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Vulnerability to modern slavery in Indonesia, particularly driven by poverty and discrimination against minority groups, has become a primary concern in the context of information transparency. This study aims to investigate the factors that can support the reporting quality of modern slavery in Indonesia, namely the industry sector, profitability, social responsibility commitment, and gender diversity as the moderating variable. The research utilized a sample of 225 companies listed on the Indonesia stock exchange (IDX) from 2020 to 2022. Data were collected from financial reports and sustainability reports as well as the Refinitiv Eikon database. Panel data regression analysis was conducted to analyze the determinants of the disclosure quality. The research findings indicate that high‐risk industry sectors tend to disclose less information regarding modern slavery, with this outcome having a partially negative impact. However, profitability is not associated with the quality of voluntary modern slavery disclosure. In contrast, corporate responsibility commitment is positively associated. Additionally, this study reveals that gender diversity does not moderate the association between the industry sector, profitability, and corporate responsibility commitment with the disclosure quality of modern slavery. This research contributes to the growing literature on the accountability of modern slavery in an emerging country context through institutional theory and gender socialization theory lenses by identifying the firm‐level factors to enhance corporate disclosure in this area. This study also contributes to corporate understanding of modern slavery issues within supply chains. With growing attention to this problem, the awareness of labor exploitation within corporate supply chains is also increasing. The findings of this research can assist companies in recognizing the importance of transparency and voluntary disclosure regarding modern slavery in their supply chains. [ABSTRACT FROM AUTHOR]

Economic effects on environmental concerns assess macroeconomic pressures or microeconomic status differences but overlook environmental and labor scholarly attention to industry contexts. I test whether employed industry, green jobs opportunities, and regulatory threats influence five environmental concern indexes using cross-sectional US General Social Surveys from 2000, 2010, and 2021 and federal administrative data. Findings indicate individuals employed in resource extraction, construction, and manufacturing express less environmental concerns than service sector individuals but vary across dimensions. Resource extraction individuals express less concern for environmental protections and pollution harms. Manufacturing, construction and utilities individuals are less willing to sacrifice for the environment. Green jobs sub-industry employment is positively associated with more willingness to sacrifice and empowerment to act for the environment. Surprisingly, employment in Environmental Protection Agency regulated sub-industries is positively associated with more willingness to sacrifice for the environment. The findings underscore future research on how industry-based economic contexts shape environmental concerns. [ABSTRACT FROM AUTHOR]

The exchange rate is one of the most important macroeconomic variables that affects different sectors of the economy from various aspects. Due to the considerable impact of industrial development on the country's economic development, this research attempts to evaluate the asymmetric effect of the exchange rate on the value added of the industrial sector for the period of 1380:1 - 1400:4, using the NARDL method. The results of the estimation show that the effect of the exchange rate on the value added of the industrial sector is asymmetric, such that an increase in the exchange rate affects the value added of the industrial sector differently from a decrease in the exchange rate. The effect of the exchange rate in the long term is such that the positive changes in the exchange rate strengthen the value added of the industrial sector, and the decrease in the exchange rate does not affect it. Therefore, the economic policymaker should abandon exchange rate suppression as an inflation control policy and allow the exchange rate to be determined based on market forces.

IntroductionPaid family leave (PFL) has the potential to reduce persistent health disparities. This study aims to characterize differences in access to paid leave by industry sector and occupational class.MethodsThe Bay Area Parental Leave Survey of Mothers included respondents 18 years of age or older who worked in the San Francisco Bay Area and gave birth from 2016 to 2017. Using linear probability models, we examined differences in five separate measures of PFL by industry sector and occupational class. We extended our regression analysis to simulate the full pay equivalent (FPE) weeks of leave that would have been taken under hypothetical scenarios of increased uptake and wage replacement rates.ResultsOur study included 806 women in private for-profit or non-profit jobs. In fully adjusted models, blue-collar workers were 10.9% less likely to take 12 weeks of paid parental leave versus white-collar workers (95% CI: -25.9, 4.1). Respondents were 19.2% less likely receive 100% of their regular pay if they worked in education and health services (-29.1, -9.3) and 17.0% less likely if they worked in leisure and hospitality (-29.5, -4.4) versus respondents in professional and financial services. Respondents in leisure and hospitality reported 1.6 fewer FPE weeks of leave versus respondents in professional and financial services (-2.73, -0.42) and blue-collar respondents reported an average of 1.5 fewer FPE weeks versus white-collar workers (-2.66, -0.42). In our simulation analysis, when we manipulated rates of uptake for paid leave, the disparities in FPE by industry sector and occupational class were eliminated.ConclusionWe observed substantial inequities in access to paid leave by industry sector and occupational class. These findings underscore the potential importance of universal PFL programs with universal benefits to reduce clear inequities that persist within the labor market today.

