reports that analyze the impact of AGOA on the economic performance of SSA countries. Employing various econometric methods and data analysis techniques, researchers have investigated the effects of AGOA on trade flows, foreign direct investment (FDI) inflows, employment, economic growth, and poverty levels. The findings reveal that AGOA has positively affected the region's trade, particularly in apparel, textiles, and agriculture. However, its influence on promoting export diversification and attracting FDI is nuanced, with substantial heterogeneity among the beneficiary countries and industries within each country. While some SSA countries have experienced substantial export growth and FDI inflows, others have not fully leveraged the benefits of AGOA due to absorptive capacity constraints and governance challenges. AGOA's effectiveness in promoting broad-based employment, GDP growth, and poverty reduction remains an active area of inquiry, necessitating further research to understand the policy's sustained impact and inform future trade policy designs for SSA countries. [ABSTRACT FROM AUTHOR]

The values that people hold are linked to their economic performance. These links can be either direct or indirect, operating through moderating variables such as social network participation, interpersonal trust, trust in institutions, human capital, managerial skills and hours worked. In this paper these effects are studied using structural equation modelling (SEM) methodology applied to European Social Survey data from 28 European countries in 2018. Schwartz classification of values is used, distinguishing between Self-Enhancement (Power, Achievement), Openness to Change (Self-Direction), Conservation (Tradition, Security, Conformity) and Self-Transcendence (Universalism, Benevolence) values. It is found that Power has the strongest positive direct effect on economic performance, further strengthened by a positive indirect structural effect through hours worked. Self-Direction is indirectly positively linked to economic performance through higher managerial skills and hours worked. Tradition has a strong negative direct effect on economic performance. Security is indirectly negatively linked with economic performance, owing to its negative effects on interpersonal trust, management skills and hours worked. Some of the identified effects are context-dependent and vary across European welfare state regimes. For example, Power is statistically significantly linked to economic performance only in the liberal and conservative regime. Values promoted by respective welfare state regimes are not necessarily associated with higher incomes within those regimes, e.g., Tradition and Security values promoted in the conservative and Mediterranean regime are associated with lower incomes. These findings may lead to a range of policy implications, particularly in relation to the policies on immigration, demographics, the labor market, and work-life balance. Unfortunately, due to the cross-sectional character of the dataset, causal relations among the variables of interest could not be identified. [ABSTRACT FROM AUTHOR]

Noncommunicable diseases and mental health conditions (referred to collectively as NMHs) are the greatest cause of preventable death, illness, and disability in South America and negatively affect countries' economic performance through their detrimental impacts on labor supply and capital investments. Sound, evidence-based policy-making requires a deep understanding of the macroeconomic costs of NMHs and of their distribution across countries and diseases. The paper estimates and projects the macroeconomic burden of NMHs over the period 2020–2050 in 10 South American countries. We estimate the impact of NMHs on gross domestic product (GDP) through a human capital-augmented production function approach, accounting for mortality and morbidity effects of NMHs on labor supply, for the impact of treatment costs on physical capital accumulation, and for variations in human capital by age. Our central estimates suggest that the overall burden of NMHs in these countries amounts to $7.3 trillion (2022 international $, 3% discount rate, 95% confidence interval: $6.8–$7.8 trillion). Overall, the macroeconomic burden of NMHs is around 4% of total GDP over 2020–2050, with little variation across countries (from 3.2% in Peru to 4.5% in Brazil). In other words, without NMHs, annual GDP over 2020–2050 would be about 4% larger. In most countries, the largest macroeconomic burden is associated with cancers. Results from the paper point to a significant macroeconomic burden of NMHs in South America and provide a strong justification for investment in NMH prevention, early detection, treatment, and formal and informal care. [ABSTRACT FROM AUTHOR]

Nowadays, the international situation is severe and complex, and the structural issues within the Chinese economy are prominent. Consequently, the financial risks faced by Chinese listed companies continue to escalate. Hence, it is of great practical significance to furnish effective early warnings for financial crises in listed companies. In this paper, we first employ web crawler technology and natural language processing technology to assess four text-linguistic features in the Management Discussion and Analysis (MD&A) section of the annual financial reports of listed companies in China from 2011 to 2020. These features are text tone, forward-looking, readability and similarity. Subsequently, we combine these features with traditional financial indicators and explore thirteen mainstream machine learning models to comparatively analyze their effectiveness in predicting financial crises in listed companies. The empirical findings of this research reveal that MD&A text readability and similarity indicators contribute valuable incremental information to prediction models, whereas text tone and forward-looking indicators exhibit the opposite effect. The latter two indicators can be manipulated more effortlessly by management, as this study's empirical findings indicate no evidence of their contributions in incremental informational value. In fact, the forward-looking indicator even introduces additional noise to the prediction. Finally, by comparing the early warning effects of thirteen machine learning models, it is found that RF, Bagging, CatBoost, GBDT, XGBoost and LightGBM models maintain stable and accurate sample recognition ability. In general, this paper constructs a more effective financial crisis early warning model by exploring the MD&A text-linguistic feature indicators, thereby offering a fresh research perspective for further investigations in this field. [ABSTRACT FROM AUTHOR]

