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Human–robot collaboration has been incorporated into production and assembly processes to promote system flexibility, changeability and adaptability. However, it poses new challenges to resource allocation and production scheduling due to its intrinsic uncertainty and also the increasing complexity of resources. This paper investigates a stochastic flow shop scheduling problem in the context of human–robot collaboration. The goal is to achieve efficient utilisation of flexible resources including human workers and cobots and take full advantage of human–robot collaboration in production scheduling. A stochastic Cobb–Douglas production function is utilised to evaluate the production efficiency of human–robot collaboration considering instabilities of human performance. A joint chance-constrained programming model is formulated to ensure that the required system performance can be achieved. A CVaR approximation-based approach is proposed to solve the formulated model with mixed-integer variables and a nonconvex constraint. The effectiveness of the formulated model and the efficiency of the proposed solution approach are evaluated via numerical experiments. Computational results show the superiority of our solution approach over three other approaches including Bonferroni approximation, scenario approach and individual chance-constrained programming. [ABSTRACT FROM AUTHOR]

The work, based on microdata, analyzes the role of air transport in shaping the business activity of Russian settlements. The focus is primarily on cities in which the dynamics of air passenger traffic is largely shaped by government subsidies. Gross revenue in constant prices of enterprises of all types operating in a locality is considered as an indicator of economic activity. Based on the concept of the Cobb–Douglas production function, several variants of models have been formed to assess this effect. In order to analyze the stability of the obtained estimates, versions of models with only air transport, as well as models with the full range of available modes of transport for a populated area, were considered. As the main result, estimates of the elasticity of the gross revenue of a populated area based on passenger traffic in air transport were obtained. [ABSTRACT FROM AUTHOR]

Mersin, K. and Mısırlıoğlu, T., 2024. A new approach for calculating ship emissions and energy efficiency of a fleet using the Cobb-Douglas function. Journal of Coastal Research, 40(6), 1182–1188. Charlotte (North Carolina), ISSN 0749-0208. This paper delves into the intricate relationship between fuel consumption and CO2 emissions within the context of maritime transportation, shedding light on a formula developed by Mersin, Misirlioglu, and Alkan for calculating fuel consumption. This formula, which considers factors such as ship displacement and machinery type, offers a nuanced understanding of fuel usage in maritime operations. Furthermore, the Energy Efficiency Design Index (EEDI) is meticulously examined, delineating its mandate of setting minimum energy efficiency standards for various ship types and models based on cargo transported per ton/mile. The EEDI formula is analyzed to facilitate a comprehensive comparison with reference EEDI scores to effectively interpret data. Through this analysis, this paper offers invaluable insights into the environmental ramifications of ship emissions and underscores the critical significance of enhancing energy efficiency within maritime transportation practices. [ABSTRACT FROM AUTHOR]

Elevation can affect agricultural outputs, affecting farms' productivity and efficiency. This article identified the significant production inputs influencing productivity and factors influencing technical efficiency (TE) and determined the average TE scores of Robusta coffee farms at varying elevations in Sultan Kudarat, Philippines. Cross-sectional data from the Mahintana Foundation, Inc. using random stratified sampling and power analysis from September 9, 2021, to January 13, 2022, were used to analyze 604 farms from areas ranging from 0.33 to 1284.18 above mean sea level (amsl), classified as low, medium, and high elevation. Open-Data-Kit-based (ODK) mobile data collection systems were utilized to precisely determine the farms' coordinates and elevation. Using stochastic frontier analysis, results showed that increasing the total fertilizer amount and total trees by 1% significantly increased yield by 0.20% and 0.79%, respectively. Meanwhile, increasing the total land area by 1%, including areas unutilized for coffee farming, decreases total yield by 0.11%. Regarding TE, results showed that TE decreases by approximately 0.58% at high elevations. Meanwhile, increasing net income from coffee farming alone by 1% significantly increases TE by 0.00008%. With an average TE of 0.60, 0.77, and 0.63 in low, medium, and high elevations, farms may be incentivized to improve farming practices to increase their TE further. TE improvement recommendations include promoting coffee-agroforestry systems and ecolabelling at medium elevations, such as shade-grown coffee, to promote sustainable production in Robusta coffee farms by assigning a premium to consumers demanding environmental conservation. [ABSTRACT FROM AUTHOR]

Efforts are underway to balance economic development and ecological preservation by transforming the energy structure. This study uses the Cobb-Douglas production function to examine the relationship between energy and economic growth. Through panel data and regression models, 32 countries are analyzed in terms of global energy consumption and economic development. Countries are further grouped based on energy intensity and economic level to explore dynamic relationships. Previous studies lacked understanding of this relationship under varying conditions, while this study proposes a novel approach. Results indicate a one-way relationship between renewable energy consumption and economic growth. Further analysis reveals that countries with higher energy intensity and economic level experience a negative impact on economic growth from increased renewable energy consumption. These research findings have implications for government decision-making. [ABSTRACT FROM AUTHOR]

