Productivity Research Articles

Heterogeneous influences of specialization and diversification on regional R&D performance: a China, Europe, and US comparison

Abstract We study the impact of industrial specialization and diversification on regional R&D performance. We respond to a need to consider specialization and diversification as being complementary and to cover a broad geographical scope. Based on Malmquist-based data envelopment analysis, we disclose disparity in R&D productivity and underlying efficiency and technical change in regions in China, Europe, and in the USA in the period 2015–19. For provinces in China, industrial diversification affects regional R&D productivity growth and efficiency enhancement in a U-shape mode. For European countries, specialization has a U-shaped influence on R&D productivity change, and diversification has an inverted U-shaped influence on productivity and efficiency change. We find no significant influence of specialization and diversification on the improvement of R&D performance at the level of states in the USA. Our findings point to place-based specificities and complementarity between specialization and diversification and come with policy recommendations for enhancing regional R&D performance.

Individual happiness and well-being as a strategy to increase productivity

This research aims to examine the role of happiness and well-being as key factors in enhancing individual productivity. With the growing body of research on mental health and well-being, a new understanding has emerged regarding the strong connection between emotional well-being and productive performance. Through a literature review, this study identifies and analyzes various empirical studies that explore the impact of happiness and well-being on productivity in different contexts, both in the workplace and in everyday life. The review process employed a systematic literature review method, with inclusion criteria encompassing studies published within the last four years and written in English or Indonesian. The findings indicate that happiness and well-being not only contribute to improved performance but also play a pivotal role in fostering an environment that supports sustainable productivity growth.

Theoretical Thinking on the Development of New Quality Productive Forces According to Local Conditions in Heilongjiang Province

The new quality productive forces reflects the systematic remodeling and revolutionary transition of the old productive forces, which is the quality of productivity in line with the requirements of high-quality development. The formation of new quality productive forces can effectively energize the revitalization and development of Heilongjiang Province. From the perspective of the revitalization of the old industrial base in Northeast China, opportunities, advantages and challenges coexist in the development of new quality productive forces in Heilongjiang Province. Based on the current situation, the practical path for the development of new quality productive forces according to local conditions in Heilongjiang Province is proposed: Cultivate innovative thinking leading the development of new quality productivity, form the industrial base for the development and growth of new quality productivity, shape the innovation economic system for the development of new quality productivity, and build innovation clusters of new quality productivity.

Factors affecting the quality of work life for industrial labour force: empirical evidence from a developing country

The success of any organization requires a skilled, competent, and satisfied workforce. If the workforce can be provided with the necessary components to ensure a high quality of working life, they will become permanent assets. Various factors undoubtedly affect the quality of workers' work lives. This study aims to investigate the drivers of the quality of work life in industrial labour force in a developing country, Bangladesh. It enumerated the elements that have an impact on industrial labour force’s quality of work life (QWL). A structured questionnaire was administered to 420 Bangladeshi workers across diverse industries, yielding a commendable response rate of 93.33%. The collected data underwent analysis employing the partial least squares structural equation modeling (PLS-SEM) technique. Representative industries and respondents were chosen by random selection. The results revealed that work environment, organizational culture and climate, relationships and cooperation, compensation and rewards, adequacy of resources, autonomy of work, job satisfaction, and security are directly related to the QWL. Training and development, and facilities do not significantly affect QWL. The research results can be used to improve the quality of work life for those working in the industrial sector. An industry may accomplish long-term and short-term goals by maintaining a pleasant workforce. The study's findings will provide policymakers and regulatory authorities of Bangladesh's industrial sector with strategic references and strategies to boost industrial productivity and economic growth for sustainable development by ensuring industrial employees' quality of work life that can serve as a template for Bangladesh.