Improving the efficiency of converting natural resources into social benefits is an important issue for sustainable development in today's world. Based on this background this paper applies the super-efficient SBM model with non-expected output to measure the ecological welfare performance (EWP) of Chinese provinces from 2005–2019, and explores the relationship between government competition and EWP under different assessment systems. The research results show that government competition under economic performance assessment is self-interested and short-sighted, which can negatively affect ecological welfare performance in the current period as well as in the next four years. In contrast, government competition under the environmental assessment system promotes EWP in both the current and long term, balancing short-term and long-term benefits. The results of the spatial GMM found that government competition under economic performance appraisal can deteriorate EWP in local as well as surrounding areas, but government competition under the environmental assessment system can achieve an increase in local ecological welfare performance and the spillover effect is not significant. To alleviate the limitations of a single appraisal system, this paper incorporates both economic and ecological appraisals into the multidimensional appraisal system. When the weights of both are between 1:9 and 3:7, the government competition under multidimensional performance appraisal can promote both current and longer-term EWP, and achieve its own ecological welfare performance without affecting the surrounding areas. [ABSTRACT FROM AUTHOR]

Addressing risks and pandemics at a country level is a complex task that requires transdisciplinary approaches. The paper aims to identify groups of the European Union countries characterized by a similar COVID-19 Resilience Index (CRI). Developed in the paper CRI index reflects the countries' COVID-19 risk and their readiness for a crisis situation, including a pandemic. Moreover, the study detects the factors that significantly differentiate the distinguished groups. According to our research, Bulgaria, Hungary, Malta, and Poland have the lowest COVID-19 Resilience Index score, with Croatia, Greece, Czechia, and Slovakia following close. At the same time, Ireland and Scandinavian countries occupy the top of the leader board, followed by Luxemburg. The Kruskal-Wallis test results indicate four COVID-19 risk indicators that significantly differentiate the countries in the first year of the COVID-19 pandemic. Among the significant factors are not only COVID-19-related factors, i.e., the changes in residential human mobility, the stringency of anti-COVID-19 policy, but also strictly environmental factors, namely pollution and material footprint. It indicates that the most critical global environmental issues might be crucial in the phase of a future pandemic. Moreover, we detect eight readiness factors that significantly differentiate the analysed country groups. Among the significant factors are the economic indicators such as GDP per capita and labour markets, the governance indicators such as Rule of Law, Access to Information, Implementation and Adaptability measures, and social indicators such as Tertiary Attainment and Research, Innovation, and Infrastructure. [ABSTRACT FROM AUTHOR]

The present paper addresses a topical issue for the agricultural production sector and it is based on an economic-financial indicators analysis for a series of 17 main agricultural crops. The practical research was carried out with information and data for 10 agricultural holdings in Iaşi County. They operate in the vegetable production sector and have a solid commercial representation on the national market. The main indicators used in the study are: crops and shared areas for each of the 10 analyzed units, considering the relevance of crops for the national economy and economic-financial indicators relevant for the design of the production activity: turnover, profit, employes number. The reference year for which the research was carried out is 2021. The work methodology mainly uses quantitative methods and descriptive analysis, with the processing and interpretation of data that have been organized in a design configured according to the specifics of the paper. In addition, qualitative information collected through interviews is used. The results of the paper indicate the relevance of basic agricultural crops for the performance of large enterprises. [ABSTRACT FROM AUTHOR]

The aim of the research paper is to find out if the republic of Georgia is likely to have emerging market. Paper analyzes different aspects of emerging market, included: historical background, political situation (international rankings, the role of the international society), economic conditions (FDI inflows, major economic indicators), legal framework. The paper argues that recent economic and political reform efforts have been successful, however, a key concern is the effective implementation of the legal and policy framework for investment environment, leading to measurable improvements. [ABSTRACT FROM AUTHOR]

The paper aims to determine the organizational structure and organizational culture of a successful construction company from Bosnia and Herzegovina. Additionally, the paper provides an insight into their interdependence and impact on the overall business operations of the company. The questionnaire examined the main dimensions of organizational structure: formalization, centralization, standardization and specialization. Cameron and Quinn’s Organizational Culture Assessment Instrument was used to examine the organizational culture at the company, while the analysis of the company’s business efficiency was informed by Kaplan and Norton’s Key Performance Indicators: financial, internal business processes, customer, and learning and growth perspectives. After the reliability of the measuring scales used were confirmed by calculating the Cronbach alpha coefficient, the Relative Importance Index determined which dimensions of the organizational structure and culture, and which efficiency indicators have the greatest influence on the design of the company's business system. According to the subjective opinion of the employees who participated in this research, the company can be characterized as hierarchical, highly formalized and structured, and customer-oriented. [ABSTRACT FROM AUTHOR]