This study investigates how organisational and geographical factors affect the efficacy of business architecture in enterprises. Employing a quantitative research methodology, the research analyses data from a diverse range of organisations using ordinal logistic regression. The findings validate the hypothesis that factors like organisational alignment, industry sector, geographic region, organisational size, and adoption duration significantly influence business architecture's maturity and strategic impact. The study contributes to the understanding of business architecture's role in organisational strategy, highlighting the importance of contextual factors. It suggests that business architecture strategies should be tailored to specific organisational contexts, offering valuable insights for policy formulation and organisational strategy development. This research provides a foundation for future studies and practical applications in business architecture and enterprise transformation, emphasizing the need for a nuanced approach considering different organisational and regional characteristics. [ABSTRACT FROM AUTHOR]

The decarbonization of the industrial sector plays a crucial role in a successful energy transition. This transformation is very costly and complex, as many of the existing production processes and plants will have to be partially or completely replaced to reduce carbon dioxide (CO2) emissions. This raises questions about how significant reductions in CO2 emissions resulting from decarbonization will affect the use of resources to produce a certain product and the overall value of sustainability. This article considers the relationship between CO2 reduction and the impact on the resource efficiency of an industrial production process. For this purpose, a methodology was developed that holistically assesses the decarbonization pathway of an industrial sector. This holistic assessment takes into account the energy carriers, raw materials, and auxiliary and construction materials used for the operation and building of the significant plant components and summarizes them as a total use of resources. For this purpose, the use of resources is represented by the thermodynamic quantity exergy, which takes into account both the energy and material components of a production process. The energy and material streams in a production process are balanced by applying exergetic analysis. This methodology is used for current state-of-the-art and future decarbonized production processes in order to quantify the effects of the decarbonization process. By comparing the calculated resource efficiencies, the thermodynamic impact on the sustainability of decarbonization paths can be set in relation to the amount of CO2 saved. For validation, the developed methodology is applied to a conventional and a decarbonized ammonia production process. The conventional production route represents the production of ammonia by methane steam reforming, and the decarbonized production route is represented by synthesis gas production via water electrolysis and an air separation unit. The resource efficiency of the conventional ammonia production route, taking into account the energy sources, raw materials, construction materials, and auxiliary materials used, is 59%, producing a total of 1539 kg of CO2 emissions per ton of ammonia. The decarbonized process has a resource efficiency of 45%, while no CO2 emissions are produced in this manufacturing process. This means that the decarbonization of the production process reduces resource efficiency by 14%. In relation to the reduced amount of CO2, specific resource efficiency decreases by 9.09%/tCO2. The decline in resource efficiency is mainly due to the high level of heat and energy recovery in the conventional process and the very electricity-intensive hydrogen production in the decarbonized production process. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak and the implementation of peak and carbon neutral policies have severely impacted oil price volatility and the industrial sector. Exploring the impact mechanisms between oil prices and industries is particularly important for accurate forecasting of crude oil prices. As one of the world's largest commodity consumers, China's crude oil market is more representative and susceptible to external factors than that of developed countries. In this paper, we propose an analytical forecasting framework based on the causal effects between Shanghai crude oil prices and various industries in China to improve the forecasting accuracy of crude oil prices. Information geometric causal inference (IGCI) is applied to detect causal relationships between 31 different industries in China and Shanghai crude oil prices in the three time periods before, during and after COVID-19, and industries with strong causal information effects on crude oil prices in the long run are screened out as additional features. An oil price forecasting model based on Gray Wolf Optimization and Extreme Learning Machine (GWO-ELM) is proposed. Considering the small amount of data for Shanghai crude oil, this paper proposes a cross-learning data approach to solve the problem. Experimental results show that the GWO-ELM model outperforms RF, LSTM, GRU, and migration learning-based Tr-LSTM and Tr-Adaboost models in the task of Shanghai crude oil futures price prediction, and find that industry characteristics with long-term causal effects on oil prices can improve the model prediction accuracy. Our proposed analytical prediction can capture the oil price trend more accurately through the information of the industry and solve the problem of insufficient training data for the model. The application of this framework is expected to provide new methods and ideas for data mining of crude oil and other futures prices. [ABSTRACT FROM AUTHOR]

The purpose of the article is to identify the role of trends in cost systems such as activity-based costing systems) ABC (and target cost (TC) to improve competitive advantage for the Sudanese industrial sector. This can help accountants in accuracy when measuring and calculating production and goods. Also, they assist companies in determining the price considering the allowable costs. The practical value of this scientific research lies in three folds. First, the findings will contribute to shedding light on the experience of using some modern cost systems in Giad industrial group companies - in Sudan. Second, they inform officials about the evaluation of these systems and the extent of benefits from them in improving the competitive advantage. Third, the study fills in the gap lack of studies that deal with this topic in the Sudanese setting. The study’s findings indicate the existence of a role for ABC in overhead cost allocation, more accurate product cost, and cost control improvement. This leads to improving advantage competitive in Sudanese industrial companies. Also, it was discovered that the existence of a role for target cost in designing the required product characteristics, and selling price is an essential guide to cost management. This leads to improving advantage competitive in Sudanese industrial companies. The study recommends a need to increase the awareness of managers of different departments of the importance of the information provided by modern cost systems. Also, attention to applying a total quality cost system for continuous improvement and reducing total cost is needed in companies. [ABSTRACT FROM AUTHOR]