Static and Dynamic Modeling of Non-Performing Loan Determinants in the Eurozone

The issue of non-performing loans (NPLs) in a bank’s portfolio is important for a bank’s stability and sustainability. Their increased presence indicates a potential worsening of the economy and a lower quality of the bank’s assets. We estimated determinants of non-performing loans in the Eurozone for quarterly data 2015–2020. The results confirmed spatial spillover effects within Eurozone countries, which means that when a shock happens in one country in the Eurozone, it will also affect the other economies of the Eurozone area. Based on the Hausman test, a fixed-effects model was chosen as appropriate and showed that bank-specific and macroeconomic determinants significantly affect NPLs in these economies. In relation to previous studies that dealt with this issue, a co-integration analysis was introduced. A significant impact of return on assets, return on equity, and the loan-to-deposit ratio, as well as the gross domestic product, inflation, and exchange rate on NPLs in the short run and long run, was confirmed using a Pooled Mean Group (PMG) estimator. Bank management should customize credit policy based on both internal and external conditions to improve their performance, focusing on enhancing profitability and maintaining a lower loan-to-deposit ratio to reduce NPLs. The research suggests that a higher gross domestic product (GDP) growth rate is associated with fewer NPLs, while inflation uncertainty and a volatile exchange rate can increase NPLs, highlighting the importance of adjusting strategies to the macroeconomic landscape.

Investigating Transfer Learning based CNN for Multi-Crop Disease Recognition in Horticulture Crops using Wireless Multimedia Sensor Network

Introduction: Achieving sustainable growth in agricultural productivity is crucial for addressing various challenges confronting food systems globally. One of the key aspects is effectively identifying and addressing diseases that can adversely affect crop quality and yield. Method: This research study proposes the use of Wireless Multimedia Sensor Network (WMSN) in conjunction with deep transfer learning model for disease detection in horticulture crops. The proposed system utilizes the image data of horticulture crops obtained using WMSN for performing a comparative assessment of several pre-trained deep learning models, encompassing VGG, ResNet, MobileNet, Inception, Xception, DenseNet, and EfficientNet, to ascertain their effectiveness in identifying diseases across a range of horticultural plants. The models undergo fine-tuning using transfer learning technique and are assessed on different measures, such as accuracy, precision, recall, F1 score, and the number of epochs needed for convergence using the image data obtained from WMSN. Results: Among the compared models, EfficientNetB3 appears as the best performing model, surpassing others in all evaluation metrics while also exhibiting low parameters and a compact size. Notably, EfficientNetB3 achieves a testing accuracy of 93.69% and a training accuracy of 98.85% after only 21 epochs of training. In contrast, DenseNet201, DenseNet169, and EfficientNetB0 demonstrate performance close to the best-performing models, but they have higher parameters or sizes. On the contrary, ResNet50, InceptionV3, and Xception exhibit poorer performance, presumably due to their substantial size in relation to the dataset. Conclusion: This analysis provides valuable insights for optimizing the top-performing models for disease classification across various plant species. Moreover, the fine-tuned EfficientNetB3 model shows potential for integration with mobile devices, facilitating real-time disease classification.

Unveiling the role of managerial ability in driving productivity, efficiency, and technological change: Insights from the Asian banking sector

AbstractIn today's competitive banking industry, the role of capable managers is crucial for the success of banks in facing various challenges and threats. The importance of measuring managerial ability has gained significant attention among researchers. In this study, we focus on assessing the managerial ability of 166 Asian banks from six different countries over the period of 2014–2020. From a rational point of view, productivity growth in banks can be directly related to effective management, as capable managers enhance the bank's productivity. Therefore, our study investigates the relationship between productivity change in banks and managerial ability. Furthermore, we examine the impact of managerial ability on the components of productivity change, specifically efficiency change and technological change. The findings of our study indicate a positive association between managerial ability and both productivity and efficiency change (EC). However, no significant association is observed between managerial ability and technological change.

