Productivity Index Research Articles

Carbon productivity growth in China’s transportation industry: empirical analysis using a global Malmquist-Luenberger productivity index based on an endogenous directional distance function

In China, transportation is one of the fastest-growing industries for CO2 emissions, so scientifically measuring the carbon total factor productivity growth of this industry could provide accurate guidance to achieve sustainable development. To this end, this study proposes an endogenous directional distance function (DDF) approach using a common directional vector based on satisfaction degree, and then integrates it with the global Malmquist-Luenberger productivity index (GMLPI) to measure the carbon total factor productivity growth. We employ this novel endogenous DDF-based GMLPI approach to evaluate and decompose the carbon total factor productivity growth of China’s 30 provincial-level transportation industries from 2010 to 2020. The empirical results show that the carbon total factor productivity of 14 provinces improved during 2010–2020, and 28 provinces from 2015 to 2020. Efficiency improvement and technological progress have become the joint drivers for the carbon total factor productivity growth. Targeted policy implications are provided.

Measuring the productivity of urban commercial banks in China

This paper contributes to the productivity analysis literature by measuring the productivity of 76 urban commercial banks operating in China's 27 regions from 2013 to 2018. A spatial total factor productivity index is constructed using a spatial autoregressive production function. The index is decomposed into the efficiency change and the returns to scale change, and it identifies both spatial direct (feedback) and spatial indirect (spillovers) components. The result confirms positive spatial dependence in the production of urban commercial banks. Additionally, productivity of China's urban commercial banks increases, which is mainly contributed to by the returns to scale change.

Analysis of scale problem using acidizing stimulation in field Z Kalrez Petroleum (Seram) LTD.

The annual decrease in production at well Z occurs due to scale deposits that impede fluid flow. Scale is a production problem due to the mixing of two types of water with different properties so that the solubility limit of the compound in the formation water is exceeded. To overcome the scale, stimulation is carried out with an acidizing method using a type of acid (HCL 10%). Evaluation was conducted to determine the effect of acidizing stimulation on scale based on productivity index (PI), inflow performance relationship (IPR) curve and comparison of stimulation methods. Evaluation of test results after acidizing stimulation of well Z experienced an increase in production. Productivity Index increased from 4.748 bpd/psi to 9.036 bpd/psi. Based on the IPR curve before acidizing, the maximum flow rate (Q max) = 324.107 bpd, increased to Qmax = 769.021 bpd. Based on the Cost Benefit Analysis (CBA), the Acidizing Stimulation method (10% formic Acid) was chosen to overcome the scale problem because the B/C ratio >1 or 1.9 means that for every 1 US$ invested in the Acidizing Stimulation method (10% formic Acid), a savings ratio of 1.9 will be obtained. So it is very reasonable to decide that the Acidizing Stimulation method (10% formic Acid), is feasible and more useful and efficient.

Efficiency Analysis of Life Insurance Companies in Indonesia and Malaysia

This study focuses on measuring the performance of life insurance companies in Indonesia and Malaysia. Input oriented Data Envelopment Analysis (DEA) uses panel data to extract the efficiency score of 5 life insurance companies from Indonesia and 5 life insurance companies from Malaysia for the year of 2015-2019. DEA-based Malmquist Total Factor Productivity (TFP) Index used to measure the efficiency change along the study period. This study utilizes asset and operating expenses as input variables, as for output variables, this study utilizes premium and investment income. Based on an efficiency score computed by DEA, most of the life insurance companies in both countries perform efficiently during the study period. However, life insurance companies in Indonesia still perform more efficiently than Malaysian life insurance companies. The results of the Malmquist TFP Index for life insurance companies in both countries show that there is 2.5% improvement in technical efficiency change, 1.5% deterioration in technology efficiency change, 0.6% improvement in pure efficiency change, 1.9% improvement on scale efficiency change, and 0.9% increase in TFP change. It shows that the main reason for TFP increased is due to improvement of technical efficiency change.