Abstract This paper documents data for global, regional (EU-27), and country-specific (G20 member countries) energy and emission pathways required to achieve a defined carbon budget of between 400 GtCO2 and 500 GtCO2, developed to limit the mean global temperature rise to 1.5 °C, over 50% likelihood. The data were calculated with the 1.5 °C sectorial pathways of the One Earth Climate Model—an integrated energy assessment model devised at the University of Technology Sydney. The data consist of the following six zip-folder datasets (refer to Sect. 2 for an explanation of the data): (1) Appendix folder: Each file contains one worksheet, which summarizes the overall 1.5 °C scenario. (2) Sector folder (XLSX): Each file contains one worksheet, which summarizes the industry sectors analysed. (3) Sector folder (CSV): The data contained are the same as those described in point 2. (4) Sector emissions folder: Each file contains one worksheet, which summarizes the total annual emissions for each industry sector. (5) Scope emissions folder (XLSX): Each file contains one worksheet, which summarizes the total annual emissions for each industry sector—with the additional specificity of emission scope. (6) Scope emissions folder (CSV): The data contained are the same as those described in point 5.

The purpose of the article is to identify the role of trends in cost systems such as activity-based costing systems) ABC (and target cost (TC) to improve competitive advantage for the Sudanese industrial sector. This can help accountants in accuracy when measuring and calculating production and goods. Also, they assist companies in determining the price considering the allowable costs. The practical value of this scientific research lies in three folds. First, the findings will contribute to shedding light on the experience of using some modern cost systems in Giad industrial group companies - in Sudan. Second, they inform officials about the evaluation of these systems and the extent of benefits from them in improving the competitive advantage. Third, the study fills in the gap lack of studies that deal with this topic in the Sudanese setting. The study’s findings indicate the existence of a role for ABC in overhead cost allocation, more accurate product cost, and cost control improvement. This leads to improving advantage competitive in Sudanese industrial companies. Also, it was discovered that the existence of a role for target cost in designing the required product characteristics, and selling price is an essential guide to cost management. This leads to improving advantage competitive in Sudanese industrial companies. The study recommends a need to increase the awareness of managers of different departments of the importance of the information provided by modern cost systems. Also, attention to applying a total quality cost system for continuous improvement and reducing total cost is needed in companies.

With the proliferation of the Industry 4.0 paradigm, the inadequacy of conventional quality management tools has become increasingly apparent. The preliminary investigation presented in this paper focuses on the identification of the Quality 4.0 readiness level of organizations operating in the Czech Republic, Poland, and Slovakia, as well as affecting factors. The study is based on the review of relevant literature. The web-based questionnaire enabling organizations' representatives through Computer-Assisted Web Interviewing (CAWI) to take part in the study was used. Data from 298 completed responses were subjected to comprehensive analysis. Descriptive statistics and hypothesis testing were applied to analyse the data. Small and medium-sized organizations achieve low levels of Quality 4.0 readiness. Large organizations are better prepared. The study confirmed the dependence between the Quality 4.0 readiness level and whether the organization operates in automotive, while automotive organizations achieved a higher level of Quality 4.0 readiness than other organizations. The significant relationship between the Quality 4.0 readiness level and whether the organization has a certified management system was also confirmed. Received data also enabled the identification of the main barriers and benefits of Quality 4.0 implementation perceived by the organizations. The research findings identify the challenges that enterprises face regarding the Quality 4.0 implementation and the necessary support that organizations require. These findings can be a foundation for developing novel research initiatives and implementation programs. The research results contribute to the existing body of knowledge and bring new information and insights into the field of quality digitalization. [ABSTRACT FROM AUTHOR]

This study envisages exploring the role of business competitiveness as a potential moderator in boosting the capacity of the real sector to cause development. Hence, it is proposed that competitiveness policy can be elementary in increasing the development-based productivity of the real sector. Using the panel data of 110 countries between 2006 and 2017, the FGLS estimates show that business competitiveness policy is useful in increasing productivity of service sector and agriculture sector of low- and low-middle-income countries, while it helps increase productivity of the industry sector and agriculture sector of high-income countries. It is evident from the estimates that higher-income countries are extracting higher returns from the competitiveness policy. Surprisingly, competitiveness reaps positive externality as the overall model shows higher returns to competitiveness than income-wise models. [ABSTRACT FROM AUTHOR]

Purpose -- The objective of this study is to examine the factors that impact the value of a company over both the short and long term. These factors include variables such as the company's size, the reputation of the underwriter and auditor, the industry sector in which it operates, and the number of shares outstanding during the initial public offering (IPO). Method -- In this study, a quantitative causality approach with analytical properties is employed as the method of analysis. The population under investigation consists of companies that conducted initial public offerings (IPOs) between the years 2020 and 2022. A sample size of 113 companies is selected using a specific sampling approach for research purposes. To analyze the data, a binary logistic regression model is applied, along with the use of statistical tools. Result -- The conducted research has yielded several findings. Firstly, it indicates that the variable of company size does not have a significant impact. Secondly, the variable of underwriter reputation also does not have a significant effect. Thirdly, the variable of auditor reputation does not significantly influence firm value. Fourthly, the stock variable does not significantly affect firm value. Lastly, the research highlights that the industry sector variable has a significant impact on firm value. Contribution -- The research is expected to contribute to the academic field and benefit capital market players by addressing the factors that should be considered when making investment decisions in the capital market. [ABSTRACT FROM AUTHOR]