The intermediate role of farmland transfer in the impact of digital financial inclusion on agricultural total factor productivity in China

IntroductionEnhancing agricultural productivity and promoting sustainable development in China are critical priorities, given their significant contribution to food security and rural development. However, achieving consistent agricultural productivity growth across regions and sectors has been challenging, leading to inefficiencies and environmental pressures. To address this, the potential of digital inclusive finance (DIF) as a catalyst for progress has been explored.MethodsThis study investigates the impact of DIF on agricultural total factor productivity (ATFP) through farmland transfer, with implications for rural revitalization and high-quality agricultural development. Using the HMB index method, we calculate and decompose China’s inter-provincial ATFP from 2011 to 2020. Employing the dynamic panel fixed effect model and SYS-GMM method, we empirically test the influence of DIF on agricultural productivity in relation to farmland transfer.Results and discussionOur findings reveal a slow upward trend in China’s ATFP, driven primarily by scale efficiency. Notably, a 1% increase in the general index of DIF correlates with a 0.136% increase in ATFP. We analyze the sub-classification indexes of digital inclusive finance, namely coverage breadth, depth of use, and digitalization degree. Their contributions to agricultural productivity growth are significant, with coverage breadth having the greatest impact, followed by depth of use and digitalization degree. Farmland transfer acts as a crucial intermediary, enhancing agricultural allocation efficiency and driving the relationship between digital finance and total factor productivity growth. Interestingly, the western region exhibits the highest growth rates, followed by the eastern region, while the central region shows no significant effects.ConclusionTo comprehensively enhance ATFP, aligning supply and demand for digital financial services, leveraging service depth, and guiding farmland transfer according to local conditions are essential. These findings offer valuable insights into effective strategies for maximizing the potential of DIF, promoting rural development, and achieving sustainable agricultural growth.

Comrades' Courts in the Soviet Period of Russian Statehood as a Form of Non-Professional Justice

The formation and development of comrades’ justice in the Soviet period of Russian statehood is associated with the implementation of the unified national concept of the court, conditioned not so much by professional justice as by the mass participation of non-professional judges from the people in court. The jurisdiction of cases heard in public courts was regulated by the relevant provisions and criminal codes, providing that these courts considered minor crimes, both by virtue of a direct indication in the law, and by way of delegation of the function of justice by the courts or the prosecutor’s office in each specific case. The activities of the comrades’ courts are divided into three periods. The first period — from 1919 to 1922 — is characterized by the disciplinary orientation of the comrades’ courts authorized to consider all violations of labor legislation. The second period — from 1928 to the beginning of the Great Patriotic War — is characterized by a variety of comrades’ and public courts that covered various spheres of economic, social and political activities, from Soviet enterprises and institutions to collective farms. Its main purpose was to free public courts from a mass of minor offenses and property disputes, as well as ensuring productivity growth and combating disruptors of production in enterprises and institutions. The third period — from the late 1950s to 1991 — set the goal of strengthening socialist democracy by involving a wide range of workers in the management of public affairs, including through comradely justice, which defined comrades’ courts as quasi-judicial bodies of public and state power, intrinsically inscribed in the concept of a socialist national state.

Photocatalysis of Adsorbed Catechol on Degussa P25 TiO2 at the Air-Solid Interface.

Semiconductor photocatalysis with commercial TiO2 (Degussa P25) has shown significant potential in water treatment of organic pollutants. However, the photoinduced reactions of adsorbed catechol, a phenolic air pollutant from biomass burning and combustion emissions, at the air-solid interface of TiO2 remain unexplored. Herein we examine the photocatalytic decay of catechol in the presence of water vapor, which acts as an electron acceptor. Experiments under variable cut-off wavelengths of irradiation (λcut-off ≥ 320, 400, and 515 nm) distinguish the mechanistic contribution of a ligand-to-metal charge-transfer (LMCT) complex of surface chemisorbed catechol on TiO2. The LMCT complex injects electrons into the conduction band of TiO2 from the highest occupied molecular orbital of catechol by visible light (≥2.11 eV) excitation. The deconvolution of diffuse reflectance UV-visible spectral bands from LMCT complexes of TiO2 with catechol, o-semiquinone radical, and quinone and the quantification of the evolving gaseous products follow a consecutive kinetic model. CO2(g) and CO(g) final oxidation products are monitored by gas chromatography and Fourier-transform infrared spectroscopy. The apparent quantum efficiency at variable λcut-off are determined for reactant loss (Φ- TiO2/catechol = 0.79 ± 0.19) and product growth ΦCO2 = 0.76 ± 0.08). Spectroscopic and electrochemical measurements reveal the energy band diagram for the LMCT of TiO2/catechol. Two photocatalytic mechanisms are analyzed based on chemical transformations and environmental relevance.