Application of Monte Carlo simulation for the estimation of production availability in geothermal well

Wellbore simulation is one of the methods used in geothermal system performance analysis using a mathematical model of the geothermal system that considers parameters such as operating conditions, feed zone parameters, and well geometry. One of the methods used to perform wellbore simulation is the homogenous method. However, the results may still have a high level of uncertainty. To overcome this, probabilistic methods such as the Monte Carlo method can improve the accuracy of geothermal well production capacity modelling. The Monte Carlo method determines variability and uncertainty in the data being analysed. In determining geothermal well production capacity, the Monte Carlo method can take random samples of various influencing parameters, such as operating conditions, feed zone parameters, and well geometry. By conducting a Monte Carlo simulation, a more comprehensive probability distribution related to well production capacity will be obtained, considering the uncertainties associated with the available data. This research aims to determine the probability of production capacity of a candidate well in a geothermal field by considering uncertainty factors. In this research, a simulation is carried out until it converges using the Monte Carlo method so that the probability value will be obtained. Based on the analysis using the Montecarlo method, the probability of production capacity at the VY-1 Well of Vyatra Field is obtained, namely the P10 value with a large Mwe of 8.31 with an error of 0.102. Next, the P50 value obtained a Mwe value of 11.44 with an error of 0.001. Then P90 was obtained at 14.44 with an error of 0.012. Based on the analysis results, the most influential parameter in determining the production capacity of a Geothermal well is the productivity index value, followed by temperature and reservoir pressure.

The Effects of The Multi-Target Policy on Green Productivity: Evidence from China’s Fossil Fuel Power Plants

We propose the non-radial meta-frontier global Luenberger productivity index, which addresses the issues of technology heterogeneity, slack variable, and linear programming infeasibility, and decompose it based on the technology perspective and factor perspective. With the dataset of China’s power plants from 2005 to 2015, we identify the effects of the multi-targets, including energy-saving targets and [Formula: see text] reduction targets, in the 12th Five-Year Plan on green productivity encompassing all channels of effects. A [Formula: see text] increase in the average energy-saving target cumulatively increases green productivity by [Formula: see text], while a [Formula: see text] increase in the average [Formula: see text] reduction target cumulatively decreases that by [Formula: see text]. In all channels, the technology leadership effect and generation efficiency exhibit sensitivity. Differential effects of the multi-targets on state-owned versus non-stateowned plants imply significant differences in observed production technology.

Technological Change and Productivity Growth in Livestock Systems: Denmark, New Zealand and Uruguay (1870–1970)

ABSTRACT By the end of the nineteenth century, Denmark, New Zealand and Uruguay enjoyed a virtuous integration into the world economy as small, peripheral, export-oriented countries with natural aptitudes for producing and exporting agricultural goods, mainly from livestock rearing. Despite these similarities, the three countries experienced different trajectories in GDP per capita, the volume of exports, and agricultural productivity until 1970. This article aims to study the dynamics of technological change from a neo-Schumpeterian perspective in the livestock systems of the three countries and their impact on agricultural growth from 1870 to 1970. Land and livestock productivity indices are estimated to measure the performance of each country's livestock system. Results verify the existence of differences in the growth rates and levels of productivity of land, meat and dairy in the three countries. Diverse agents (government, academia and the productive sector) and their links were fundamental for adapting to a new technological paradigm and for promoting innovation processes related to land improvements in the livestock systems.

Productivity and energy-efficiency indices for diversified rice (Oryza sativa) based cropping systems in West Central Table Land Zone of Odisha

A long-term field experiment was conducted at Chiplima, Odisha, under irrigated medium land condition during 2006–07 to 2012–13, to evaluate the production potential and economics of 10 rice (Oryza sativa L.)-based crop ping systems. Rice–maize (Zea mays L.)–cowpea [Vigna unguiculata (L.) Walp.] and rice–groundnut (Arachis hypogaea L.)–bottle gourd [Lagenaria siceraria (Molina) Standl.] cropping systems recorded significantly higher average rice equivalent yield (19.55 and 18.57 t/ha, respectively) than the other systems evaluated, the relative production efficiency being 85.8 and 76.5% over the rice–groundnut system. Rice-based 3-cropping systems hav ing groundnut as winter (rabi) crop had higher land-use efficiency (83%). Rice–maize–cowpea recorded the high est irrigation water-use efficiency (230 kg REY/ha), whereas rice–groundnut–bottle gourd recorded the highest ap parent nutrient use efficiency (60.8 kg REY/kg NPK applied). Rice–maize–cowpea also recorded the highest en ergy-use efficiency (5.89), energy-output efficiency (1,240 MJ/ha/day) and energy productivity (0.34 kg REY/MJ). Rice–maize–cowpea had the highest employment generation efficiency (124.7%), followed by rice–groundnut bottle gourd (120.5%) and rice–groundnut–cowpea (120.0%). Rice–maize–cowpea gave the highest net returns of 135,087/ha, followed by rice–groundnut–bottle gourd system ( 111,777/ha). Rice–maize–cowpea system showed the highest system profitability ( 370/ha/day) and crop profitability ( 500/ha/day). This system also gave the highest benefit: cost ratio (2.56), with highest relative production efficiency (85.8%) and relative economic effi ciency (168.5%) compared to rice–groundnut system.