This paper documents data for global, regional (EU-27), and country-specific (G20 member countries) energy and emission pathways required to achieve a defined carbon budget of between 400 GtCO2 and 500 GtCO2, developed to limit the mean global temperature rise to 1.5 °C, over 50% likelihood. The data were calculated with the 1.5 °C sectorial pathways of the One Earth Climate Model—an integrated energy assessment model devised at the University of Technology Sydney. The data consist of the following six zip-folder datasets (refer to Sect. 2 for an explanation of the data): (1) Appendix folder: Each file contains one worksheet, which summarizes the overall 1.5 °C scenario. (2) Sector folder (XLSX): Each file contains one worksheet, which summarizes the industry sectors analysed. (3) Sector folder (CSV): The data contained are the same as those described in point 2. (4) Sector emissions folder: Each file contains one worksheet, which summarizes the total annual emissions for each industry sector. (5) Scope emissions folder (XLSX): Each file contains one worksheet, which summarizes the total annual emissions for each industry sector—with the additional specificity of emission scope. (6) Scope emissions folder (CSV): The data contained are the same as those described in point 5.Article Highlights: Scope 1, 2 and 3 emission data for 16 industry sectors—data format was developed with the financial industry specifically for Net-Zero target setting. Industry specific mission data for all G20 member countries, one region (EU27) and globally. Detailled country specific 1.5 °C decabonization pathways for all G20 member countries. [ABSTRACT FROM AUTHOR]

The Chinese government is actively pursuing a low-carbon development model with a clear target of reducing carbon dioxide (CO2) emissions by 2030. This study presents a project-based perspective on CO2 emissions from the industrial sector in the city. The article quantifies and analyzes the project planning by including the entire gross industrial production value, industrial structure, energy intensity, energy structure, and CO2 emission coefficient of the industrial sector's CO2 emissions decomposition model. Monte Carlo simulation and scenario analysis were coupled to evaluate how the city's industrial sector could achieve its peak carbon targets by industry. The expected range of CO2 emissions from the city's industrial sector in 2025, 2030, and 2035, based on the project plan and policies in place, is projected to be between 65.64 and 69.26 Mt, 72.13–78.48 Mt, and 69.32–76.62 Mt. However, the simulations show that there are still considerable uncertainties in reaching the peak carbon target in 2030, necessitating greater government efforts. To achieve the 2030 goal for the city's industrial sector, the paper recommends that the government increase the baseline criteria for industrial structure, energy intensity, and energy structure. This study provides scientific project planning guidance for Chinese cities to successfully achieve the 2030 goal.

Amaç: Çalışmada sanayi sektörü elektrik tüketimi ve sanayi sektörü büyüklüğü arasındaki yapısal ilişki ve olası ters U ilişkisinin araştırılması amaçlanmaktadır. Yöntem: Çalışmada 2004-2019 dönemi için İBBS 3 düzeyi sanayi sektörü elektrik tüketimi ve sanayi sektörü büyüklüğü verilerinden oluşturulan bir panel veri setinden yararlanarak, panel zaman serileri analizleri ile mekânsal panel veri analizleri kullanılmıştır. Bulgular: Elde edilen bulgular, sanayi sektöründen elektrik tüketimine doğru bir nedensellik olduğunu ve mekânsal etkiler altında değişkenler arasındaki ilişkinin ters U şeklinde olduğunu göstermektedir. Bu durum toplam mekânsal etkiler altında sanayi sektörünün büyüklüğünün 280 milyar ABD dolarına kadar ölçek etkisinin, daha sonrasında ise kompozisyon ve teknik etkilerin hâkim olacağını ifade ediyor olabilir. Bunun nedeni olarak 2000 sonrası dönemde hizmetler sektörünün elektrik tüketimi içindeki payının artması ve enerji tasarrufu ile yenilenebilir kaynaklara dayalı enerji üretimindeki artışlar gösterilebilir. Özgünlük: Çalışmada sanayi sektörü elektrik tüketimi ile sanayi sektörü büyüklüğü arasındaki yapısal ilişki ve olası ters U ilişkisi mekânsal etkiler altında araştırılmaktadır.

This study is an original study and adds to the research debate on the impact of small and medium enterprises in generating new jobs, with a special focus on the industry and services sector, as in Kosovo for these sectors still do not there has been special research. The objective of this research paper is presents the impacts of small and medium enterprises have in generating new jobs. To achieve the stated objective and to prove the hypotheses in this research, the OLS regression model has been used whereas the data processing has been done through SPSS. This research paper has been conducted by using secondary data collected by the World Bank and Kosovo Agency of Statistics, for the time period 2012-2018. Results in this research paper from this model show that the industry and services sector affects generating new jobs in Kosovo, therefore there is a positive correlation between the presented variables. Also we can notice a positive correlation between the GDP and employment rate. The results presented in this research paper can be used as a guide for new businesses in the services and industry sector and their impact on the generation of new jobs in Kosovo, as well as efforts to further improve performance in these sectors.