The study focused on investment, profitability, and input–output specific technical and scale efficiencies and suggested appropriately for its sustainable development in Andhra Pradesh. Farmers (n = 60) were interviewed, and data were analyzed using descriptive statistics, B-C ratio, C-D production function, and DEA techniques. The results depicted that majority of the farmers' primary occupation was aquaculture and 53% of them were farming on leased land. Yield (kg/ha) was highest for large farmers (5247 kg) followed by medium (5200 kg) and small farmers (4800 kg) which resulted the net incomes of $8771 for large farmers, medium ($7377), and small farmers ($6186). The share of feed cost and medicine cost was higher for large farmers, while feed and other costs were highest for medium and small farmers. Net returns were found to be proportional to the land holdings, while labor days have a negative effect. Inefficiency scores given by the DEA model suggest farmers were able to produce the same level of output with combination of inputs corresponding to the minimum cost of production. Adoption of scientific farming practices and CAA guidelines may ensure sustainable farm income. The DoF, AP has to frame policies for the promotion and monitoring of inland low-saline shrimp culture for the mutual benefit of all stakeholders. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of technological advancements, particularly the integration of the Internet of Things (IoT), on the efficiency and productivity of the postal service industry in Slovakia. By employing the Cobb–Douglas production function, we analyze the relationship between key inputs—capital and labor—and output for six major postal service providers: Slovak Post, Packeta, DHL Express, DPD, TNT Express, and GLS. Using data from 2017 to 2021, this study quantifies the elasticities of capital and labor to assess how IoT adoption influences operational performance. The regression analysis reveals significant variations in input contributions across companies, highlighting the diverse effects of IoT integration. Findings suggest that while some companies benefit more from capital investments in technology, others rely heavily on labor efficiency. These insights offer valuable implications for policymakers and industry stakeholders aiming to optimize resource allocation and enhance productivity through technological innovation. [ABSTRACT FROM AUTHOR]

Bu araştırma, Türkiye’de yeni kurulan teknoloji ve yenilik odaklı fikir aşamasındaki girişimlerin (start-up’ların) değerlemesinde kullanılacak yeni bir yöntem geliştirmeyi amaçlamaktadır. Bu çalışma, start-up’ların fikir veya projelerinin ölçeklenebilirliği, ekibinin niteliği, kurucuların sayısı, ekibin eğitim dereceleri, yatırımının içinde bulunduğu endüstri gibi bazı değişkenleri test etmek suretiyle, değerlerini etkileyen etmenlerin neler olduğunu; bulunan bu etmenlerin değeri ne kadar etkilediğini ve değerlemede işe yarayacak yeni bir yöntem geliştirmeyi amaçlamaktadır. Türkiye’de 2022-2023 döneminde kitle fonlama platformları (KFP) üzerinden tohum aşamasında satılan ya da girişim sermayesi yatırım fonları (GSYF) tarafından birinci turda payı satın alınan start-up’ların yataykesit verilerinin ve Cobb-Douglas üretim modelinin kullanıldığı bu çalışmada, normal en küçük kareler regresyon analiziyle söz konusu start-up’ların değerleri tahmin edilmiştir. Araştırma sonuçları, Türkiye’deki KFP’lerce fonlanan tohum işletmelerin hisselerinin değerleri için yüksek teknolojinin ve proje ekibinin eğitim derecelerinin önemli bir etkiye sahip olduğunu; GSYF’lerin satın aldığı start-up’lar için yapılan değerlemelerde ise, start-up’ların yüksek teknolojiye ve ölçeklenebilirlik özelliklerine sahip projelerinin nispeten daha yüksek etkiye sahip olduğunu göstermektedir. Araştırma sonucu, ABD gibi gelişmiş ülkelerdeki start-up değerlemesinde kullanılan Berkus, puankartı değerleme yöntemi veya risk faktörlerini toplama yöntemi gibi değerleme yöntemlerindeki değer katsayılarının Türkiye’ye uygulanması halinde, çok gerçekçi sonuçlar alınmayacağını; her ülkedeki şirketlerin değer katsayılarının farklı olabileceğini göstermektedir.

Purpose. To characterize consequences of forced migration from Ukraine to European countries, quantifying its impact on economic growth, the number, income of the economically active population, investment and industry of Ukraine, and to develop recommendations for overcoming the negative economic effect of migration. Methodology. The methods of analysis and synthesis, scientific abstraction, statistical analysis, economic and mathematical modeling, and graphical analysis were used. Findings. The article studies the factors that caused forced migration from Ukraine’s to European countries as well as the main differences in migration processes provoked by Russia’s war against Ukraine are substantiated. The economic effects and consequences of its impact on the Ukrainian economy are analyzed. The study is based on statistical data characterizing economic growth (GDP) and the factors that determine it (capital investment, economically active population). On the basis of the CobbDouglas production function with neutral scientific and technological progress or Hicks scientific and technological progress and the use of linear regression analysis methods, the relationship between changes in the number of economically active population and economic growth is established. Originality. A forecast of changes in GDP under the influence of forced migration of the economically active population of Ukraine in 2023 is calculated and three main scenarios of GDP dynamics are developed in accordance with these forecasts. Each of them envisages a significant drop in output under the influence of migration. Practical value. The article proposes ways to address the problem of forced migration in Ukraine’s economy and the consequences of its negative impact on sustainable development based on the experience of European countries. Ways to restore industry and attract investments to Ukraine are substantiated. [ABSTRACT FROM AUTHOR]

India is a predominantly agricultural economy. More than 70% of its population is directly or indirectly involved in agricultural activities. India is one of the foremost producers of spices in the world. According to the Bureau of Indian Standards (BIS), 63 spices are grown in India. Ginger is one of the main spices and plays a vital role in the production and export of the country. Meghalaya's economy is predominantly agriculture-based with 81% of its population depending on agriculture, though agricultural productivity in Meghalaya is very low. This paper analyzes resource use efficiency in ginger production in Meghalaya's West Garo Hills district. The study is based on primary data. The multi-stage random sampling technique was used to select 300 ginger farmers. To estimate resource use efficiency in ginger production, the Cobb-Douglas type of production function was best fitted to the data. Independent variables identified were land (X1), seed (X2), labour (X3), harvesting cost (X4), marketing cost (X5) and others include hoe, dao (wait), digging spades (X6) and dependent variables as production of ginger(Y). Among the inputs used for the production of ginger which had positive and significant influences at the overall level, the MVP to PX ratio was less than one for land (0.07), seed (0.26), human labor (0.08), harvesting cost (0.08), marketing cost (0.13) and others (0.09) indicated under-utilization of these resources in the cultivation of ginger. [ABSTRACT FROM AUTHOR]