Comprehensive evaluation of spring barley mutants according to their yield components

Background. The need to increase the genetic diversity of barley (Hordeum vulgare L.) is determined by its value and cultivation scope, which is especially important in the context of the changing climate.Material and methods. The study was carried out in 2021 and 2022 at the experimental site of the Lake Kuchak biostation located in Nizhnetavdinsky District, Tyumen Province (57°20ʼ57.3”N, 66°03ʼ21.8”E). Mutant forms were obtained by treating seeds of accessions ʻZernogradsky 813ʼ, Dz02-129 and C.I. 10995 with solutions of the chemical mutagen phosphemide at concentrations of 0.002% (2·10–3 М) and 0.01% (1·10–2 М). The mutants of the fifth (M5) and sixth (M6) generations were evaluated for a set of traits valuable for breeding in comparison with the original forms and reference cultivars ʻAchaʼ and ʻAbalakʼ. The main productivity characters were analyzed in the laboratory, and breeding indices were calculated (ear potential index, Canadian index, ear linear density index, Mexican index, plant productivity index, and Finnish-Scandinavian index).Results and conclusion. Most of the studied mutants under moisture deficit and elevated temperature conditions were superior to the original forms in their productivity characters. Mutant plant samples with stable manifestation of those traits, irrespective of the growing season conditions, were selected. Assessment of the genotype–environment interaction using breeding indices made it possible to identify promising mutants for inclusion in breeding programs. Correlation analysis helped to identify indices closely related to grain yield: Canadian index (r = 0.85), Mexican index (r = 0.76), and plant productivity index (r = 0.70). They can be recommended for selection of stress-resistant barley forms.

ИНДЕКС ФОНДООТДАЧИ: СОВРЕМЕННОЕ СОСТОЯНИЕ И ФАКТОРЫ РОСТА

The scientific article contains an analysis of scientific literature on ensuring the efficient use of fixed assets in enterprises, research on capital productivity and capital intensity, and the development of main directions for the efficient use of fixed capital. The dynamics of the coefficients of renewal and disposal of fixed assets in the economy are presented in graphical form. The information base for the study was data from the official website of the Federal State Statistics Service. The maximum values of the renewal coefficient were observed in 2018, 2019 and 2022, and the minimum in 2015, 2020 and 2021. The maximum values of the retirement rate are presented in 2014, 2015 and 2016, and the minimum in 2019, 2020 and 2021. An econometric study of the capital productivity index showed an inverse and very weak relationship with the value of gross domestic product and the cost of fixed assets (the value of the correlation coefficient (index) (-0.1)): with an increase in the value of gross domestic product and the value of fixed assets in the period under study, no growth was observed capital productivity index. The value of the gross domestic product and the cost of fixed assets have a direct and close relationship (the value of the correlation coefficient (index) is 0.9): the annual growth of the gross domestic product is accompanied by an increase in the cost of fixed assets. A matrix of correlation coefficients (indices) was constructed to calculate the total correlation coefficient (index). The result of calculating the total correlation coefficient (index) (its value is 0.4) showed that there is a direct and weak connection between the capital productivity index, the value of the gross domestic product and the cost of fixed assets: the growth of the capital productivity index is weakly related to the growth of the gross domestic product and the cost of fixed assets funds.