THIS PAPER AIMS TO DEVOTE AN ANALYTIC EYE ON THE LIBERALIZATION COURSE ADOPTED BY THE POLISH GOVERNMENT AFTER THE FALL OF THE COMMUNIST REGIME IN 1989. AFTER THE PEACEFUL TRANSITION FROM A TOTALITARIAN COMMUNIST INSPIRED REGIME TO A DEMOCRATIC FORM OF GOVERNMENT, THE NEW POLISH POLITICAL ELITE HAD TO EMBARK IN REFORMS, AIMING TO GENERATE ECONOMIC PROSPERITY AND RECOVER THE BACKWARDNESS COMPARED TO THE WESTERN COUNTRIES, FROM WHICH ADOPTED THE DEVELOPMENT MODEL. THIS PAPER ARGUES THAT IF THE PROPER ECONOMIC AND POLITICAL INSTITUTIONS ARE DEVELOPED BY THE STATES, THEN THE POVERTY IS REDUCED, FROM THE THEORETICAL PERSPECTIVE OF INSTITUTIONAL ECONOMICS, AS PROPOSED BY DARON ACEMOGLU AND JAMES A. ROBINSON. BASICALLY, THIS PAPER ARGUES THAT THE ADOPTION OF INCLUSIVE POLITICAL AND ECONOMIC INSTITUTIONS GENERATED PROSPERITY AND ECONOMIC POSITIVE PERFORMANCE FOR POLAND AFTER THE FALL OF THE EXTRACTIVE COMMUNIST REGIME. [ABSTRACT FROM AUTHOR]

The paper aims to present models of agricultural production optimization as tools for managers to increase yield, crop structure, crop rotation, increased efficiency and profitability. The two optimization models are: Case 1: Optimization of yield depending on wheat price and subsidy for increasing net return and profitability in wheat culture; Case 2: Optimal model for optimizing crop rotation in cereal culture with maximum income, having two solutions: (a) Basic optimal primal solution and (b) Basic optimal dual solution. The methodology included the calculations regarding the specific indicators reflecting the economic efficiency in wheat cropping for Case 1 and determination of the optimal primal and dual solutions assisted by SOLVER application from MS Excel for Case 2. The two examples come from vegetal farming but, other models of optimization could be developed in animal production for improving livestock structure by species and category and also in animal feeding setting up optimized feed ratios to sustain production. [ABSTRACT FROM AUTHOR]

In order to improve the laws and regulations of the financial system, in the construction of laws and regulations, the traditional financial risk Early Warning (EW) model is optimized. The financial prevention and control measures with legal protection are implemented to warn the financial risks, which plays an important role in the construction of the rule of law in the Financial Market (FM) and the establishment of financial risk prevention and control laws and regulations. This paper combines the deep learning model and the Markov regime Switching Vector Auto Regression (MS-VAR) model and constructs a regional financial risk EW model from the following aspects: macroeconomic operation EW indicators, regional economic risk EW indicators, regional financial institution risk EW indicators. The model is empirically researched and analyzed. The results show that the fluctuation trend of the macroeconomic pressure index in the time series is relatively large, and the overall fluctuation of the regional economic pressure index is small, and fluctuates around 0 in most periods. After the financial crisis, local governments stepped up their supervision of non-performing corporate and household loans. From 2011 to 2018, the non-performing loan ratio began to decline, and the overall fluctuation of the regional financial comprehensive stress index was small, fluctuating around 0. Due to the lack of legal regulation, from the perspective of the regional economy, the risk level is more likely to change from low risk to moderate risk, while the risk status is less likely to change from high risk to moderate risk. From the perspective of regional financial institutions, the probabilities of maintaining low risk and moderate risk are 0.98 and 0.97, respectively, which is stronger than maintaining the stability of high risk. From the perspective of the state transition of the regional financial risk composite index, the probability of maintaining low risk and high risk is 0.97 and 0.93, which is higher than maintaining the stability of medium risk. The Deep Learning (DL) regional financial risk EW MS-VAR model has strong risk prediction ability. The model can better analyze the conversion probability of regional financial risk EW index and has better risk EW ability. This paper enhances the role of legal systems in financial risk prevention and control. The regional financial risk EW model incorporating financial legal indicators can better describe the regional financial risk level, and the EW results are basically consistent with the actual situation. In order to effectively prevent financial risks and ensure the safety of the financial system, it is recommended that the government improve local debt management, improve financial regulations and systems, and improve the legislative level of financial legal supervision. [ABSTRACT FROM AUTHOR]