Political stability in authoritarian regimes: the case of Central Asia

ABSTRACT Existing research indicates that political stability is a prerequisite for good governance and economic development in Central Asia. All five countries in the region are authoritarian regimes but it is unclear which factors impact on political stability. Using data for the period 2002–2022, this paper examines the variables which make a significant contribution to political stability and finds that the rule of law, personalist rule, a free media, freedom of assembly, political polarization and gross domestic product (GDP) growth, respectively have a positive effect on political stability while government accountability, exclusions by social group and civil society participation have a negative effect. Some of the findings are at odds with other studies on autocratic regimes, illustrating the importance of geo-political context.

Interrelation of protein metabolism and autonomic nervous system in laying hens

The study of factors influencing the processes of protein metabolism in the poultry body will help to better balance the diet, which will help to more effectively stimulate the growth of animal productivity. The aim of the work was to investigate the role of the autonomic nervous system in protein metabolism and to take into account the individual characteristics of the poultry organism, characterized by different tone of the autonomic nervous system. The formation of experimental groups of animals was carried out by electrocardiographic examination using the Baevsky method, on the basis of which three experimental groups of animals were formed: normotonics, vagotonics, and sympathotonics. The blood serum was studied using a LabLine-010 spectrophotometer (Austria) and test systems from Laboratory Granum LLC, Kharkiv. Kharkiv. According to the results of the biochemical study, it was found that the content of total protein, which was compared with the experimental group of normotonics (46.10±1.35 g/l) with a balanced sympathovagal balance, was 14.8 % lower than that of the experimental group of sympathotonics (54.10±2.60 g/l) (P<0.01) and 18.1 % lower than that of the experimental group of vagotonics (56.30±1.90 g/l) (P<0.01). The albumin content, which was compared with the experimental group of normotonics (4.56±0.55 g/l) with a balanced sympathovagal balance, was 40.55 % lower than that of the experimental group of sympathotonics (6.96±0.49 g/l) (P<0.001) and 1.5 times lower than that of the experimental group of vagotonics (7.67±0.38 g/l) (P<0.01). The creatinine content compared to the normotonic group (47.12±0.77) with a balanced sympathovagal balance was lower than that of the experimental group by 6.77 % compared to the experimental group of vagotonic poultry (7.67±0.38 g/l) (P<0.001). Taking into account the individual characteristics of the poultry organism and establishing the tone of the autonomic nervous system, it was determined that the autonomic nervous system has an effect on protein metabolism in poultry. The prospect of further research is to study the use of nanoaquahelate preparations to improve productivity and metabolic processes, taking into account the tone of the autonomic nervous system.

Unveiling the Welfare Puzzle: Exploring Fertilizer Subsidy Effects on Farmer's Earnings in Indonesia

This study investigates the unresolved issue of how fertilizer subsidies affect paddy production and farmer income, a critical aspect of Indonesia's agricultural policy that has not been fully understood. By analyzing panel data from 33 provinces between 2019 and 2022 using the Generalized Least Squares (GLS) method, the research explores both income dynamics and productivity. Results reveal that NPK and SP36 fertilizers boost paddy yields by 0.198% and 0.155%, respectively, while UREA and ZA have no significant impact on production. Additionally, rising wages reduce production by 1.343% but increase farmer income by 0.332%. These findings highlight the complexity of balancing productivity with farmer welfare, suggesting that while fertilizer subsidies can enhance yields, they are not a universal solution. Policymakers must consider multifaceted approaches that address both productivity and sustainable income growth to ensure long-term welfare improvements for Indonesian farmers.