Exploring the optimal integrated multi-trophic aquaculture (IMTA) patterns benefiting culture animals and natural water environment

Despite bringing various benefits, rapid developments in aquaculture have contributed to the eutrophication of natural water environments. Therefore, it is imperative to mitigate nutrient load in natural water bodies while ensuring sustainable development of aquaculture. On the basis, we proposed an integrated multi-trophic aquaculture (IMTA) system, which considered a perfect solution and constructed an optimised IMTA pattern. Silver and bighead carps and freshwater pearl mussels were used as purification organisms. Six experimental groups were established for a land-based enclosure experiment: giant freshwater prawn monoculture group (G); giant freshwater prawn and freshwater pearl mussel polyculture group (GH2); giant freshwater prawn and silver and bighead carp polyculture group (GSB); giant freshwater prawn, freshwater pearl mussel and silver and bighead carp polyculture groups (GSBH1, GSBH2 and GSBH3) in different densities of freshwater pearl mussels. Each group had four replicates. Control of cyanobacterial blooms, productivity index, outputs of total nitrogen and total phosphorus and microbial community composition were studied and compared in different culturing patterns. Results showed that the GSBH1 group had the most obvious comprehensive advantages in the above four aspects (no cyanobacterial bloom occurred; the best comprehensive productivity index of giant freshwater prawn; the abundance of beneficial microorganisms in sediments was the highest; reduced phosphorus emissions in tailwater by 60.34%; the utilisation rates of nitrogen and phosphorus increased by 10.99% and 13.05%, respectively). Even so, however, the GSBH1 group might not be the most optimal IMTA pattern in practice because the mortality rate of the mussels reached 12.33% and the weight gain was −3.66%. Additionally, the presence of freshwater pearl mussel at its lowest density in this experiment had exhibited detrimental impacts on the growth of silver and bighead carps. Therefore, the most optimal IMTA pattern needs to be determined by further research.

Rancang Bangun Mesin Pengaduk Pakan Ternak Bebek Melalui Pendekatan Antropometri Guna Mengurangi Waktu Proses Pengadukan di UD. Hadhita Jaya Makmur

UD. Hadhita Jaya Makmur was established in 1993 and located on Jalan S. Parman, Modopuro Village Rt.03, Rw.07, Mojosari District, Mojokerto Regency. The founder of this company is Mr. Drs.Munasrib, who is known in poultry farming activists, especially ducks. UD. Hadhita Jaya Makmur has ducks with a population of 3000 laying ducks, ducks at UD Hadhita Jaya Makmur produce about 2100 eggs every 2 days in December. UD. Hadhita Jaya Makmur strives to improve the quality of duck eggs by setting a target of feeding ducks as much as 500 kg every day for a population of 3000 ducks that are ready to lay eggs. Nevertheless, the use of manual methods in mixing duck animal feed ingredients has some negative impacts. The process of stirring duck animal feed takes quite a long time, which can reach 40 minute so that workers at UD. Hadhita Jaya Makmur experienced fatigue. One idea to be able to solve the problem is to design an animal feed mixer machine to provide significant results, providing results in accelerating the time of the 500kg per day animal feed stirring process which was originally at UD. Hadhita Jaya Makmur stirred animal feed ingredients in the process still using manual methods with a processing time duration of 43 minutes. After the design of the animal feed mixer machine, the process time of stirring animal feed ingredients to 15 minutes, the magnitude of the reduction in process time also affected the worker productivity index which was originally 19,3% to 55.5%.

Evaluation of the Productivity Performance of BPR for Economic Resilience in East Java

The Rural Bank (BPR) plays a crucial role in the Indonesian banking industry, particularly at the regional level, serving as an alternative financ-ing source for the unbankable population. This research aims to analyse the productivity levels of BPRs in East Java using the Malmquist Pro-ductivity Index (MPI) during the period from 2016 to 2022. The study sample comprises 30 BPRs in East Java. The analysis results indicate that the productivity of BPRs in East Java fluc-tuates from year to year. Moreover, during the COVID-19 pandemic, BPR productivity experi-enced a significant decline. The study provides recommendations for BPR management and regulators to pay more attention to BPR pro-ductivity and decision-making foundations.