This paper investigates the complex causal relationships between various types of environmental regulatory instruments (ERI) and agri-firms' technological innovation employing fuzzy set qualitative comparative analysis (fsQCA). The study finds a well-designed set of ERI can promote technological innovation in agribusiness; control-command ERI cannot promote technological innovation in agribusiness solely, market-incentivized ERI is indispensable in promoting firms' innovation performance, implicit ERI plays an important role in promoting firms' innovation and voluntary ERI does not play a significant role in promoting firms' technological innovation. The government should coordinate among various types of ERI and improve the design of ERI to achieve a win-win situation for both economic and environmental performance in the agriculture sector. [ABSTRACT FROM AUTHOR]

Carbon price prediction is of great importance to regulators and participants in the carbon trading market. It is the basis for developing policies related to the carbon trading market and stabilizing that market. Considering the numerous factors that influence carbon prices in China, dimensionality reduction is needed to improve the prediction accuracy and efficiency. However, the traditional dimensionality reduction methods fail to fully consider the role of influencing factors, which has certain limitations. In this paper, a new dimensionality reduction method, namely scaled principal component analysis (s-PCA), is employed to improve the prediction accuracy of carbon prices. Firstly, a factor library that influence carbon prices is constructed from three perspectives: technical indicators, financial indicators and commodities indicators. Then, the s-PCA method is used to reduce the dimensionality of factors influencing carbon price. Next, two different methods are used to predict carbon prices, including traditional regression method and Long Short-Term Memory (LSTM) method. Finally, the economic value of the s-PCA method is examined by constructing investment portfolios. The empirical results of the Hubei Emissions Exchange show that the s-PCA model outperforms other competing models both in- and out-of-sample. In addition, the LSTM model could improve the performance of the s-PCA model in carbon price prediction. From a market timing perspective, investors can achieve a greater return and a larger Sharpe ratio using the s-PCA method than using other comparative methods and buy-and-hold strategy. Therefore, the s-PCA method is effective and robust in predicting carbon price. [ABSTRACT FROM AUTHOR]

This paper aims to identify and categorize the factors influencing consumer goods' value into ecological and economic dimensions and subsequently compare them. The analysis employs the Allegro Reviews (AR) dataset, comprising post-purchase product reviews, with a focus on a sample of 1,400 randomly selected reviews from a pool of 10,615 comments. Through this examination, distinct influencing factors are identified, categorized as either ecological or economic, and their frequency of reference in online reviews was compared. The research findings show that consumers consistently address economic dimensions in their reviews. Notably, emphasis is placed on goods' quality, pricing, and the price-quality relationship. On the other hand, ecological aspects receive limited attention in reviews, suggesting their lesser significance to consumers compared to economic considerations. This study's implications for theory and practice indicate that companies should prioritize economic aspects in their value creation endeavors, relegating ecological factors to a secondary role. However, from a global standpoint, enterprises must incorporate ecological dimensions during the value creation process to avert environmental degradation, which could otherwise undermine overall societal quality of life. In terms of originality and value, this research diverges from typical consumer choice studies that rely on questionnaires. Instead, it analyzes actual post-purchase product reviews, providing insights into tangible elements contributing to goods' value, thus bypassing reliance on mere declarations. [ABSTRACT FROM AUTHOR]

Research background: The climate crisis is one of the greatest challenges the world is facing in the 21st century. The global response to this problem must comprise transitions in land and ecosystems, energy, urban, infrastructure, and industrial systems and a transformation in enterprise and risk management. With the global pressure to fight climate change and achieve the Sustainable Development Goals, the innovative potential of Industry 4.0 technologies (blockchain, Big Data analytics, the Internet of Things, cloud computing, artificial intelligence, 3D additive manufacturing and technology platforms) has been subject to enormous interest among researchers and practitioners. Additionally, the COVID-19 pandemic has accelerated technology investment and digital transformation in many business areas, potentially including sustainability risk management. Purpose of the article: The purpose of this paper is to explore the scope of Industry 4.0 technology implementation in sustainability risk management and its financial impact. Methods: Based on the survey research, the authors verified if enterprises implementing Industry 4.0 technologies during the last five years are benefiting from their investment depending on the number of technologies. Due to the ordinal measurement scale of the analyzed variables, the verification of hypotheses was carried out using the Mann-Whitney U test. Findings & value added: In the opinion of the managers surveyed, the number of Industry 4.0 technologies implemented in the sustainability risk management process does not affect the enterprise's aggregate Financial Performance Indicator, individual financial indicators (ROA, ROE, OPM, NPM and FLR) and the enterprise's ability to manage financial risk. This study contributes to the literature on the technological transformation of the sustainability risk management process and its financial importance. The design and implementation of sustainable development strategies imply a long-term perspective, including the achievement of risk management effects in this area. The implementation of one technology, let alone two or more, is a difficult and time-consuming management challenge before synergy effects are achieved in an integrated technological eco-system. [ABSTRACT FROM AUTHOR]