Purpose — The objective of this study is to examine the factors that impact the value of a company over both the short and long term. These factors include variables such as the company's size, the reputation of the underwriter and auditor, the industry sector in which it operates, and the number of shares outstanding during the initial public offering (IPO). Method — In this study, a quantitative causality approach with analytical properties is employed as the method of analysis. The population under investigation consists of companies that conducted initial public offerings (IPOs) between the years 2020 and 2022. A sample size of 113 companies is selected using a specific sampling approach for research purposes. To analyze the data, a binary logistic regression model is applied, along with the use of statistical tools. Result — The conducted research has yielded several findings. Firstly, it indicates that the variable of company size does not have a significant impact. Secondly, the variable of underwriter reputation also does not have a significant effect. Thirdly, the variable of auditor reputation does not significantly influence firm value. Fourthly, the stock variable does not significantly affect firm value. Lastly, the research highlights that the industry sector variable has a significant impact on firm value. Contribution — The research is expected to contribute to the academic field and benefit capital market players by addressing the factors that should be considered when making investment decisions in the capital market.

China's industrial sector dominates the country's total energy consumption, and improving energy efficiency in that sector is crucial to help China reach its energy and carbon dioxide emissions reduction goals. There are many energy efficiency policies in China, but the motivation and willingness of enterprises to improve energy efficiency has weakened. This article first identifies barriers that enterprises face to be self-motivated to implement energy efficiency measures and then categorizes these barriers into four categories: awareness, information, technical capacity, and financial availability. It then reviews international policies and programs to improve energy efficiency, and evaluates how these policies have helped to address the barriers identified. We found that policies and programs in energy efficiency and carbon reduction need to go hand in hand to incentivize companies, and that those policies and programs send clearer signals and help change enterprises' decisions when they are persistent but dynamic. Our specific policy recommendations to China fall under three key categories: identification of energy efficiency potential, workforce development, and market channels for energy efficiency financing. This article is categorized under: Energy and Climate > Economics and Policy Energy Efficiency > Economics and Policy Energy Efficiency > Climate and Environment.

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The study aims to determine the connection between intellectual capital (IC) and financial performance of the Jordanian industrial listed companies. The methodology uses regression models, the IC will be measured using the VAIC model (value-added intellectual coefficient), on the other hand, company performance will be measured using return on equity (ROE). The main model includes financial leverage as a control variable to study the leverage role in the association between IC and return on equity. The study also investigates the incremental information content for intellectual capital components in explaining the change in firm performance. In addition, the size effect is studied to show if the company’s size affects the link between ROE and IC. The sample for this study is 77 Jordanian industrial firms and 788 company-year observations during the period 2006–2020. The study results are as follows: Intellectual capital has an important influence on industrial firm performance; Intellectual capital components have a significant impact on industrial firm performance. In particular, human capital efficiency (HCE) and capital employed efficiency (CEE) have a positive influence on ROE, and structural Capital efficiency (SCE) has a negative impact on firm performance. Lastly, firm size has an effect on the relationship between IC and industrial company performance.

This study examines cost-effective strategies for reducing greenhouse gas (GHG) emissions in Korea's industry sector to achieve the nation's 2050 carbon neutrality goal, using the Global Change Analysis Model (GCAM) integrated assessment modeling (IAM) framework. We find that the iron & steel, cement, and chemical industry segments contribute about 70% of the sector's GHG mitigation efforts to align with 2050 carbon neutrality. Key decarbonization options include electrification of industrial processes, utilization of hydrogen and bioenergy, and adoption of carbon capture and storage (CCS) technologies, although the relative significance of these options varies across the segments. We also demonstrate the dependency of sectoral decarbonization pathways on the availability of CCS and hydrogen technologies, as well as their influence on the development of upstream energy infrastructures, such as electricity and hydrogen production. Our results indicate that limited CCS deployment would necessitate a faster phase-out of fossil fuel-based industrial technologies and quicker decarbonization of the electricity and hydrogen production sectors. Conversely, constrained hydrogen deployment would increase reliance on CCS, placing a greater emission reduction burden on other sectors like electricity generation and buildings. Within the industry sector, limited CCS utilization would force the chemical segment to achieve disproportionately larger negative emissions compared to the constrained hydrogen deployment scenario, as the latter allows for wider adoption of CCS, particularly in the iron & steel segment. Overall, the study emphasizes the need for rapid and extensive transformation of the three key industrial segments to achieve Korea's 2050 carbon neutrality target, with CCS technologies and, to a lesser extent, hydrogen technologies playing a significant role in shaping the industry's decarbonization pathways and the nation's energy systems. [ABSTRACT FROM AUTHOR]

This study compares the performance of Pytorch-based Deep Learning, Multiple Perceptron Neural Networks with Multiple Linear Regression in terms of software effort estimations based on function point analysis. This study investigates Adjusted Function Points, Function Point Categories, Industry Sector, and Relative Size. The ISBSG dataset (version 2020/R1) is used as the historical dataset. The effort estimation performance is compared among multiple models by evaluating a prediction level of 0.30 and standardized accuracy. According to the findings, the Multiple Perceptron Neural Network based on Adjusted Function Points combined with Industry Sector predictors yielded 53% and 61% in terms of standardized accuracy and a prediction level of 0.30, respectively. The findings of Pytorch-based Deep Learning are similar to Multiple Perceptron Neural Networks, with even better results than that, with standardized accuracy and a prediction level of 0.30, 72% and 72%, respectively. The results reveal that both the Pytorch-based Deep Learning and Multiple Perceptron model outperformed Multiple Linear Regression and baseline models using the experimental dataset. Furthermore, in the studied dataset, Adjusted Function Points may not contribute to higher accuracy than Function Point Categories.