A firm-specific Malmquist productivity index model for stochastic data envelopment analysis: an application to commercial banks

In the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a firm-specific, DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment. First, in order to estimate bank-specific efficiency, we employed a two-stage double bootstrap DEA procedure. Specifically, in the first stage, the technical efficiency scores of banks were calculated by the classic DEA model, while in the second stage, the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency. Second, we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance. Finally, an empirical investigation of the Iranian banking sector, consisting of 120 bank-year observations of 15 banks from 2014 to 2021, was performed to measure their efficiency and productivity change. Based on the findings, the explanatory variables (i.e., the nonperforming loan ratio and the number of branches) indicated an inverse relationship with stochastic technical efficiency and productivity change. The implication of the findings is that, in order to improve the efficiency and productivity of banks, it is important to optimize these factors.

Enhancing cotton (Gossypium hirsutum L.) productivity and quality with magnetized ionized water and Bacillus subtilis intervention under film-mulched drip irrigation in saline soil in Xinjiang

ContextSoil salinity stress and limited nutrient availability significantly impede crop production. Addressing these challenges, the activation of irrigation water and soil enhancement strategies have proven increasingly effective in improving crop production in saline soils. In particular, magnetized ionized water technology has been shown to augment the leaching of soil salinity, while Bacillus subtilis has been applied to increase nutrient availability. However, information on the synergistic effects of magnetized ionized water and B. subtilis are presently limited. ObjectiveThis study aimed to investigate the potential of utilizing B. subtilis in combination with magnetized ionized water to enhance cotton (Gossypium hirsutum L.) production and understand its underlying driving mechanism. MethodsA two-year field experiment explored the impact of varying amounts of B. subtilis, with two types of irrigation water [non-magnetized-ionized water (NMIW) and magnetized ionized water (MIW)] on soil conditions (pH, salt accumulation, and nutrient content), and cotton growth (dry matter, nutrient accumulation, seed cotton yield, and quality) in southern Xinjiang's saline soil. The experiment included five B. subtilis levels (0, 15, 30, 45, and 60 kg ha−1) with NMIW (designated as B0, B1, B2, B3, and B4) and MIW (designated as MB0, MB1, MB2, MB3, and MB4). ResultsMIW and B. subtilis significantly (p < 0.05) reduced soil pH and salt accumulation, while B. subtilis significantly (p < 0.01) increased soil residual nitrate nitrogen and residual available phosphorus content in the 0–40 cm soil layers compared to B0. Furthermore, a significant increase (p < 0.05) in cotton dry matter, nitrogen, and phosphorus accumulation was observed with both measures compared to B0. Seed cotton yield (Y), water productivity (WP), and fiber quality index (FQI) also showed significant improvements (p < 0.05). Compared with the NMIW treatments, the MIW treatments resulted in an average increase in Y of 5.7%, WP of 3.7%, and FQI of 20.2%. Similarly, B. subtilis treatments, compared to no B. subtilis treatments, led to an average increase in Y by 10.6%, WP by 6.9%, and FQI by 29.1%. Quadratic function relationships with Y, WP, and FQI were established using B. subtilis amount as an independent variable. The appropriate range of B. subtilis amount under MIW treatment, corresponding to 99.5% of the maximum values of Y, WP, and FQI, was determined to be 51.1–56.4 kg ha−1. ConclusionMIW and B. subtilis have been found to increase nutrient accumulation in cotton by reducing 0–40 cm soil salinity and alkalinity and increasing 0–40 cm soil nutrient content, thereby enhancing cotton production. To optimize the cotton cultivation under film-mulched drip irrigation in saline soil of southern Xinjiang, China, it is recommended to apply 51.1–56.4 kg ha−1B. subtilis under MIW.

Digital Financial Services (DFS) And Productivity of Indian Banking Sector - Empirical Evidence Using Malmquist Productivity Index and Panel Data Regression

Purpose: The aim of this study is to examine the impact of Digital Financial Services (DFS) on the productivity of banking sector in India. Theoretical framework: This research considered various digital banking services offered by bank and how it affects the actual bank performance in terms of productivity, by adopting a two-stage model i.e., Malmquist Productivity Index (MPI) and panel data regression. Design/Methodology/Approach: The empirical study was based on eight-year balanced panel data from 2012 to 2020. The sample of the study consists of forty-four commercial banks from India. This study is completely based on secondary data collected from the website of the database of the Indian economy and the National Payment Corporation of India (NPCI). To achieve the research goals, a two-stage approach has been used. Initially, Malmquist Productivity Index (MPI) was employed to estimate the total factor productivity changes. In the second phase, panel regression analyses were used to study the impact of Digital Financial Services (DFS) on bank productivity. Findings: The findings show that the Digital Financial Services (DFS) variables such as mobile banking, online banking, Automatic Teller Machines (ATM) and Point of Sale (POS) transactions are significantly improved the productivity of the Indian banking industry. Research, Practical &amp; Social implications: The study addresses the issues such as identifications of factors affecting the productivity of banks including Digital Financial Services (DFS). In the world of digital revolution, it analyses whether bank can retain, continue and enhance their performance by offering modern product and services to their customers. Originality/Value: This article has conducted extensive analyses of Digital Financial Services (DFS) and banks' productivity. The authors also provide suggestions for the policymakers for the future implementation of digital banking services.