Digitalization of Mining Enterprise: A Key Factor in Ensuring Economic Security

The level of competitiveness of mining companies is primarily determined by productivity and operational excellence. Digitalization is becoming a key factor that enables companies in this industry to remain competitive in the future. In the mining industry, the transition to new and better ways of working has been slow due to the scale and complexity of production processes, as well as the significant costs of modernization. As a result, some enterprises are not actively implementing digital technologies. However, leading global and Kyrgyz mining companies are actively investing in the development of modern technologies in the field of energy and automation in order to increase production volumes, improve environmental efficiency, reduce the use of manual labor, costs and energy consumption. It is obvious that digital technologies open new opportunities for a significant increase in labor productivity and profit growth. The article discusses the main directions of digital transformation of mining enterprises, reveals the key advantages and potential threats. The author analyses both foreign and Kyrgyz examples of effective digitalization in this industry.

The Analysis of Factors that Influence Stunting

Stunting in children is a national problem caused by many factors that harm human resources in the future, including an impact on decreasing intelligence, vulnerability to disease, hampering economic growth, work productivity, exacerbating inequality, and height growth is shorter than age in general. Stunting in children under five is a consequence of several factors that are often associated with poverty, including nutrition, health, sanitation, and the environment There are five main factors that cause stunting, namely poverty, social and cultural, increased exposure to infectious diseases, food insecurity and community access to health service. The purpose of this literature review was to analyze the factors that influence stunting. The article was obtained from a SINTA accredited journal published in the 2013-2023 period with the same title, as well as the same research design. The selected articles were then tested for plagiarism, and nine articles with the smallest plagiarism level were selected. Analysis PICO (Population, Intervention, Comparison, Outcome) is carried out on each article, followed by making conclusions. The results of the analysis determined that factors that influence stunting include social and cultural, increased exposure to infectious diseases, food insecurity and community access to health services alone or together. The author hopes that this research will further greatly help how to do health promotion, case finding and prevention, and, many sectors must be involved and work together for the problem of stunting.

Macroeconomic Determinants of Foreign Direct Investment Inflow in Laos

This study aims to study macroeconomic determinants of foreign direct investment inflow in Lao PDR, which includes macroeconomic variables such as gross domestic product growth rate (GDPGRO), government investment spending (GI), exchange rate (EXR), inflation rate (IFR), interest rate (IR), openness trade (OPTR) and money supply (MS) from 2001-2022. This results found that: The foreign direct investment inflow has 12,298.57 million US dollars on an average per year is equal to 559.03 million US dollars and has an average growth rate of 4.73% per year, for the public expenditure used to investment is increasing every year with an average growth rate of 10.96% per year. The exchange rate of kip per US dollar has an increasing trend but overall there is a growth rate equal to 1 digit only in 2022 there is a growth rate equal to 2 digits which is equal to 45.94%. For the inflation, the growth rate is 6.33% per year, which is the year with the lowest inflation rate is 2017 which is equal to 0.83% and the year with the highest inflation rate is 2022 which is equal to 22.96%, The decreasing trend in which the year with the highest interest rate on US currency loans is 2002 which is equal to 13.5% and the year with the lowest interest rate on US currency loans is 2011 which is equal to 8.15%, the open trade has an increasing trend. The year with the highest increase in 2021 is equal to 77.91% of GDP and the money supply is increasing every year. For the analysis of macroeconomic factors to foreign direct investment, it was found that the economic growth rate of gross domestic product (GDPGRO), public investment expenditure, the exchange rate of kip per US dollar and the money supply have a positive coefficient and reject the null hypothesis with a statistical significance level of 0.01 and 0.05 indicates that it is a doubtful factor for foreign direct investment to increase. Meanwhile, the inflation rate has a negative coefficient and rejects the null hypothesis at a statistical significance level of 0.05, which is a factor that reduces foreign direct investment transfers. For the interest rate in dollars and the open trade, there are accepted null hypothesis, it shows that there is no effect on the transfer of foreign direct investment.