Until the Augmented Neo-Classical Growth Model developed by Mankiw, Romer and Weil, growth theories have ignored the human capital factor. This study aims to investigate the impact of health on economic growth in Turkey between 1960-2014 through a production function that includes human capital. Health and education are included in the production function as the two main components of human capital. The Multivariate Auto-Regressive Distributed Lag (ARDL) Bounds Test was conducted for empirical analysis. As a result, a significant long-term cointegration relationship was found between the variables. The results also indicate that a 1% increase in life expectancy at birth leads to a 0.67% increase in GDP, a 1% increase in the number of students per teacher in vocational and technical secondary education leads to a 0.21% decrease in GDP, and a 1% increase in the number of students per teacher in tertiary education leads to a 0.21% increase in GDP. [ABSTRACT FROM AUTHOR]

New Flexible Advertising Model Unveiled: Enhancing Advertising Strategies Researchers have generalized the classical Sethi advertising model (1983) to provide a flexible yet tractable approach to optimizing advertising strategies. Unlike traditional methods, the generalized Sethi advertising model is designed to adapt to different market conditions in various media and markets, offering advertisers greater flexibility. By assuming a constant-returns-to-scale relationship between advertising expenditure and untapped market potential, the generalized Sethi advertising model provides advertisers with more options without sacrificing tractability. The research team has made important breakthroughs by developing practical formulas for determining the best advertising strategies for both individual companies and groups of companies. They have also conducted analyses to better understand how different factors influence these strategies. The generalized Sethi advertising model opens up new opportunities for advertisers to fine-tune their campaigns and reach more customers. This research marks a significant step forward in advertising optimization, giving businesses a valuable tool to achieve better results and make informed decisions in their advertising efforts. We propose a flexible yet tractable dynamic advertising model called the generalized Sethi model to capture different market penetration rates across various media and markets via advertising. Specifically, the generalized Sethi model employs a Cobb–Douglas production function of advertising expenditure and the untapped market share with constant returns to scale. It encompasses some standard dynamic advertising models as particular cases. Moreover, the model's flexibility does not compromise its tractability. We demonstrate it by showing single- and multifirm advertising problems involving Nash and Stackelberg games to admit closed-form expressions for the firms' optimal advertising strategies and value functions under the generalized model. Sensitivity analysis of the model parameters also yields novel economic insights regarding the firms' optimal advertising strategies and value functions. Funding: A. P. Kennedy acknowledges the Hong Kong University Grant Council for their support of him pursuing his PhD at the Chinese University of Hong Kong. S. P. Sethi acknowledges financial support from the Eugene McDermott Chair Professorship. C. C. Siu acknowledges financial support from the Research Grants Council of Hong Kong [Grant "Generalized Sethi Advertising Model and Extensions" (Project UGC/FDS14/P02/20)]. S. C. P. Yam acknowledges financial support from HKGRF-14301321 [Project "General Theory for Infinite Dimensional Stochastic Control: Mean Field and Some Classical Problems] and General Research Fund by the Research Grants Council of Hong Kong-14300123 [Project "Well-Posedness of Some Poisson-Driven Mean Field Learning Models and Their Applications"]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2021.0717. [ABSTRACT FROM AUTHOR]

Environmental degradation occurs during economic development. Green Total Factor Productivity (TFP) was developed by incorporating environmental variables into traditional TFP to measure the efficiency of using technology to produce output, while balancing environmental quality. This study aims to determine the general description of economic development in Indonesia in 2015–2021, estimate economic development, and calculate Green TFP in Indonesia in 2015–2021, know the general description of Green TFP, and the variables that are thought to influence Green TFP in Indonesia in 2015–2021. 2021 and analyzed the variables influencing Green TFP in Indonesia in 2015–2021. The estimation results of the economic growth model showed a trade-off between economic growth and environmental quality in Indonesia. The Green TFP results for provinces in Indonesia are obtained using the Cobb-Douglas production function and panel data regression. The value of Green TFP in Indonesia is stagnant, at approximately 0.002. The analysis of variables affecting Green TFP using panel data regression shows that HDI, government spending on education, electricity consumption, industry share, capital structure, and trade openness have significant effects on Green TFP. [ABSTRACT FROM AUTHOR]

This article has examined the impact of selected macroeconomic variables on economic growth in the Bay of Bengal Initiative for Multi-sectoral, Technical and Economic Cooperation (BIMSTEC). Thus, quarterly data have been considered over a period from 2000 to 2021. The study has taken into consideration the Cobb-Douglas production function as a model specification to examine the above issue. It has been found that agricultural production is an important macroeconomic determinant to justify economic growth in BIMSTEC and its members. However, foreign direct investment is a significant macroeconomic factor for economic growth in BIMSTEC and also in India. Moreover, GDP in Bhutan, Sri Lanka and Thailand is positively and significantly affected by the balance of trade. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Research in Economics, Politics & Finance / Ekonomi, Politika & Finans Arastirmalari Dergisi is the property of Journal of Research in Economics, Politics & Finance 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.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office 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.)