It is unclear how sectoral growth in the agriculture, industrial, and service sectors affects inflation, and the topic is also quite rare. Accordingly, the researchers in this paper examine the long- and short-term effects of agriculture, service, and industry sectors on inflation rates. In order to achieve this, the researchers applied an autoregressive distributed lag model from 1975 to 2019. In order to determine the direction of causation, the Granger causality test was conducted. The results clearly demonstrate the negative relationship between agriculture, services, population, and inflation over the long term. In the short run, previous inflation, the service sector, the second lag in population, and the agricultural sector do not reduce inflation. The industrial sector and the first lag of the population can lower inflation rates. Thus, the industry sector in the long run and the service and agricultural sectors in the short run are inefficient at reducing inflation. Inflation and the agricultural sector are causally linked in both directions. Additionally, unidirectional causality runs from industry and the service sector to inflation. Early researchers have not examined the impact of the service, industry, and agriculture sectors on inflation rate, thus offering a unique contribution to policy makers. Panel data are not used to compare the sectoral responsibility for reducing inflation in other African countries with researchers. Practically, the agriculture and service sectors on the short run, along with the industry sector on the long run, both need attention.

Copyright of Journal of Business Economics & Management Research is the property of Bayburt University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present paper explains the dynamics of substitution tensions between fossil energy carriers in Iran: Policy guidelines for gas consumption in the industrial sector on the horizon 2025 using the space model and Kalman filter approach for the years 2006-2019 in the form of quarterly data. Based on the model estimation results; Price and revenue elasticity of kerosene, gasoline, gas oil, furnace oil and liquefied petroleum gas -0.14, -0.07, -0.46, -0.10 and -0.24 and 0.48, / 06 0, 0.17, 0.48 and 0.01. Because the price elasticity of all four products is less than one, increasing the prices increases manufacturers’ costs, and increasing costs slow down the pace of gas replacement. There is a direct relationship between sales tariffs and natural gas demand, which means that with a one percent increase in sales tariffs and liberalization of kerosene, gasoline, gas oil, fuel oil and liquefied petroleum gas prices; Gas demand respectively; 0.46, 0.34, 0.004, 0.17 and 0.11 will increase. As a result, natural gas is a stretchable commodity in the long run. Also, the highest price elasticity and substitution elasticity among petroleum products with natural gas up to the horizon of 1404, respectively; related to gas oil, furnace oil, kerosene, gasoline and liquefied petroleum gas. In other words, as a result of the implementation of the above policies, the share of crude oil in the initial energy supply has decreased from 89.5 to 42.5 percent. Furthermore, the share of natural gas has increased from 8.5 to 63.5 percent. As a result, the country is currently far from the goals set out in the document. [ABSTRACT FROM AUTHOR]

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Introduction: Paid family leave (PFL) has the potential to reduce persistent health disparities. This study aims to characterize differences in access to paid leave by industry sector and occupational class. Methods: The Bay Area Parental Leave Survey of Mothers included respondents 18 years of age or older who worked in the San Francisco Bay Area and gave birth from 2016 to 2017. Using linear probability models, we examined differences in five separate measures of PFL by industry sector and occupational class. We extended our regression analysis to simulate the full pay equivalent (FPE) weeks of leave that would have been taken under hypothetical scenarios of increased uptake and wage replacement rates. Results: Our study included 806 women in private for-profit or non-profit jobs. In fully adjusted models, blue-collar workers were 10.9% less likely to take 12 weeks of paid parental leave versus white-collar workers (95% CI: -25.9, 4.1). Respondents were 19.2% less likely receive 100% of their regular pay if they worked in education and health services (−29.1, −9.3) and 17.0% less likely if they worked in leisure and hospitality (−29.5, −4.4) versus respondents in professional and financial services. Respondents in leisure and hospitality reported 1.6 fewer FPE weeks of leave versus respondents in professional and financial services (−2.73, −0.42) and blue-collar respondents reported an average of 1.5 fewer FPE weeks versus white-collar workers (−2.66, −0.42). In our simulation analysis, when we manipulated rates of uptake for paid leave, the disparities in FPE by industry sector and occupational class were eliminated. Conclusion: We observed substantial inequities in access to paid leave by industry sector and occupational class. These findings underscore the potential importance of universal PFL programs with universal benefits to reduce clear inequities that persist within the labor market today.