Digitalization and Agricultural Green Total Factor Productivity: Evidence from China

Based on panel data of 31 provinces (autonomous regions and municipalities) in China from 2011 to 2022, this paper empirically examines the impact of digitalization on the inputs and outputs of the agricultural production process, and thereby derives the effects and mechanisms by which digitalization empowers the growth of agricultural green total factor productivity. The study finds that agricultural and rural areas’ digitalization significantly improves agricultural green total factor productivity, and this promotion mainly comes from the improvement of technical efficiency. Further analysis shows that digitalization mainly reduces land input and labor input, increases expected output, and reduces undesired output during the agricultural production process to achieve an improvement in agricultural green total factor productivity, indicating that digitalization has altered the allocation of agricultural factors. Heterogeneity analysis finds that the effect of digitalization on the growth of agricultural green total factor productivity is more pronounced in the eastern regions, southern regions, and areas with higher levels of agricultural digitalization, indicating that the development of digitalization exacerbates the gap in agricultural green total factor productivity among regions.

READJUSTMENTS OF PUBLIC SERVANTS AND THE IMPACT ON THE CONCORD ECONOMY

The economic analysis of a location is often based on the growth of the Gross Domestic Product (GDP). However, GDP alone does not provide definitive conclusions about the population’s quality of life. For a more comprehensive assessment, it is necessary to consider multiple indicators that reveal economic and social dynamics. This work investigates the relationship between the adjustment of public servants’ remuneration and economic performance in Concórdia, Santa Catarina, from 2014 to 2021. The analysis includes inflation data, comparison between real growth in remuneration and agriculture, and other indicators. We hope to identify correlations and impacts on quality of life, contributing to more effective and equitable public policies.

The growth of the county economy in China

ABSTRACT This article evaluates the gross domestic product (GDP) growth of 2,089 counties in 31 provinces in China from three aspects over the period of 2015–2019: all of 2,089 counties at the national level, all counties within each province, and the county economy of 31 provinces. It has three key findings on the low-growth performance of the county economy: (1) There were 27 national-level low-growth counties, 24 of which were in three northeastern provinces (i.e. Liaoning, Jilin, and Heilongjiang) that are major grain producing provinces in China. (2) There were five provincial-level low-growth counties in four provinces. (3) Three provinces (i.e. Liaoning, Jilin, and Tianjin) had low performances in the growth of the county economy. This article sheds light on the regional patterns of the low-growth county economy in China. Policy recommendations for improving the development of the county economy in China are also discussed.

Innovation and Demand as Drivers of Labour Productivity: An Integrated Analysis for OECD Countries

ABSTRACT The article seeks to empirically reconcile two strands of research on the determinants of labour productivity growth: on one hand, the Kaldorian literature emphasises the role of autonomous demand; on the other hand, the Schumpeterian literature underscores the role of innovative investments. Specifically, we test two hypotheses. Firstly, we investigate whether demand shocks, private research intensity, and public R&D expenditure influence labour productivity when these variables are considered simultaneously. Secondly, we examine whether private research intensity is affected by demand shocks and public investments in innovation. We make use of a panel of 12 OECD countries spanning the period from 1986 to 2017. We combine the Local Projection approach with structural shocks estimated through Structural Vector Autoregressive modelling. Findings show a positive impact of government R&D investment, demand shocks, and private research intensity on labour productivity. Additionally, when examining the effects of demand shocks and innovative activities by the public sector on research intensity, the results affirm a positive impact of these variables, thus supporting the presence of the Schmooklerian demand-pull hypothesis. These results remain robust across various model specifications and different measures of labour productivity.