An overview of productivity management in Ghana

Improving productivity at the individual, enterprise, and national levels is the surest and quickest way to create wealth and enhance the competitiveness and agility of indigenous enterprises. This paper evaluates the extent to which productivity management has made positive impacts on the growth of economies and poverty alleviation. It also identifies stakeholders' roles and strategies in productivity movements in Asia, Europe, Botswana, and Ghana. Results of the study show that Ghana has relatively lower productivity indices than Asian countries. This accounts for one of the factors responsible for the slow growth rate of the Ghanaian economy and the uncompetitive nature of its indigenous enterprises. Recommendations are made to improve productivity levels in Ghana to catalyze the country's efforts towards the attainment of middle-income economy by 2015.

Optimization Method for Fracture-Network Design under Transient and Pseudosteady Conditions Using Unified-Fracture-Design and Deep-Learning Approaches

Summary In unconventional shale and tight reservoirs, the concept of stimulated reservoir volume (SRV) is used to correlate the volume of total injected proppant with well performance. The SRV configuration consists of primary fractures connected to the wellbore and secondary fractures intersecting primary fractures. SRV productivity is determined by fracture conductivity, fracture dimensions, and network complexity, which also vary with time. This work presents an extension of the unified-fracture-design (UFD) approach to account for not only the pseudosteady state (PSS) but also transient flow regimes and ultimately optimize SRV for maximizing well performance. A generalized productivity index (PI) for both the transient and PSS regimes is presented to improve well performance by searching for the maximum PI over time. In addition, a surrogate model is developed to accelerate the optimization. This study demonstrates that the UFD enables the determination of the optimal fracture network conductivity and complexity that contribute to the maximum PI with a given proppant volume. The optimal SRV design is time-dependent until the PSS is reached. The surrogate model not only improves the computational efficiency but also delivers high precision, which means far less computational burden than the traditional parametric-sensitivity analysis.

Research on Evaluation Methods of Black Soil Farmland Productivity Based on Field Block Scale

Black soil plays an important role in maintaining a healthy ecosystem, promoting high-yield and efficient agricultural production, and conserving soil resources. In this paper, a typical black soil area of Keshan Farm in Qiqihar City, Heilongjiang Province, China, is used as a case study to investigate the black soil farmland productivity evaluation model. Based on the analysis of the composite index (CI) model, productivity index (PI) model and various machine learning models, the soil productivity evaluation method was improved and a prediction model was established. The results showed that the support vector machine regression model based on simulated annealing algorithm (SA-SVR), as well as the Gaussian process regression model (GPR), had obvious advantages in data preprocessing, feature selection, and model optimization compared to the modified composite index model (MCI), the modified productivity index model (MPI), and the coefficients of determination (R2) of their modelling, which were up to 0.70 and 0.71, respectively, and these machine learning prediction models can reflect the effects on maize cultivation and its yield through soil parameters even with small datasets, which can better capture the nonlinear relationship and improve the accuracy and stability of yield prediction, and is an effective method for guiding agricultural production as well as soil productivity evaluation.

An integrated framework for decomposing the eco-Malmquist productivity index

ABSTRACT The relevant study employs the conception of the Malmquist productivity index to develop eco-productivity measures alongside various decompositions. The analysis utilizing the frontier approach presents various eco-productivity components under the supporting cone and best practice eco-technology. The various eco-productivity components are presented and estimated in an illustrative empirical application for the U.S. states over two distinct periods (2000–2010 and 2010–2019). Our findings suggest that eco-productivity levels across the US states have improved over the two sample periods. This could be attributed to the increased eco-technological change levels.