Objective: The sustainability of economic growth, the development of the industrial sector, the service sector, the agricultural sector and the oil sector are at the forefront of economic discussions in developing countries. Because economic growth and development is the product of interactions between different economic sectors. The importance of identifying the large economic sector of each country and determining the share of each sector in the future improvement and performance of each economy and country is one of the most important issues studied by economic planners of each country. So that the effect of decisions and policies of each economic sector can have different economic and social effects on the economy of each country. Therefore, the main purpose of this study is to determine the dominant sector among the sectors of agriculture, industry, services and oil in the Iranian economy. Also, the effect of each of these economic sectors on economic growth has been studied and analyzed. Method: In order to determine the dominant sector in the Iranian economy among the economic sectors (agriculture, industry, services and oil), the Herfindahl method has been used. In order to investigate the effect of each economic sector on economic growth, the distributed intermittent auto regressive distributed lag (ARDL) method has been used. The data of the present study from 1978 to 2017 were extracted from the site of the Central Bank of Iran and then examined. Considering that the results of this research can be used in the decision-making process of economic planners, it is applied in terms of the purpose of this research. Findings: The results of Herfindal index show that the service sector is the dominant sector in the Iranian economy in terms of size, which means that the service sector has the largest share in terms of size in terms of GDP. Also, after the services sector, in terms of share, the oil sector, industry sector and agricultural sector have formed other sectors of the Iranian economy, respectively. While the results of the estimate show that there is a positive and significant relationship between value added of services, industry, agriculture and oil with economic growth in the short and long term. On the other hand, the findings of the model with auto regressive distributed lag (ARDL) show that the effect of oil in the short term and services in the long run on Iran's economic growth was greater than other sectors, so that even in the short and long term, respectively The second place in terms of impact after the services and oil sector is on economic growth. Examination of the error correction factor also shows that in each period, 69% of the imbalance in different economic sectors moves towards the long-term value. Conclusion: According to the results of the study, the oil sector can be mentioned as an important part of economic growth. While the agricultural sector has played a very weak role on economic growth during the period under review. So that the agricultural sector, both in terms of size and impact, has the lowest amount of the country's economy.

Aiming at the inconsistency problems on price fluctuation of industry sectors existed in the stock market, clustering analysis is adopted to study the heterogeneity of industry sector. Partial least squares method is used to establish an evaluation index system, and measure the investor sentiment in industry sectors, as well as the impact of investor sentiment heterogeneity on stock returns. It reveals the mechanism and path between the performance of sectors heterogeneity and investor sentiment. The research shows that the heterogeneity of industry sector leads to the same characteristics with investor sentiment, and investor sentiment leads to heterogeneity of returns on sectors. So guiding investor sentiment from the perspective of sectors can help the both sides of the market return to rational trading. [ABSTRACT FROM AUTHOR]

Female employment is a crucial measure especially for developing countries. It increases women empowerment, brings financial solvency, declines poverty rate and gender gap, reduces unemployment rate, and improves living standard and more. The prime goals of the paper are to investigate the impacts of capital formation on three major sectorial (agriculture, industry and service) female employments in six South Asian countries. The panel data set for the six South Asian countries is collected from 1991 to 2018. Fixed effect, random effects model and Hausman test have been employed to conduct the study. To discuss the impacts of capital formation on the three female employment sectors the study is splinted in three models. The econometric outcomes of the first model represent that there is a highly significant strong negative impact of gross capital formation on the agricultural sector. The study identifies that mechanization, structural transformation, declining agricultural land areas through capital formation, and female literacy rate are the key factors for this expected result. On the other side, the empirical results of the second and third models make it clear that gross capital formation has strong and highly significant positive impacts in the industrial and service sectors. Findings of the study confirm that economic growth, improvement of educational level, growth of manufacturing, advertising, marketing, finance, entertainment, telecommunications, media, hospitality sectors, RMG sector, tourism sector, banks, insurance companies, NGOs, trade related services, living standard, and health sector through capital formation are the responsible factors for these desired results in the industrial and service sectors' female employment. [ABSTRACT FROM AUTHOR]

PURPOSE: The aim of the paper is to analyse the importance of both internal capabilities (resources) and external information sources in implementing product, process, marketing and organizational innovations aiming to maximize firm competitive advantage and create value for stakeholders. Furthermore, in particular, we examine the role of public organizations, business networks, firm size, and the industry sector, in the emergence of different types of product, process, marketing, and organizational innovations. The research was based on the typology of innovation (product, process, marketing, and organizational) adopted by the OECD. METHODOLOGY: The paper is based on data from 389 SMEs located in Finland and describes the development of a model for testing the factors that increase the innovativeness of SMEs. The logistic regression model is used as a methodology. Findings: The results show that the creation of novel products, processes and marketing innovation is connected to various external sources of information, such as fairs, the media and the internet. Moreover, the relationship between internal capabilities such as the firm’s know-how increases the marketing and organizational innovativeness of SMEs. Our results demonstrated that the creation of product innovation is positively connected to manufacturing. Furthermore, we find that the creation of novel processes and organizational innovation is related to firm size, such that firms with fewer than 20 employees (smallest firms) were concentrated among non-innovators and companies with more than 20 employees were concentrated among innovators. IMPLICATIONS FOR THEORY AND PRACTICE: The contribution of our study is to analyse to what extent various types of innovation rely on specific information sources. This study also provides suggestions for practice and policymakers. Contrary to expectations regarding our findings, public support organizations were not statistically significant in any innovation model. Therefore, public support organizations should develop better mechanisms to find SMEs with strong motivations to develop new products and market opportunities. ORIGINALITY AND VALUE: This paper provides a new and topical viewpoint for the literature by examining the possible factors explaining the increase in SMEs’ likelihood of implementing product, process, marketing, and organizational innovations. Our study provides comprehensive information on how different stakeholders contribute to the emergence of SME innovation.