Grouper aquaculture is a rapidly growing and dynamic industry within the Taiwan aquaculture sector that serves as an important source of income generation. Farming fishes at a better location (FFABL) is a promising production strategy. This study evaluated the production and economic performance of grouper farming in Taiwan. This investigation employed two steps: (1) a cost–benefit analysis to determine the main component affecting profitability; and (2) multivariate statistics to clarify the relationship between biological and economic factors. The findings suggest that the best choice of species is hybrid giant grouper that generates and highlights a positive income, viable benefit–cost ratio and profit rate. The study found the feed management of hybrid giant groupers requires more consideration due to its low feed conversion ratio. The producers need to replace trash fish in commercial feed during the production cycle to ensure better feed management. Finally, this paper argues that feed is the main constraint for grouper farming, which is sensitive to any change in feed productivity, and this constraint must be solved to sustain the grouper industry in Taiwan. [ABSTRACT FROM AUTHOR]

The paper aims to identify the essential factors affecting CFROI (based on a comparative analysis of theoretical sources, case studies and conclusions from our research) with a subsequent analysis of the implementation process of this method. The consequence of the connection is the systematic, holistically incorporated principles of the method into managers' decision-making. The procedure for applying the CFROI method consists of eight parts, namely data collection, determination of the value of depreciated assets and their useful life, calculation of the value of depreciated assets at current prices, calculation of the value of non-depreciated assets, determination of the value of the investment, quantification of cash flow, calculation of the CFROI indicator and its economic interpretation. [ABSTRACT FROM AUTHOR]

Background: Only a few studies explore the role of nurses in genetic counselling and genetic health care, and none of them is related to orphan diseases. In addition, few studies address the issue of finding variables that might affect the economy of a service or perform a cost-effectiveness analysis of a having genetic nurse at a unit. Methods: A multidisciplinary panel of experts working in the hospital was set up to identify sensitive indicators and remove confounding variables. This panel evaluated efficiency and effectiveness indicators and drafted a questionnaire to estimate patient perception of the quality of the service. Data were captured from different sources, including the hospital patient database and a web-accessible platform for data collection. More than 600 clinical evaluations of 400 patients were considered, and economic parameters were studied by applying Porter's Time-Driven Activity-Based Costing methodology to evaluate costs and outcomes. Additionally, an anonymous, semi-structured, paper-and-pencil interview questionnaire was given to patients at their periodic follow-ups. Results: The results showed an increase in the quality of patient management, more accurate data capturing, and higher quality ambulatory care. In fact, approximately 70% of the respondents reported positive changes. In addition, a parallel economic analysis explored indicators influencing economic impact, and outcomes showed positive results with the quality of outcomes improving more compared to the increase in costs. Conclusions: The variety of evaluated issues highlighted that having a nurse in a genetic service and at day clinic activities resulted in better access, better scheduling, more satisfaction, and proved to be a cost-effective solution for patients affected by rare diseases. [ABSTRACT FROM AUTHOR]

Poland is an important producer of rapeseed used in the biofuel industry. The rate of production of the biofuel industry increased after Poland's accession to the European Union (EU). The reasons for these changes are numerous, of which the European Union's energy policy is the most important. This paper aims to analyze the performance of the biofuel industry in Poland in view of changes in the market. Moreover, I evaluated changes in the biofuel industry after Poland's accession to the EU. In addition, I analyzed the fixed and current assets of the Polish biofuel. The hypothesis that the price of rapeseed oil is the key determinant of profitability in the biodiesel industry was formulated. A statistical analysis proved the second hypothesis stating that the net profit of biodiesel companies depends on biodiesel production to the greatest extent. The time range of the analysis was 2005–2021. To analyze the economic performance of the biofuel industry in Poland, these changes were used. A regression analysis to find factors influencing the economic performance of the biofuel industry was used. More and more oils are used for the production of first-generation biofuels. Refined rapeseed oil also increased from 386.5 thousand tons to 780.6 thousand tons. Such numbers demonstrate the development of biofuel markets. [ABSTRACT FROM AUTHOR]

Cultivation of blueberries is an entrepreneurial activity recently approached by local farmers, a business with a fairly high economic potential. The nutritional and economic value of this crop fuels an active interest for both consumers and local producers. However, blueberry cultivation represents a risky challenge for potential domestic producers. This fact is conditioned, mainly, by the local natural factors that are unsuitable for the development and fruiting of the blueberry, respectively, for the creation of conditions similar to the natural habitat of the blueberry, considerable investments are required. The aim of the paper is to present a series of calculations proving that blueberry cultivation represents a profitable business in Moldova. The used methodology is based on comparative, analytical methods, and financial indicators that prove the business profitability. With a thorough elaboration of the whole business process, with all the calculations and analysis of the estimated results, as well as the exact forecasting of the risks and the impact, the cultivation and production of blueberries in the conditions of our country can become a successful business. [ABSTRACT FROM AUTHOR]