This study investigates the critical role of structural transformation in African economies and its significance for inclusive growth, utilizing the African Transformation Index (ATI). The core focus is to understand how structural transformation influences economic growth and to highlight key factors driving this process. By employing a Cobb-Douglas production function and panel quantile regression analysis on data from 30 African countries from 2000 to 2022, the research aims to fill a gap in the literature on African economic development. The major findings reveal that the ATI positively impacts GDP per capita growth rates, especially at lower quantiles, indicating that structural transformation is vital for inclusive growth. Conversely, diversification negatively affects growth, highlighting the challenges of overly diversified economies. Additionally, export competitiveness and productivity improvements contribute positively to growth, while technology upgrading shows significant impact mainly at lower quantiles. Human well-being is identified as a crucial driver of growth, particularly at middle quantiles. The significance of these findings lies in their policy implications: prioritizing structural transformation, enhancing export competitiveness, improving productivity, and focusing on human well-being are essential for achieving sustainable and inclusive growth in Africa. This research provides empirical evidence on the importance of structural transformation and offers valuable insights for policymakers aiming to foster sustainable development in African economies.

This paper applied the Cobb-Douglas production function to look into the impact of global crude oil prices on agricultural output in Ghana. Annual time-series secondary data spanning from 1980 to 2020 were utilized, sourced from the World Development Indicators and the US Energy Information Administration. The variables employed included agriculture value added per gross domestic product (GDP), international Brent crude oil prices, agricultural employment as a percentage of total employment, Tractors and agricultural equipment, as well as the proportion of land used for agriculture. To investigate the short- and long-term correlations between these variables, the Autoregressive Distributed Lag (ARDL) cointegration technique was employed. A unit root test was performed to evaluate the stationarity of the variables before ARDL analysis. The EViews Statistical/Econometric package facilitated the analysis. The findings from the ARDL cointegration estimates revealed a negative correlation between international crude oil prices and agriculture value added per GDP. According to the model, all variables exhibited cointegration over both the short and long term. Control variables, including agricultural employment as a percentage of total employment and agriculture machinery and tractors, showed a positive correlation with agriculture value added per GDP. However, agricultural land was found to be insignificant in influencing agricultural output.

Copyright of Economic & Regional Studies/Studia Ekonomiczne i Regionalne is the property of Sciendo 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.)

A kinetic model of binary interactions is developed to describe an exchange market consisting of two groups (A and B) of manufacturing enterprises and two types of production factors (capital and labor). The relationship between production factors and output satisfies the Cobb-Douglas production function. The objective of the manufacturing enterprise is to obtain maximum profits. In the multi-agent market, manufacturing enterprises exchange surplus production factors for insufficient production factors. We assume that manufacturing enterprises in group A put all of the production factors into the market, while the manufacturing enterprises in group B have the priority of selecting a suitable percentage of production factors for exchange. A system of linear kinetic equations is developed for two groups of manufacturing enterprises to characterize the evolution of the quantity of exchanged production factors. The effect of various strategies on the price of production factors and the profit of manufacturing enterprises is explored. The findings reveal that the trading strategy of group B significantly impacts the price of production factors and effectively improves the profit under certain conditions. Furthermore, a system of Boltzmann equations for the probability distribution of production factors is presented to describe the price issues. Simulation experiments illustrate how the trading strategy and the elasticity coefficient of output influence the final price of production factors. [ABSTRACT FROM AUTHOR]

The profound impact of climate change on agricultural production, and the government's fiscal expenditure for agriculture, is considered a crucial means to address this challenge. This study utilizes panel data from all prefecture-level cities in Heilongjiang Province from 2000 to 2020. Drawing upon the Cobb-Douglas production function, an economic climate model is constructed to empirically analyze the impact of climate change on grain yield in Heilongjiang Province. Furthermore, the role of fiscal expenditure for agriculture in mitigating the effects of climate change on grain yield is explored. Feasible Generalized Least Squares (FGLS) estimation is employed to address issues of "heteroscedasticity," "autocorrelation within groups," and "cross-sectional contemporaneous correlation" present in the model. The results indicate that climate change has a positive impact on rice and corn yields, while exhibiting a negative impact on wheat yield. The influence of climate change on crop yield is both linear and nonlinear. Specifically, temperature demonstrates a linear relationship with rice and corn yields, whereas precipitation shows a significant inverted U-shaped relationship with rice and corn yields. The impact of climate change on grain production in Heilongjiang Province varies significantly across regions. Fiscal expenditure for agriculture has a significant positive effect on the yield of major grain crops in Heilongjiang Province. In addressing the impact of climate change on grain production, agricultural fiscal expenditure enhances the positive effect of precipitation on rice and corn yields, while diminishing the positive impact of temperature on corn yield. [ABSTRACT FROM AUTHOR]

This paper aims to simulate total factor productivity, following the original proposal made by Cobb and Douglas (1928). Estimates with annual frequency are computed for the United States during two periods, i.e. 1899-1992 and 1933-2019. In the case of Mexico, estimates are computed for the 1993-2015 period. An income distribution in favor of capital in recent decades is found both for the United States and México. Capital share has grown in the United States from 25% in 1899-1922 to 89% in 1993-2019, while for Mexico it has been 82% for 1993-2015. Functional income distribution requires close monitoring. [ABSTRACT FROM AUTHOR]

The industrial sector is a pertinent driving force for economic development in developing countries, including Indonesia. Therefore, the industrial sector more than other industries must be prepared to become a leading sector. One of the industrial sectors growing in the Banyumas district is the food industry, especially cakes and bread. This research aims to analyze the effect of capital, labor, and raw material on the production of the food items and identify the independent variables that influence the production the most. The population of this study is 108 bread and cake business units. The sampling technique used is Stratified Random Sampling based on the number of workers. The data analysis technique used is multiple linear regression which refers to the Cobb-Douglas production function using natural logarithms. The results show that capital, labor, and raw materials partially have a positive and significant effect on production; capital, labor, and raw materials simultaneously have a substantial impact on production; the most influential variable on production is the raw material. The research implies that the bakery industry in Banyumas Regency should use a combination of production factors such as capital, labor, and raw materials optimally to increase production. Furthermore, it is hoped that the Banyumas Regency Government and financial institutions can increase the ease of access to capital to support business development. To increase labor productivity, the government and companies can facilitate to improve their knowledge and skills. [ABSTRACT FROM AUTHOR]