The objective of this paper is to investigate the effects of industrialization, technology and labor efficiency on electricity consumption in East African Region especially in Rwanda, Kenya and Tanzania over the period from 1990 to 2019. This study adopts a three-stage approach, we used four different panel unit root tests including Levin, Lin and Chu (LLC); Im, Pesaran, and Shin (IPS); ADF - Fisher Chi-square and PP - Fisher Chi-square. The results reveal that all variables are stationary and integrated with order one. Pedroni's cointegration tests reveals that the variables are not cointegrated while Johansen Fisher and error correction-based panel cointegration tests reveal that all variables are cointegrated with at most one cointegrating equation. The study uses Full Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) to estimate the long run relationship among the variables. We find that the increase in industrialization increases electricity consumption whiles increase in technology and enhanced labor efficiency decreases electricity consumption. The study recommends that countries need to consider the current level and the future GCF in planning of electricity supply and production to meet demand, promote efficient use of innovative technology and improve labor efficiency in the industrial sector.

Purpose of the study: The study looks at the changes in India's outer FDI. It also looks at the difficulties that may occur because of India's Outward Foreign Direct Investment. The Indian economy has been more exposed to foreign money because of liberalisation and globalisation, FDI is critical to a country's economic development. India, as a rising country, is the BRICS' second most desirable FDI destination. India is rated fourteenth in the world in terms of industry production. This occurred because of the implementation of a programme targeted at developing industrial zones and attracting foreign investment. Design/methodology/approach: In this study, the researchers conduct their investigation using secondary data. Secondary sources are employing to gather statistical data, including journals, agencies, and governmental institutions, among others. Findings: The increased drive for reform is coming from developing nations and transforming economies, where many private and state-owned firms are progressively expanding outside through FDI. Companies are developing their activities by investing in international markets to have a regional and global footprint. External FDI from India has expanded quickly since 2005-06 because of India's internal and international export policy liberalisation Originality: The Indian economy has become increasingly open to foreign money. Foreign direct investment (FDI) is crucial to a country's economic growth. Changes in policy settings across nations have had a significant influence on the global economy's outward investment pattern. The goal of this study figures out how much money spend as external FDI and how its categories depending on time and development level. [ABSTRACT FROM AUTHOR]

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It is unclear how sectoral growth in the agriculture, industrial, and service sectors affects inflation, and the topic is also quite rare. Accordingly, the researchers in this paper examine the long- and short-term effects of agriculture, service, and industry sectors on inflation rates. In order to achieve this, the researchers applied an autoregressive distributed lag model from 1975 to 2019. In order to determine the direction of causation, the Granger causality test was conducted. The results clearly demonstrate the negative relationship between agriculture, services, population, and inflation over the long term. In the short run, previous inflation, the service sector, the second lag in population, and the agricultural sector do not reduce inflation. The industrial sector and the first lag of the population can lower inflation rates. Thus, the industry sector in the long run and the service and agricultural sectors in the short run are inefficient at reducing inflation. Inflation and the agricultural sector are causally linked in both directions. Additionally, unidirectional causality runs from industry and the service sector to inflation. Early researchers have not examined the impact of the service, industry, and agriculture sectors on inflation rate, thus offering a unique contribution to policy makers. Panel data are not used to compare the sectoral responsibility for reducing inflation in other African countries with researchers. Practically, the agriculture and service sectors on the short run, along with the industry sector on the long run, both need attention. [ABSTRACT FROM AUTHOR]

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The industry selection effect occurring from the impact of environmental regulation on foreign direct investment (FDI) in China is heterogeneous. Based on the extended game theory model, and by using panel data of 35 Chinese industries from 2005 to 2014, this study constructs a system of simultaneous equations to explore the dynamic effect of environmental regulation on FDI in terms of industry selection decisions. Specifically, three-stage least square analysis method (3SLS) of simultaneous equations is utilized to check robustness of the results under different standards. Results reveal that environmental regulation promotes the technological innovation within the Chinese industry and attract larger foreign capital investment. While the influx of capital further boosts the technological progress, a benign interaction effect was observed between the technological innovation and foreign investment. Findings of our study show that the policy of market borrowing technology is more effective, and the implementation of the new environmental policy will intensify the strategies between managers and enterprises. Results of our study show a positive interaction between R&D funding and foreign capital flows. Enhanced coordination activity within industrial organizations will generate more effective organizational and technological innovation, and attract a large flow of FDI. In addition, industry sample results highlight that a compensation effect of technological innovation in the raw materials and manufacturing industry, though environmental regulation of high-tech industries will generate a balance effect with respect to technological innovation. The government should emphasize on the enhancement of execution and effectiveness of environmental regulation, enhancing FDI and enlightening the synergistic possessions of environmental regulation and FDI. [ABSTRACT FROM AUTHOR]

Copyright of Bingol University Journal of Economics & Administrative Science is the property of Bingol University Journal of Economics & Administrative Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)