The determination of the influences of the management on the economic performance of an agricultural holding can be an important process for the farm manager, as a source of information which can consist in a valuable component needed in the decisional process. In this matter, the analysis is useful during a specific period of time, which also comprises future predictions. In this paper, we will present a study of the connection between the farm management approach, represented by several characteristics of the farm and the farmer, and the farm economic performance, represented by the financial result of the farm activity. This study is presented as a comparative analysis of two methods that establish the existence and intensity of the mentioned connection, the first one being based on statistical methods and instruments and the second one being based on machine-learning based tools, specifically supervised learning. This study aims to find alternative means of studying causal implications of the management type on the economic activity within a farm, based on digital-based tools. The obtained results for the mentioned research showed that the methods based on supervised learning can be an important tool of analysis, being complementary with the traditional statistical methods regarding the analysis of the microeconomic agricultural environment and performance, providing supplementary key data regarding the economic indicators. [ABSTRACT FROM AUTHOR]

The paper analyzed the EU agri-food trade based on Eurostat data in the period 2013-2022 in order establish in what measure its commerce is efficient in terms of total trade, export, import, coverage ratio, trade-to GDP, export ratio, net export, share of groups of products in export and import value, growth rate and regression equations. The results highlighted an increase in agricultural output value by 33.77% which enhanced export. The total agri-food trade increased by +61.3% in the analyzed interval, accounting for Euro 424.6 Billion in 2022. Export value reached Euro 229.1 Billion in 2022, being by 58% higher, while import value raised by 65.53%, attaining Euro 195.5 Billion. Net exports were positive and varied between Euro 25.6 Billion in 2015 and Euro 46.9 Billion, the peak attained in 2021. Also, the coverage ratio was over 100% in the whole interval. The exported amounts were higher than the imported ones till 2016, but then imports exceeded exports, except the year 2021. The average export price was superior to the average import price every year. In the analyzed interval, the average export price increased by 37.13%, while import price by 25.71%. Export ratio was over 100 ranging between 119 in 2015, 131 in 2020 and 117 in 2022. The variations in export and import quantities and values produced changes in the share of the groups of products reflecting that in 2022, the hierarchy for export was: Foodstuffs, Animal products, Vegetal products, Fats and Oils, and for import: Vegetal products, Food stuffs, Animal products and Fats and oils. A positive trade balance and coverage ratio over 100 were found in case of Animal products and Food stuffs, and a negative trade balance and a coverage ratio below 100 was registered for Vegetal products and Fats and oils. Agrifood export accounted for 42.9% in agricultural output value in 2022, but the peak was 44.6% in 2018. The regression equation Y = 0.5259 X - 46.0376 shows that an increase by Euro 1 Billion in agricultural output value could raise export value by Euro 0.52 Billion. This research work highlighted the high efficiency in the agri-food trade of the EU in the period 2013-2022. To preserve its position of world leader in agri-food trade, the EU has to continue its CAP reforms oriented to a high performance from an economic, social, environment and food security point of view. [ABSTRACT FROM AUTHOR]

This paper analyses the direction and intensity of the impact of economic trends on the profitability of banks in Serbia and Croatia in the period between the years 2006 and 2021. This paper aims to determine which indicators of economic trends have the most substantial impact on the profitability of banks in the selected countries. As key indicators of economic trends, GDP per capita, the GDP growth rate, inflation rate, real interest rate, broad money growth, general government final consumption expenditure, current account balance, gross savings, trade, and unemployment are selected as independent variables. At the same time, bank profitability was measured with bank return on equity, in percentages (ROE), and bank return on assets, in percentages (ROA) – two indicators which represent the dependent variables selected for this research. Descriptive analysis, mean difference, correlation, and univariate and multivariate regression were used in the research. Research results show that changes in real interest rates and unemployment have a significant impact on the profitability of banks in both of the selected countries, while changes in GDP per capita growth have a statistically significant effect only in Serbia, and general government final consumption expenditure has a statistically significant impact only in Croatia. The influence of other indicators of economic trends is not statistically significant. [ABSTRACT FROM AUTHOR]

China's economy has shifted from the stage of high-speed growth to the stage of high-quality development. This paper selects panel data of 30 provinces, municipalities directly under the Central Government and autonomous regions (except Tibet) in mainland China with the time dimension of 2006–2016, selects indicators from five dimensions of innovation, coordination, greenness, openness and sharing, uses principal component analysis to construct a system of indicators of high-quality economic development, and uses the spatial Durbin model to empirically the impact of government investment behavior in the three industries on the regional economic high-quality development was studied. The results show that: first, there is a significant positive spatial correlation between China's economic quality development. Second, government investment in different industries has different effects on the quality development of the economy. Investment in the tertiary industry can boost employment, raise income level, promote economic quality development, and enhance sharing, coordination and innovation; investment in the secondary industry can enhance innovation, but because of the "crowding-out effect", it will reduce openness and sharing, and is not conducive to promoting economic quality development; investment in the primary industry can Investment in the primary industry can significantly improve coordination, but it will reduce innovation, greenness, openness and sharing, which will also have a negative impact on the overall high-quality economic development. Third, there is a significant spatial spillover effect of government investment behavior on regional economic quality development, and the economic quality development of this region will have an impact on neighboring regions. Finally, based on the research results, this paper puts forward countermeasure suggestions for promoting high-quality economic development. [ABSTRACT FROM AUTHOR]