This paper analyzes the development of the activities of small business entities through the fusion of digital technologies in ensuring the social and economic development of Uzbekistan, its significant aspects in the development of the country's economy. In Uzbekistan the economic, social and legal levels of small business entities in organizing their activities through digital technologies were determined. 5 directions of its economic and social support were analyzed based on today's policy, and the advantage of using the digital economy in the activities of small business entities compared to large enterprises was determined. The research employs a confluence of descriptive statistics, panel data regression models, and time-series analysis to unravel the intricate correlation matrix that binds various dimensions of investment outcomes within the country's distinct economic climate. A conclusion was made based on the results of the study of the main economic development indicators of the development of small business entities through digital technologies. In assessing the effectiveness of the development of the activities of small business entities through digital technologies, the effectiveness of digitalization on the activities of small business entities was determined using the Cobb-Douglas production function. Proposals and recommendations were developed according to the forecasting results. [ABSTRACT FROM AUTHOR]

Accurately predicting the growth curve of technological innovations during their product life cycle is essential for a firm's strategic planning and survival in an ever-increasing competitive environment. The dissemination of innovation among prospective customers is commonly measured using the diffusion process. Despite considerable research on modeling the diffusion dynamics of innovation, no sustainable model focuses on repurchasing behavior under the effect of price change and time-varying adoption rate. Consequently, the present study develops a new sales forecast model to analyze the propagation of technological products using the two-dimensional framework that integrates the effect of price change and its continuation time in the market. A Cobb–Douglas function has been utilized to mathematically relate the dynamic price and goodwill of the innovation to the product's value. The dynamic behavior of the adoption rate is described using the concept of change-point. A control chart (or c-chart) is utilized to identify the change-point location in the diffusion process of the technological products. The proposed model is fitted to the historical data from two industries, Electronics and Automobiles, using a non-linear least square (NLS) estimation procedure to demonstrate its practical applicability. The empirical analysis shows that the proposed model fits better than well-established diffusion models. [ABSTRACT FROM AUTHOR]

In this study, we apply a detailed country level data in the 1961–2015 period to investigate the relationship between weather variables, CO2, share of renewable energy sources, gross domestic product, and total factor productivity in a standard Cobb–Douglas production function by using an instrumental variable approach. Our findings suggest that economic growth has been positively affected by temperature and CO2 emissions, while climate vulnerability varies significantly between rich‐poor countries. Furthermore, the negative nexus between renewable sources and CO2 emissions demonstrates its importance for optimal environmental policies design while an inverted U‐shaped relationship for temperature and emissions. [ABSTRACT FROM AUTHOR]

Background: Onions are economically and nutritionally important vegetable crops. Despite advances in technology and acreage, Indian onion growers face challenges in realizing their full productivity potential. This study examines the technical efficiency of onion growers, the factors influencing it, and the constraints faced by those adopting drip irrigation in the Ghod river basin of western Maharashtra. A sample of 480 farmers including those practicing drip irrigation and those not practicing it, was selected from Junnar, Shirur, Parner, and Shrigonda blocks of the basin. The primary data was collected through semi-structured interviews. Analytical tools such as the Cobb-Douglas production function (represents technological relationship between multiple inputs and the resulting output), a single-stage stochastic frontier model, the Tobit model, and descriptive statistics were used to assess the technical efficiency of onion production at the farm level. Results: According to the maximum likelihood estimates of the stochastic frontier analysis, drip adopters exhibited a mean technical efficiency of 92%, while for non-adopters it was 65%. It indicates that the use of drip irrigation technology is associated with higher technical efficiency. The association of technical efficiency and socio-economic characters of households showed that education, extension contacts, social participation, and use of information sources had a positive influence on technical efficiency, while family size had a negative influence on the drip irrigation adopters. For non-drip adopters, significant positive effects were observed for landholding, extension contact, and information source use. The major constraints faced by drip system adopters included a lack of knowledge about the proper operating techniques for drip systems and the cost of maintenance. Conclusion: The differences with inputs associated with two irrigation methods showed that the response of inputs to increase onion yield is greater for farmers who use drip irrigation than for farmers who do not, and are a result of the large differences in the technical efficiencies. These inefficiencies and other limitations following the introduction of drip irrigation, such as lack of knowledge about the proper operations, need to be addressed through tailored training for farmers and further interventions. [ABSTRACT FROM AUTHOR]

This paper analyses the winemaking sector in the Republic of Moldova using econometric models. The use of econometric models in agriculture involves the application of statistical methods and economic theory to analyze and model relationships in the agricultural sector. These models help researchers, policy makers and practitioners to understand the factors that influence agricultural outcomes and make informed decisions. The article presents the results of regression estimations in which the endogenous factor is the volume of overall production in agriculture, but also the volume of production in the wine sector. On the basis of official statistical data of the Republic of Moldova, the Cobb-Douglas production function was estimated, whereas exogenous factors are labor and capital used in agriculture, but also technical and scientific progress observed in agriculture. The function is used for both short-term and long-term forecasts. [ABSTRACT FROM AUTHOR]