This paper studies the joint dynamics of foreign direct investments (FDI) and output growth in European regions by using spatially augmented systems of equations modeling framework that incorporates third‐region and spillover effects. The joint framework is used to study the dynamic impacts of regional human capital endowments, which demonstrates the importance of explicitly accounting for an endogenous relationship. The relationship is highlighted in a stylized projection exercise, where the long‐run impacts are pronounced in Eastern Europe and capital cities. Overall, ignoring the relationship of regional economic performance and FDI distorts the implied transmission mechanism, which is of utmost importance for policy makers. [ABSTRACT FROM AUTHOR]

Many studies have shown that scaling laws widely exist in various complex systems, such as living organisms, cities, and online communities. In this research, we found that scaling laws also hold for companies. The macroscopic variables of companies, such as incomes, expenses, or total liability, all have power-law relationships with respect to the sizes of companies, which can be measured by sales, total assets, or the total number of employees. What is more, we also found the power law exponents always deviate from 1. That means large companies naturally have certain advantages, but the widely used financial indicators based on total volume or ratio may not reflect the company's status well because they are also size-dependent. To tackle this problem, this paper proposes a new set of evaluation indices based on the deviations of the macroscopic variables from the scaling law to eliminate the size-dependent effect. We found that the indicators based on deviations can give more reasonable evaluations for companies and can outperform other conventional indicators to predict the financial distress of companies. [ABSTRACT FROM AUTHOR]

Renewable energy consumption has gained growing importance in the world energy consumption portfolio over recent years. One of the reasons is the increasingly negative development of climate change. The research carried out in this paper aims to discern whether the examined economic indicator (GDP per capita) and the environmental indicator (CO2 emissions per capita) affect the renewable energy consumption in the region of the Visegrad Group (V4 - Czech Republic, Hungary, Poland, and Slovak Republic) countries, and to draw implications for public administration in the given issue. The fixed effects panel regression model was used to verify the mentioned relationships between variables from 1990-2020. The results show that the level of the share of renewable energy consumption on the total energy consumption in the region of the V4 countries can be affected by the GDP per capita (positive relationship validated) and the CO2 emissions per capita (negative relationship validated). These results are mostly in line with the findings of other researchers conducted on different samples of countries, although some differences can be noted, especially regarding the direction of the relationship. The implications of the research results are presented on three levels: practical implications for the business sector, emphasis placed on political implications for public administration, and theoretical implications that lay the foundation for further research. The main limitation of the research results comes from the sample used in V4 countries and, thus, from the limited possibilities of generalizing the results. The direction of further research in the addressed issue will include a larger number of countries in the research and the use of various quantitative and qualitative research methods. [ABSTRACT FROM AUTHOR]

The adoption of e-mobility in the countries of the European Union shows significant differences in terms of dynamics of electric car sales and in terms of differences in the share of electric cars in the total fleet of passenger cars in individual Member states. Despite the common European policy of transition to less emission-intensive car drives, the economic performance of countries, as well as other determinants, turn out to be the key drivers of differences in the sales and shares of electric cars on the car fleet within individual countries. In light of these findings, the paper contributes to the existing discussion and knowledge with additional recent findings and how intensive main consensual factors cause differences in the recent electric cars market shares in the EU countries. [ABSTRACT FROM AUTHOR]

Limited skilled labor has been one of the greatest challenges facing the construction industry. The COVID-19 pandemic has further exaggerated the already strained construction labor market, leading to an additional negative impact. One of the major contributors to skilled labor shortages in construction is the issue of labor retention. Overall, this is a complex and dynamic situation that requires effective and efficient simulation-based techniques to capture the interdependent relationships that affect the performance of the construction labor market. This paper fills this knowledge gap. To this end, the authors used a multistep research methodology that involved (1) identifying factors that affect skilled labor shortages; (2) developing a one-module system dynamics model that consists of three interconnected systems (namely, construction labor market system, industry characteristics system, and economic conditions system); (3) initializing and calibrating the model to simulate the construction labor market; (4) validating the model through structural, behavioral, and calibration tests; and (5) conducting sensitivity analysis to simulate different parameters and examine their impact on skilled labor shortage. Among other findings, results indicated that all scenarios were successful in improving the conditions of the skilled labor market by increasing the workforce size and labor retention rate. Further, the model demonstrated that economic indicators have a more impactful influence on labor retention patterns compared with industry characteristics. The developed model offers industry practitioners, policymakers, business analysts, and other associated stakeholders a useful tool to test various scenarios including national-level economic policies and labor retention regulations that affect the construction skilled labor market. Consequently, this allows users to analyze the impact of variables such as fiscal policies, economic support plans, and construction spending strategies. [ABSTRACT FROM AUTHOR]