Indoor agriculture is an innovative and environmentally sustainable approach to high-quality food production, utilizing advanced technology to reduce water usage by 95% and achieve a 100-fold increase in production per unit of land compared to conventional farming systems. These enclosed systems provide year-round production of pesticide-free fresh food, even in cities with less favourable climates, addressing food deserts and creating employment opportunities in urban areas. However, the industry faces significant challenges, primarily stemming from substantial investment and operating costs, exacerbated by a limited understanding of the input-output relationship within these systems. This study employs a bioeconomic framework to establish a foundational production function based on growth cycle duration (time) and required growing area (space). Through a partial budget analysis, a 19-day production schedule was identified to provide the highest contribution margin to profits. Results set the minimum size of this hypothetical lettuce indoor farm at 273 m2, rendering it suitable for installation in urban areas. The farm harvests 118 kg per day, within an 800 m2 growing area distributed across four vertically stacked shelves. Estimates of economic output sensitivity to exogenous factors in the US context are also presented, along with a comparison between cost-minimizing and revenue-maximizing strategies. [ABSTRACT FROM AUTHOR]

The paper seeks to identify and estimate the effects of knowledge flows and spillovers from R&D, exports, imports and FDI on the productivity of small and medium enterprises (SMEs). The study proposes a modified Cobb-Douglas production function using the CMIE PROWESS database to estimate the effects of knowledge flows of small firms from their own efforts and spillovers. The results are derived from generalized methods of moments estimator (GMM) and the SYS-GMM estimator. The study has been conducted separately for small enterprises (SEs) and medium enterprises (MEs). Knowledge flows from own R&D have unambiguous positive externality. The study presents evidence of a sizable positive spillover from exporting. It does not corroborate the theorized positive impact of FDI spillovers. It contributes to productivity spillover and knowledge management literature in small firms, establishing that R&D and other knowledge flows contribute to productivity through industry-wide spillover effects. The study arrives at a novel understanding of the impact of knowledge flows and spillovers through R&D and trade on SME productivity at the aggregate and disaggregate levels. It also presents counterintuitive results for the impact of FDI spillover on SME productivity. [ABSTRACT FROM AUTHOR]

The process of circular economy is gaining momentum in view of the ongoing nature depletion scenario in the world. The present study develops a co-flow econometric model on Cobb–Douglas aggregate production function framework for the circular economy process. The developed model is estimated using full information maximum likelihood estimation for the Indian copper industry. For the present systemic behaviour sustaining to future, the primary and secondary copper production was found to exhibit counterintuitive behaviour of "overshoot and collapse" beyond the year 2026. It is evidenced that the maximum environmental impact out of circular economy occurs in 2025 and maximum reduction of environmental impact occurs in 2029 in the copper industry. The circular economy induced rebound effect is found to fluctuate between the range of − 2.57 to 2.16 with backfire, partial rebound and super-conservation. The rebound effect is found to be unstable over time. The resource displacements show an overshoot and collapse behavior during the period 2025 and 2027. The overshoot and collapse behaviour needs more exploration to understand the underlying resource dynamics and for designing, experimenting and implementing nature conservation policies as the resource limits are approached. [ABSTRACT FROM AUTHOR]

The development of coffee in West Java has experienced a very rapid increase in production. Coffee is a commodity that has economic value and is a superior commodity that helps the economy and GDP in West Java. Therefore, this research has the purpose of determine the effect factors of production on the output and measuring technical efficiency in the coffee processing industry in West Java. The type of data used is secondary data related to the coffee processing industry for the period 2011 to 2020. The research method used is the Stochastic Frontier Analysis approach using the Cobb-Douglas production function. The results of the study indicate that the coffee processing industry in West Java during the period from 2011 to 2020 is not technically efficient with a coefficient of 0.76. The variable of capital has a significant negative effect on the output produced by producers in the coffee processing industry, while the variable of labor and raw materials has a significant positive impact on the output produced by producers in the coffee processing industry in West Java. [ABSTRACT FROM AUTHOR]

Inefficiency is a problem in the production process, including in the organic farming sector. Over a long term period, this problem can disrupt the productivity of agricultural crops. This research aims to analyze the production and marketing efficiency of organic cabbage farming in the Kopeng agropolitan area, Indonesia. We utilized a Cobb–Douglas production efficiency analysis with the Stochastic Frontier Analysis (SFA) approach. The variables in this study include organic cabbage production, land area, seedlings, organic fertilizers, organic pesticides, and labor. We conducted in-depth interviews with 60 organic cabbage farmers in Kopeng, Indonesia, from January to August 2023. The research results showed that organic cabbage cultivation was economically inefficient in production, technical, and marketing. The use of organic fertilizers, the ability to diversify products on limited land, and the use of pesticides, have not been utilized optimally yet. The results of the marketing efficiency analysis showed that it was efficient. Organic plants were believed to have their market share and to have a higher selling value than non-organic ones. The implication was that the government needed to provide training in producing organic fertilizers and pesticides to reduce production costs so that organic farming could be technically and financially efficient. This research enriched the discussion regarding the need to analyze production and marketing efficiency to find strategies to increase organic cabbage productivity. [ABSTRACT FROM AUTHOR]

In this paper, we focus on estimating output growth and its components attributed to quasi-fixed inputs, variable inputs, and productivity change, while treating variable inputs as endogenous. We consider two approaches. In the classical approach the time trend variable proxies for technical (productivity) change, while in the productivity (proxy variable) approach, we add a "productivity" term which is correlated with the variable inputs. Therefore, estimation strategies in the two models are different. Instead of using a Cobb–Douglas production function, we employ a translog production function to add flexibility. We showcase our theoretical results with Chinese manufacturing as an empirical exercise. [ABSTRACT FROM AUTHOR]