In this paper, the performance of an innovative micro-combined cooling, heating, and power (CCHP) system, based on an internal combustion engine fueled with syngas from woody biomass, is analyzed. In particular, a numerical model, which considers a direct coupling between the internal combustion engine and the gasifier as a novel aspect, was developed, validated and applied to three different case studies to perform an energetic, economic and environmental analysis. For each considered case, the CCHP system was equipped with a reversible electric air–water pump and a back-up boiler. The energy analysis shows that the user characterized by a high uniformity of the thermal load exploits the CCHP system in the optimal way as it allows for the highest thermal self-consumption rate. On the contrary, for the cases in which the thermal request is not uniform, a high electric surplus is recorded. In this case, the adoption of the heat pump allows to compensate for this disadvantage by recovering the electric surplus, thus achieving a thermal integration and CO2 emissions reduction of about 15.8% with respect to the case in which no heat pump is used. Overall, the results demonstrate the affordability of the biomass-based CCHP system, which is of increasing importance in this period of contingent international political crisis. [ABSTRACT FROM AUTHOR]

The choice of agricultural crops for sowing and the planning of yields and economic results is realized in conditions of uncertainty and risk. The factors that contribute most to the uncertainty in achieving yields in agricultural production can be quantified using the method of fuzzyfication. The method based on the unique assessment of criteria represents an innovative approach to solving uncertainty in agricultural production. A key feature of this method is its ability to treat criteria as fuzzy scores and to allow their aggregation to make a final yield planning decision. In the paper, 15 main criteria were chosen that influence the planning of yield when sowing sage, nettle and rye. Based on economic indicators, the economic analysis does not numerically describe the impact of uncertainty, which in agricultural production can have an inestimable importance on realized yields and incomes. The method used is a suitable tool for analysis and planning in agriculture, it enables effective treatment of uncertainty and competing criteria, providing farmers with a reliable basis for making decisions about yield planning. [ABSTRACT FROM AUTHOR]

Intangible assets are gaining more relevance within companies in recent decades, as they have an increasing share in the composition of corporate assets. The intangible assets have become new drivers of the international economic environment. In this sense, the objective of this paper is to investigate the relationship between economic performance and the degree of intangibility in companies in Brazil and the United States. In addition, it is proposed to verify whether there are differences between the impact of intangibility on business performance between these two countries. For this purpose, panel data models were estimated between 2012 and 2017 for a sample of companies from Brazil and the United States. The results reveal that the positive relationship between degree of intangibility and performance is more evident to US companies. In the case of Brazil, this relationship is still tenuous. [ABSTRACT FROM AUTHOR]

Spindle nose stiffness is a leading technical indicator of machine tool spindle. However, the stiffness of machine tool spindle supported by fluid bearings has not been studied thoroughly, by far; there is not an ideal approach to obtain the spindle nose stiffness due to the nonlinear fluid bearings. This paper proposes a new methodology for the spindle nose stiffness including definition of the spindle nose stiffness with the fluid bearings, experimental and theoretical approach to obtain the spindle nose stiffness. A motorized spindle with hydrodynamic water-lubricated spiral groove bearings developed in our laboratory is selected as an object; a theoretical and experimental investigation on the spindle nose stiffness is conducted. The result shows that the proposed methodology is applicable for obtaining the spindle nose stiffness with the fluid bearings; the experimental device has the advantages of simple structure, low cost, and convenient operation. Meanwhile, the spindle nose stiffness can be calculated by simultaneously solving the dynamic model of rotor-bearing system. We expect an improvement for the experimental device by introducing another load device to apply a perturbed load with an any angle to the external load on the spindle nose. [ABSTRACT FROM AUTHOR]

This paper analyzes the stochastic properties of consumer sentiment to understand how they affected the luxury sector in the United States before and after COVID-19. The results were derived using fractional integration methodologies and suggest that, before the pandemic episode, both variables were expected to be mean reverting and the shocks were transitory, having similar behavior. However, after the appearance of COVID-19, results suggest that consumer sentiment recovered before the luxury sector. Results from the use of cointegration methodologies show that the effects of COVID-19 disappeared in the short-run. Finally, the sentiment of consumers acts as a leading indicator of the behavior of the luxury sector according to wavelet analysis. Thus, an increase in consumer sentiment implies an increase of 3.6% in the luxury sector. [ABSTRACT FROM AUTHOR]