This paper examines whether local human capital spillovers can affect plant productivity in three Association of Southeast Asian Nations (ASEAN) countries using panel data from the World Bank enterprise survey between 2009 and 2015. According to the literature, spillovers in the form of human capital are critical for economic growth. The spillovers exist if plants can produce more in the region with the abundant number of skilled workers given their inputs. This study uses the augmented Cobb-Douglas production function to evaluate the influence of the non-production worker proportion outside the plant which serves as a proxy for skilled workers. The findings indicate that plant production is impacted by spillovers of human capital. This study finds that a 1 percentage point increase in the proportion of nonproduction workers within a region will enhance the productivity of plants in all regions by roughly 7.1-8.9 percent. Moreover, productivity rises are found to be higher for low-tech plants. According to the economic significance of these spillover effects, the value-added per plant will rise by US$ 330,000 or US$ 866.75 million for the manufacturing sector as a whole. According to the findings, policymakers should encourage plants to provide workers with additional training and raise the level of human capital through education. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of technological advancements, particularly the integration of the Internet of Things (IoT), on the efficiency and productivity of the postal service industry in Slovakia. By employing the Cobb–Douglas production function, we analyze the relationship between key inputs—capital and labor—and output for six major postal service providers: Slovak Post, Packeta, DHL Express, DPD, TNT Express, and GLS. Using data from 2017 to 2021, this study quantifies the elasticities of capital and labor to assess how IoT adoption influences operational performance. The regression analysis reveals significant variations in input contributions across companies, highlighting the diverse effects of IoT integration. Findings suggest that while some companies benefit more from capital investments in technology, others rely heavily on labor efficiency. These insights offer valuable implications for policymakers and industry stakeholders aiming to optimize resource allocation and enhance productivity through technological innovation.

[Display omitted] • We study mineral role in total renewable energy and solar electricity generation. • We develop a Cob-Douglas production function for renewable energy production. • We apply the cross-quantilogram method with the dataset's fat-tailed distribution. • We find an increasing return to scale in renewable energy triggered by minerals. • The geopolitical risks heterogeneously impact these energy transition dynamics. Minerals are critical resources in manufacturing and operating renewable energy technologies. Therefore, mineral-producing countries step forward to nestle renewable energy hubs using these resources. Likewise, Saudi Arabia intends to move on an equal footing by designing the national vision 2030 to realize its sustainable development goals. Given this, our objective is to examine the input demand (e.g., mineral production, human capital-augmented labour) for the aggregate renewable energy and solar electricity production within the purview of the decomposed measures of geopolitical risks,' threats' and 'acts' under the Cobb-Douglas production function analysis. To this end, we apply the cross-quantilogram (CQ) technique to examine the causal quantile connectedness between the variables with their fat-tailed distributive feature using monthly data from January 2008 to December 2021. Our findings confirm the increasing return to scale in cumulative renewable energy and solar electricity generation in Saudi Arabia. Specifically, this finding implies that mineral production positively impacts total renewable and solar energy generation at the low and medium quantiles under short, medium and long memories. Also, human capital-augmented labour favourably influences these two clusters of clean energy transitions in all quantiles under entire memories. In addition, the geopolitical risk 'threats' measure elevates, and the 'acts' parameter downsizes these dynamics of energy transformations in whole quantiles. Therefore, we recommend optimizing mineral resources to reach Saudi Arabia's aspirated renewable energy trajectory amid worldwide geopolitical tensions. [ABSTRACT FROM AUTHOR]

The primary goal of the research was to quantify the technical efficiency and to identify its causes in the production of turmeric production in Sheko and Yeki districts. Three hundred sixty sample household heads were chosen using a two-stage random sampling procedure. Descriptive statistics and econometrics models like, Cobb-Douglas and Tobit's models were used to examine efficiency and determination respectively. As a result, the average technical efficiency was 73.72. The average technical efficiency suggests that it is possible to raise turmeric production by 26.28 percent without utilizing additional inputs. Land, labor, oxen, seeds, herbicide, and urea all had a big impact on how much turmeric was produced. The Tobit model revealed that gender, age, household size, the number of plots, and market information substantially impacted technical efficiency. Policies aimed at motivating and strengthening the existing agricultural extension system, and providing appropriate marketing information, are required to improve turmeric growers' production efficiency. [ABSTRACT FROM AUTHOR]

In this work, we delved into advanced modeling of economic relationships using the Cobb–Douglas production function as a theoretical foundation. Our primary goal was to develop an innovative multiple linear regression model by introducing innovations based on the -stable distribution. By adapting the traditional multiple linear regression model, our approach incorporates the -stable distribution to better represent the complexity of relationships between economic variables. This modification enables a better fit for asymmetric distributions and scenarios where data exhibit heavy tails. To assess the performance of our model, we applied it to real financial data. This practical step allowed us to evaluate the effectiveness and predictive capability of our approach in a real-world context, thus offering fresh perspectives for financial data analysis. [ABSTRACT FROM AUTHOR]

In transitional economies characterized by digital finance and uncertainty, the environmental, social, and governance (ESG) impact on enterprise performance has become a core issue in the sustainable development of enterprises. The existing literature does not pay attention to the simultaneous existence of digital finance and economic policy uncertainty in transition countries such as China. This paper introduces ESG as intangible capital into the Cobb–Douglas production function, considers the impact of digital finance and economic policy uncertainty, establishes a theoretical analysis framework, and empirically tests the impact of ESG on enterprise performance using panel data of 1688 listed companies in China from 2011 to 2020. The results reveal that ESG promotes enterprise performance; digital finance strengthens the positive impact of ESG on enterprise performance, and increased economic policy uncertainty strengthens the positive moderating effect of digital finance. Heterogeneity analysis reveals that the impact of ESG on enterprise performance and the moderating effect of digital finance are significant in both the eastern region and the central and western regions, but the former performs better when economic policy uncertainty increases. The research conclusion provides a policy reference for selecting appropriate digital finance policies to promote the sustainable development of enterprises with ESG as the core. [ABSTRACT FROM AUTHOR]

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This paper introduces a novel methodology for estimating carbon total factor productivity based on the Cobb–Douglas production function. The research method introduced in this article expands upon the framework for assessing total factor productivity through the Solow residual method. It unifies the conceptual and methodological aspects of carbon total factor productivity with those of single factor productivity. Utilizing panel data from various provinces between 2010 and 2021, we computed carbon total factor productivity to understand its implications for China in combating global climate change. We demonstrate that (i) we have introduced a method to handle negative coefficients in the Cobb–Douglas production function by incorporating productivity in lieu of input factors during calculations. (ii) Carbon total factor productivity, encapsulating the geometric weighted mean of labor, capital, and carbon productivity, holds notable economic relevance. Further, it serves as an integrative metric comprising carbon productivity intertwined with the mean labor and capital carbon factors. And (iii) the influence of carbon total factor productivity growth on economic progression remains relatively subdued, with escalating labor force growth posing detrimental effects on several provincial economies. Enhancing carbon total factor productivity emerges as an imperative to harmonize robust economic growth with strategic carbon curtailment. Our analytical framework provides nuanced perspectives on productivity determinants, accentuating the thrust towards sustainable evolution amidst climatic challenges. This investigation bears profound significance for policymakers endeavoring to sculpt a carbon-conscious economic paradigm in consonance with global climatic ambitions. [ABSTRACT FROM AUTHOR]

This study provides an econometric methodology to test a linear structural relationship among economic variables. We propose the so-called distance-difference (DD) test and show that it has omnibus power against arbitrary nonlinear structural relationships. If the DD-test rejects the linear model hypothesis, a sequential testing procedure assisted by the DD-test can consistently estimate the degree of a polynomial function that arbitrarily approximates the nonlinear structural equation. Using extensive Monte Carlo simulations, we confirm the DD-test's finite sample properties and compare its performance with the sequential testing procedure assisted by the J-test and moment selection criteria. Finally, through investigation, we empirically illustrate the relationship between the value-added and its production factors using firm-level data from the United States. We demonstrate that the production function has exhibited a factor-biased technological change instead of Hicks-neutral technology presumed by the Cobb–Douglas production function. [ABSTRACT FROM AUTHOR]

This study examines the impact of renewable energy on sustainable development in the Kingdom of Saudi Arabia from 2000 to 2019 and analyzes the kingdom's most essential practices in this field to achieve sustainable development. The Cobb–Douglas production function is used in this study to investigate the impact of renewable energy on sustainable development using ordinary least squares (OLS) estimation. According to the findings, renewable energy consumption has a negative but insignificant effect on GDP. Additionally, traditional energy consumption has a major negative influence on GDP. The findings also demonstrate that fixed capital formulation and technical progress have a significant positive impact on Saudi Arabia's sustainable development. Furthermore, while the labor force has a positive impact on GDP, this effect is not statistically significant. This report provides some recommendations for Saudi government policymakers to reform the country's energy efficiency and consumption technologies in order to reduce energy waste and satisfy the goals of sustainable development. While the labor force is recognized as having a positive influence on GDP, it is notable that this result lacks statistical significance. The suggestions of these findings are mainly applicable to Saudi policymakers, and we present recommendations to improve energy competence and utilization technologies. Specially, our suggestions are intended to reduce energy dissipation and to support the objectives of sustainable development. [ABSTRACT FROM AUTHOR]

Policy adjustments can help strike a balance between economic growth and environmental sustainability, which has increasingly been the heart to nations and regions throughout the World. This paper examines how public investment affects economic growth, energy consumption, and CO2 emissions in eight ASEAN countries: Cambodia, Myanmar, Malaysia, Indonesia, the Philippines, Singapore, Thailand, and Vietnam. Extension of a Cobb–Douglas production function and application of panel cointegration techniques reveal bidirectional Granger causation between public investment and both private development and CO2 emissions from 1980 to 2019. Public investment Granger causes energy usage, the opposite does not hold statistically. More findings from pooled mean group estimations show a mean-reversion dynamic that corrects disequilibria by 14% yearly. State investment crowds in private sector growth, energy use, and carbon footprint. It also finds an inverted U-shaped relationship between public investment and energy consumption, and a U-shaped relationship between public investment and CO2 emissions, indicating complex regional interactions. It is suggested the implementation of public investment policies that enrich green infrastructure projects to foster growth while minimizing environmental impacts, and encourage a strategic approach to public investment for prioritizing environmental sustainability and thus, achieving Sustainable Development Goals 7 to 9 and 11 to 13 in this region. [ABSTRACT FROM AUTHOR]

There have been many research results that show that production factors affect agricultural production. However, a thorough analysis of production factors has not been carried out much. In addition, there has been no comprehensive analysis of the efficiency of potato production factors in Indonesia. Therefore, this study was conducted to determine the production factors that significantly affect potato production and the efficiency of the use of production factors. A Cobb-Douglas production function analysis was carried out to determine the influence of production factors on potato production. Furthermore, an allocative efficiency analysis was carried out to determine the efficiency of using production factors. The study results showed that the production factors of land area, seed, urea fertilizer, NPK fertilizer, fungicide, land cultivation labor, and harvest labor positively and significantly affected potato production. This study also found that only the input factor of planting labor had a significant adverse effect on potato production. In the allocative efficiency analysis, it was found that the use of production factors of seed, urea fertilizer, NPK fertilizer, fungicide, land cultivation labor, and harvest labor is inefficient, so these production factors must be increased in their use. On the other hand, the production factor of the land area shows inefficient results, so the land area must be reduced to achieve optimal efficiency. [ABSTRACT FROM AUTHOR]